JP7808662B2 - system - Google Patents

Description

The technology disclosed herein relates to a system.

Patent document 1 discloses a persona chatbot control method executed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Japanese Patent Application Laid-Open No. 2022-180282

Currently, when looking for employment, changing jobs, or planning a career, it is difficult to obtain a comprehensive understanding of information such as the average annual salary for one's occupation, regional salary levels, industry trends and demand forecasts, and factors that affect income based on skills and experience. To obtain this information, it is necessary to find multiple sources of information and compare and analyze each one, which is time-consuming and laborious.

This invention provides a system that calculates the average annual salary for an occupation and regional salary levels when a user inputs the name of the occupation and related information, and also provides information on industry trends, demand forecasts, and factors that affect income based on skills and experience. This allows users to obtain the information they need in a centralized location, enabling more appropriate career planning.

1 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a first embodiment. 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. 10 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a second embodiment. FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. FIG. 10 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a third embodiment. FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. 1 shows an emotion map onto which multiple emotions are mapped. 1 shows an emotion map onto which multiple emotions are mapped. FIG. 10 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. FIG. 10 is a sequence diagram showing a processing flow of the data processing system in Application Example 1 of Form Example 1. FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2. FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a third embodiment of the third form example. FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined.

Below, an example of an embodiment of a system relating to the technology disclosed herein will be described with reference to the accompanying drawings.

First, let me explain the terminology used in the following explanation.

In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, a processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose Computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

In the following embodiments, coded random access memory (RAM) is memory in which information is temporarily stored and is used as work memory by the processor.

In the following embodiments, the coded storage refers to one or more non-volatile storage devices that store various programs, parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

In the following embodiments, a communication I/F (Interface) with a symbol is an interface that includes a communication processor, an antenna, etc. The communication I/F controls communication between multiple computers. Examples of communication standards that can be applied to the communication I/F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

In the following embodiments, "A and/or B" is synonymous with "at least one of A and B." In other words, "A and/or B" means that it may be just A, just B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and/or B" also applies when three or more things are expressed connected by "and/or."

[First embodiment]

Figure 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I/F 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

The reception device 38 is equipped with a touch panel 38A, a microphone 38B, etc., and receives user input. The touch panel 38A detects contact with an indicator (e.g., a pen or finger) to receive user input via the indicator. The microphone 38B detects the user's voice to receive user input via voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

The output device 40 is equipped with a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible by the user 20 (e.g., audio and/or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54.

Figure 2 shows an example of the main functions of the data processing device 12 and smart device 14.

As shown in FIG. 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

"Example 2"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their occupation name through the system's user interface. This user interface can be provided through a web browser or dedicated application.

Step 2: Based on the entered occupation name, the system retrieves information on the corresponding occupation from a database. This database includes information such as the average annual salary for each occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3: Based on the information obtained, the system calculates the average annual salary and salary levels in each region. It also simultaneously obtains industry trends, demand forecasts, and factors that affect income based on skills and experience. Step 4: The system displays the calculated and obtained information to the user. As a specific example, if the user enters "software engineer," the system will display the average annual salary for software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

(Example 1)

Next, we will explain Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous occupational information systems had the problem of making it difficult for users to quickly and accurately obtain detailed information even when they entered the name of an occupation. In particular, they were unable to provide a wide range of information in a unified manner, such as average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for transmitting the input information to the server, means for the server to obtain information about occupations from a database, means for calculating average annual income and regional salary levels based on the obtained information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, and means for displaying the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations.

"Means for users to input their occupation name and related information" refers to means that provide an interface for users to input their occupation name and related information, and is realized through a web browser or dedicated application.

"Means for sending input information to the server" refers to the means for sending the occupation name and related information input by the user to the server, and is realized using a communication protocol such as an HTTP request.

"Means by which the server retrieves information about occupations from the database" refers to the means by which the server executes queries against the database and retrieves information about occupations, and is realized using database technologies such as SQL or NoSQL.

"Means for calculating average annual income and regional salary levels based on acquired information" refers to the means by which the server calculates average annual income for each occupation and regional salary levels based on information acquired from the database.

"Means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience" refers to a means by which the server analyzes industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and provides these to users.

"Means for displaying calculated/obtained information to the user" refers to the means by which the server displays calculated/obtained information to the user through a user interface, and is realized using web technologies such as HTML, CSS, and JavaScript (registered trademark).

This invention is a system that allows users to input occupational titles and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. This system operates in cooperation with a server, terminal, and user.

Providing a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their job title and related information through this interface.

Accepting user input

The user enters their occupation and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server.

Submit input data

The device sends the occupation name entered by the user to the server. This is done via an HTTP request. Specifically, the input data is sent using the JavaScript fetch API.

Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it uses an SQL query to retrieve information about the occupation.

Data calculation and processing

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

Displaying information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

Specific examples and prompt sentence examples

As a concrete example, a user opens a web browser and types "software engineer" into the provided interface. The server retrieves information about software engineers from the database and calculates and displays the following information:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

An example prompt might be, "Please tell me the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily obtain detailed information about occupations.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Provide a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their occupation name and related information through this interface. The input includes the occupation name and related information, and the output is the data entered by the user.

Step 2: Accept user input

The user enters the job title and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server. The input includes the job title and related information entered by the user, and the output is the input data sent to the terminal.

Step 3: Send input data

The device sends the occupation name entered by the user to the server. This transmission is performed via an HTTP request. Specifically, the input data is sent using JavaScript's fetch API. The input includes the occupation name entered by the user and related information, and the output is the data sent to the server.

Step 4: Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it retrieves information about occupations using an SQL query. The input includes the occupation name sent to the server, and the output is the occupation information retrieved from the database.

Step 5: Calculate and process data

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

The input includes occupational information obtained from the database, and the output is various calculated information.

Step 6: Display information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

The input includes various calculated information, and the output is the information displayed on the user interface.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

In conventional occupational information systems, even if a user inputs the name of an occupation and related information, the information is simply displayed in text format, making it difficult for users to obtain information in a format that is intuitively easy to understand. Furthermore, because occupational information is not provided in virtual environments, users are unable to search for occupational information within virtual spaces.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual salary of the occupation and the salary level for each region based on the input information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, means for displaying occupational information within the virtual environment, and means for the user to acquire occupational information while moving within the virtual environment. This allows the user to intuitively search for occupational information within the virtual space and acquire information in an easy-to-understand format.

"User" refers to an individual or corporation that uses the system to enter and obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, such as location, skills, years of experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that shows a prediction of future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to the number of years and type of practical experience in a particular occupation.

"Income variables" refers to factors that cause income to fluctuate in a particular occupation, including skills and experience.

A "virtual environment" is a virtual space created using computer technology in which users can interact.

"Display means" refers to a method or device for visually presenting information to the user.

"Means of movement" refers to methods or devices that allow a user to move freely within a virtual environment.

A system for implementing this invention allows users to input occupational titles and related information, and based on that information, calculates the average annual salary for the occupation and regional salary levels, and provides industry trends, demand forecasts, and factors that affect income based on skills and experience. Furthermore, this information is displayed within a virtual environment, allowing users to obtain occupational information while moving around within the virtual environment.

Hardware and software configuration

Hardware: Smartphone, head-mounted display

Software: Flask (a Python web framework), database (a Python dictionary was used as a dummy database)

System Operation

1. User input:

Users use a smartphone or head-mounted display to enter their job title and related information within the virtual environment. For example, a user might enter "software engineer."

2. Data acquisition and calculation:

The server retrieves relevant occupational information from a database based on the entered occupation name, including average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Displaying information:

The server displays the retrieved information to the user within the virtual environment. The user can intuitively explore this information while moving around within the virtual environment.

Specific examples

When a user types "software engineer" in the virtual store, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 7.5 million yen, Osaka: 7 million yen, Fukuoka: 6.5 million yen

Industry Trends: Increasing Demand

Demand forecast: 20% increase over the next five years

Factors that affect income: years of experience, skill set

Example prompt

Please enter your job title: Software Engineer

This system allows users to intuitively search for occupational information in a virtual space and obtain information in an easy-to-understand format.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The user uses a smartphone or head-mounted display to input their job title and related information within the virtual environment. The input information is then sent to the server. The input data includes the job title (e.g., "software engineer") and related information (e.g., region, skills, years of experience).

Step 2:

The server retrieves the relevant occupational information from a database based on the received occupation name. Specifically, it searches the database using the occupation name as a key to retrieve average annual income, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. The input data is the occupation name, and the output data is a set of occupational information.

Step 3:

The server processes the data based on the acquired occupational information. For example, it converts regional salary levels into a format that makes them easier to compare, and graphs industry trends and demand forecasts. The input data is a set of occupational information, and the output data is the processed occupational information.

Step 4:

The server converts the processed occupational information into a data format for display within the virtual environment. Specifically, it generates data for display as 3D models and interactive UI elements. The input data is the processed occupational information, and the output data is the data for display.

Step 5:

The user explores the displayed occupational information while moving around the virtual environment. The user's movement information is sent to the server in real time, and the server updates the display content accordingly. The input data is the user's movement information, and the output data is the updated display content.

Step 6:

If the user wants more information about a specific occupation, they enter an additional prompt statement. The server retrieves more detailed information from the database based on this prompt statement and displays it in the virtual environment. The input data is the additional prompt statement, and the output data is the detailed occupation information.

Step 7:

When the user finishes searching for job information, the server saves the session data so the user can access it again later. The input data is the session data, and the output data is the saved session data.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

With conventional occupational information systems, even if users entered the name of an occupation, it was difficult to quickly and accurately obtain detailed salary information, industry trends, demand forecasts, or factors that affect income based on skills and experience. There was also a lack of ways to provide this information to users in an easy-to-understand manner. This meant that users were unable to obtain sufficient information for occupational selection and career planning, making it difficult for them to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes: a means for the user to input the name of an occupation and related information; a means for transmitting the input information to the server; a means for the server to obtain occupational information from a database; a means for calculating average annual income and regional salary levels based on the obtained information; a means for obtaining industry trends, demand forecasts, and income fluctuation factors based on skills and experience; and a means for providing the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations, enabling them to make appropriate decisions when choosing an occupation or planning their career.

"User" refers to an individual or organization that uses the system to enter occupational information and obtain the necessary information.

"Occupation name and related information" refers to the name of the occupation and information related to that occupation that the user enters into the system.

A "server" is a computer system that receives information sent by users, retrieves the necessary information from a database, processes and calculates the data, and provides it to users.

A "database" is an information management system for storing data such as occupational information, salary information, industry trends, demand forecasts, and factors that affect income based on skills and experience.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average or median salary for a particular occupation in each region.

"Industry trends" refers to information about the current situation and future predictions in a particular industry.

"Demand forecasting" is the prediction of future demand for specific occupations or skills.

"Skill- and experience-based income variables" are factors that show the impact that specific skill sets and years of experience have on income.

"Means of providing information" refers to the methods and technologies used by the server to communicate the information it has acquired and calculated to the user.

"Means of displaying information" refers to methods or technologies that allow users to visually confirm information.

This invention is a system that allows users to input occupation names and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. The system includes a user interface, a server, a database, and a means for displaying information.

The user enters their occupation name using a web browser or dedicated application. For example, they can use a web browser such as GOOGLE CHROME (registered trademark) or Mozilla Firefox, or a dedicated mobile application. Once the user enters their occupation name, the device sends this information to the server. Specifically, the data is sent using an HTTP request.

The server retrieves the corresponding occupation information from a database based on the received occupation name. For example, it uses a database such as MySQL (registered trademark) or PostgreSQL. The server performs the following data processing and calculations based on the retrieved information:

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

This information is sent from the server to the device and displayed to the user. The device then displays the results received from the server to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java (registered trademark) skills are highly valued

As a concrete example, consider the case where a user enters "software engineer." The user enters their occupation in a web browser using Google® Chrome. The device sends this information to a server, which retrieves information about software engineers from a database. The server calculates the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, and sends this information to the device. Finally, the device displays this information to the user.

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

Using this prompt, the generative AI model can obtain the necessary information and provide it to the user.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

User enters occupation name

The user enters their occupational name using a web browser or dedicated application. For example, they open Google Chrome, access the system's web page, and enter "software engineer" in the input field. The input data is their occupational name.

Step 2:

The device sends the input data to the server.

The device sends the occupation name entered by the user to the server. Specifically, it sends data using an HTTP request. The input is the occupation name entered by the user, and the output is the occupation name data sent to the server. For example, the device sends the following JSON-formatted data to the server:

json

{

"Occupation": "Software Engineer"

}

Step 3:

The server retrieves occupation information from the database.

The server retrieves the corresponding occupation information from the database based on the received occupation name. The input is the occupation name data sent to the server, and the output is the occupation information retrieved from the database. For example, run the following SQL query using a MySQL database:

sql

SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer';

Step 4:

The server processes and calculates the data.

The server performs the following data processing and calculations based on the acquired data. The input is occupational information acquired from the database, and the output is the processed and calculated results.

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

Step 5:

The server sends the results to the device.

The server sends the processed and calculated results to the terminal. The input is the processed and calculated results, and the output is the resulting data sent to the terminal. Specifically, the following JSON-formatted data is sent as an HTTP response:

json

{

"Average annual income": 7 million yen,

"Salary levels by region": {

"Tokyo": 8 million yen,

"Osaka": 7.5 million yen,

"Fukuoka": 7 million yen

},

"Industry Trends": "Demand is increasing due to advances in AI technology",

"Demand forecast": "20% increase over the next five years",

"Income fluctuation factors": "Python and Java skills are highly valued"

}

Step 6:

The device displays the results to the user.

The terminal displays the results received from the server to the user. The input is the result data sent from the server, and the output is the information displayed to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

With conventional career information systems, it was difficult for users to obtain detailed information about careers in real time, especially in a virtual environment. Furthermore, there was a lack of means to display information using smart devices, limiting the user experience. This meant that users were unable to obtain sufficient information when choosing a career or planning their career, making it difficult to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for calculating the average annual salary of an occupation and regional salary levels based on the input information, means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience, means for users to obtain information about occupations in real time within the virtual environment, and means for displaying the information via a smart device. This allows users to obtain detailed information about occupations in real time within the virtual environment and visually confirm it via a smart device.

"User" means an individual or corporation that uses the system to input and obtain occupational information.

"Occupation name" is a name used to identify a specific occupation.

"Related information" refers to detailed data and attribute information related to an occupation.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries for occupations in a particular region.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that shows future demand prospects for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

A "virtual environment" is a virtual space or environment created using computer technology.

"Real-time" means that data and information are processed immediately and provided without delay.

"Smart device" refers to an electronic device with internet connectivity and advanced computing capabilities.

"Means for displaying information" refers to a method or device for visually providing information to the user.

The system for implementing this invention includes a server, a user terminal, and a smart device. The specific configuration and operation of the system are described below.

System Configuration

1. Server:

Hardware: Any cloud server (e.g., AWS (registered trademark) EC2)

Software: Python, Flask, SQLite

Function: Accepts user input of occupation name and related information, retrieves relevant occupation information from a database, and calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

2. User device:

Hardware: Smartphones, tablets

Software: Web browser or dedicated application

Function: The user enters their occupation and related information and displays the information retrieved from the server.

3. Smart Devices:

Hardware: Head-mounted display (e.g., Oculus Quest)

Software: Unity (head-mounted display application development)

Function: Allows users to obtain and visually display career information in real time within a virtual environment.

Data processing and calculation

The server receives the occupation name and related information entered by the user and performs the following processes.

1. Retrieving information from the database:

Retrieve the relevant occupation information from the SQLite database.

2. Information Calculation:

Calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Information provision:

The calculated information is sent to the user's terminal and smart device.

Specific examples

When a user types "software engineer" in the virtual environment, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 6.5 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase by 2025

Skill and experience-based income variables: AI and cloud technology skills are highly valued

Example prompt

Occupation: Software Engineer

Information obtained: average annual salary, regional salary levels, industry trends, demand forecasts, and factors affecting income based on skills and experience.

In this way, users can obtain detailed information about their occupation in real time within the virtual environment and visually view it via their smart device.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Users enter their occupation and related information.

Input: The user enters a job title (e.g., software engineer).

Operation: Enter your occupation and related information through the user's device interface.

Output: The entered occupation name and related information are sent to the server.

Step 2:

The server receives the entered information.

Input: Occupation name and related information sent from the user's device.

How it works: The server uses Flask to receive requests from users.

Output: The received occupation name and related information are processed within the server.

Step 3:

The server retrieves the relevant occupation information from the database.

Input: Received job name.

How it works: The server queries the SQLite database to retrieve information about the corresponding occupation.

Output: Average annual salary for occupations, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience are obtained.

Step 4:

Data processing and calculations are performed based on the information obtained by the server.

Input: Occupation information retrieved from the database.

How it works: The server uses Python to calculate average annual income and regional salary levels, and analyzes industry trends, demand forecasts, and factors that affect income based on skills and experience.

Output: Calculated and analyzed occupational information.

Step 5:

The server sends the calculated and analyzed information to the user's terminal and smart device.

Input: Calculated and analyzed occupational information.

How it works: The server uses Flask to send information to user terminals and smart devices.

Output: Occupation information is sent to the user's terminal and smart device.

Step 6:

Displays information received by user terminals and smart devices.

Input: Occupation information sent from the server.

How it works: The user's device displays information using a web browser or dedicated application, and the smart device uses Unity to visually display information within the virtual environment.

Output: Users can view detailed occupation information in real time.

Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

"Example 2"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their job title and related information into the system.

Step 2: Based on the information entered, the system calculates the average annual salary for each occupation and the salary level for each region.

Step 3: The system provides industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Step 4: The emotion engine recognizes the user's emotions.

Step 5: The emotion engine adjusts the way average annual salaries and regional salary levels are displayed based on user sentiment.

Step 6: The emotion engine uses user sentiment to adjust how it displays industry trends, demand forecasts, and income variables based on skills and experience.

(Example 1)

Next, we will explain Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional occupational information systems had the problem that even when users input the name of an occupation and related information, the information provided was uniform and could not be flexibly displayed according to the user's emotions or level of understanding. Furthermore, when providing detailed information such as industry trends, demand forecasts, and factors that affect income based on skills and experience, users could feel stressed and find it difficult to understand the information.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means for recognizing the user's emotions; and means for adjusting the display method based on the recognized emotions. This enables flexible information provision according to the user's emotions and level of understanding, making it easier for the user to understand detailed information about occupations without feeling stressed.

"User" refers to an individual or organization that uses the system to enter their occupational title and related information and obtain information.

"Occupation name" is the name that indicates a specific occupation and is part of the information that a user enters into the system.

"Related information" is additional information related to the occupation title that users can enter into the system.

"Means" refers to a method or device for achieving a specific function or purpose.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries by region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecasting" refers to predicting future demand for a particular occupation or industry.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to work experience and history in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, region, industry trends, etc.

An "emotion engine" is a technology that recognizes a user's emotions and adjusts the system's behavior and display methods based on those emotions.

"Means for adjusting the display method" refers to a method or device for changing the display format of information based on the user's emotions.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their job title and related information using a web browser (e.g., Google Chrome) or a dedicated application (e.g., iOS app). The user interface is built using web technologies such as HTML, CSS, and JavaScript.

Database

The server retrieves information about the corresponding occupation from a database (e.g., MySQL) based on the occupation name entered by the user. The database stores information on the average annual salary for each occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Information calculation

The server calculates the average annual salary and salary levels for each region based on information obtained from the database. For example, it calculates the national average annual salary and then calculates the difference between regions.

Get industry trends and demand forecasts

The server sends requests to external APIs (e.g., economic data APIs) to obtain information on industry trends, demand forecasts, and income fluctuation factors based on skills and experience. It then analyzes the obtained data and prepares the information to provide to the user.

View information

The server displays the calculated and acquired information to the user. For example, it displays it in graph or table format on a web browser. Users can check the average annual salary of software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Adjusting display methods using the emotion engine

The server uses an emotion engine (e.g., emotion recognition software) to recognize the user's emotions. If the emotion engine determines that the user is feeling stressed, the server adjusts the way it displays information, for example, by presenting it graphically or explaining it in simpler terms.

Specific examples

If the user types "software engineer," the server displays the following information:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Furthermore, if the emotion engine determines that the user is feeling stressed, the server will display this information graphically or explain it in simple terms.

Example prompt

"Please tell me the average annual salary of software engineers, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily get detailed information about jobs.

The flow of the identification process in Example 1 will be explained using Figure 15.

Step 1:

Users enter their job title and related information using a web browser or dedicated application.

Enter: Occupation or related information (e.g., "Software Engineer")

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the occupation "Software Engineer" and clicks the submit button.

Step 2:

The server retrieves relevant occupation information from the database based on the occupation name entered by the user.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Specific operation: The server sends the query "SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer'" to the database and retrieves the results.

Step 3:

The server calculates the average annual salary and salary levels for each region based on information obtained from the database.

Input: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Output: Calculated average annual income and salary levels for each region

Specific operation: The server analyzes the data it acquires and calculates the national average annual salary and salary levels by region.

Step 4:

The server sends requests to external APIs to obtain industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Industry trends and demand forecast data obtained from external APIs

Specific operation: The server sends a request to an external API to obtain industry trends and demand forecast data.

Step 5:

The server displays the calculated and obtained information to the user.

Input: Calculated average annual salary, regional salary levels, industry trends and demand forecast data obtained from external APIs

Output: Information displayed to the user (e.g., occupational information displayed in graph or table format)

Specific operation: The server displays the information in graphs and tables on the web browser.

Step 6:

The server uses an emotion engine to recognize the user's emotions and adjust how they are displayed.

Input: User emotion data (e.g., whether they feel stressed)

Output: Tailored display (e.g., graphical display, simple explanation)

Specific operation: The server uses an emotion engine to analyze the user's emotions and displays information graphically or explains it in simple terms.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Traditional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, based on the occupation name and related information entered by the user. However, they lack the ability to adjust the way information is displayed based on the user's emotions. Furthermore, there is a lack of means to provide information visually within a virtual space, making it difficult to provide information in a way that is intuitively easy for users to understand.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for visually displaying occupation information within a virtual space. This makes it possible to adjust the information display method according to the user's emotions and provide information visually within a virtual space.

"User" means an individual or corporation that uses the system to enter occupational information and obtain related information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" refers to information related to the job title, such as region, skills, experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" refers to information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that predicts future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to practical experience in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, etc.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Virtual space" is a virtual space generated by a computer, an environment in which users can visually view information.

"Visually displaying" means presenting information to the user in a graphical format.

As an embodiment of this invention, we provide a system that allows users to input their occupation name and related information and visually confirm that information in a virtual space. Specific embodiments are described below.

System Configuration

The system consists of the following main components:

1. User terminal: A device such as a smartphone or head-mounted display that provides an interface for users to enter their occupation name and related information.

2. Server: Connects to the database to retrieve and process occupational information. Includes an emotion engine that adjusts the way information is displayed based on the user's emotions.

3. Database: Stores information such as average annual salary for occupations, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Program processing

The server performs the following process:

1. Accepting user input: Receive occupation name and related information from the user's device.

2. Retrieving information from the database: Retrieve relevant information from the database based on the entered occupation name.

3. Emotion Recognition: Use an emotion engine to recognize the user's emotions.

4. Adjusting how information is displayed: Adjust how information is displayed based on the user's emotions.

5. Display in virtual space: Display information visually in a virtual space.

Hardware and software used

Hardware: Smartphone, head-mounted display

Software: Python, EmotionRecognizer library, requests library, database API

Specific examples

When a user types "software engineer" on their smartphone, the server retrieves information about software engineers from the database. If the emotion engine recognizes the user's emotion as "stressed," the information is displayed concisely. For example, the average annual salary and regional salary levels are displayed graphically.

Example prompt

Example of a prompt to input to a generative AI model:

If a user types "software engineer" and the emotion engine identifies them as "stressed," briefly display the following information:

Average annual income

Salary levels by region

In this way, information can be provided in an easy-to-understand format even when users are feeling stressed.

The flow of the specific processing in Application Example 1 will be explained using Figure 16.

Step 1:

Users enter their occupation and related information.

Input: The user uses a smartphone or head-mounted display to enter their job title (e.g., "Software Engineer") and related information.

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the name of their occupation into the interface and presses the submit button.

Step 2:

The server retrieves occupation information from the database.

Input: Occupation name and related information submitted by the user.

Output: Average annual salary for occupations retrieved from the database, salary levels for each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Specific operation: The server calls the database API and retrieves relevant information based on the entered occupation name.

Step 3:

The server uses an emotion engine to recognize the user's emotions.

Input: Emotional information such as the user's facial expressions and voice data.

Output: Recognized user emotion (e.g., "I feel stressed").

Specific operation: The server uses the EmotionRecognizer library to analyze the user's emotions.

Step 4:

The server adjusts how information is displayed based on the user's emotions.

Input: Recognized user emotion and occupational information obtained from the database.

Output: Adjusted information display format (e.g., concise display format).

Specific behavior: The server determines whether to display information graphically or concisely in text based on the user's emotions.

Step 5:

The server visually displays occupation information within the virtual space.

Input: Adjusted information display format and occupation information.

Output: Occupational information visually displayed in a virtual space.

Specific operation: The server generates a virtual space and sends information to the user's device to display it visually.

In this way, occupational information can be provided to users in an intuitive and easy-to-understand format.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience based on the occupation name entered by the user, but they lack the ability to adjust the way information is displayed based on the user's emotional state. As a result, there is an issue where appropriate information is not provided when the user is feeling stressed or has difficulty understanding the information.

The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual income of the occupation and the salary level for each region based on the input information, means for providing factors that affect income based on industry trends, demand forecasts, skills, and experience, means including an emotion engine that recognizes the user's emotions, and means for adjusting the display method based on the emotion engine. This makes it possible to provide appropriate information according to the user's emotional state.

A "user interface" is a means by which a user enters their job title and related information, and is provided through a web browser or dedicated application.

The "database" is an information management system for storing information such as average annual income by occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Average annual income" refers to the average annual income of employees in a particular occupation.

"Salary level" refers to the general level of salary in a particular region or occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

A "demand forecast" is a forecast of future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

"Means for adjusting the display method" refers to means for changing the display format of information depending on the user's emotional state.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their occupational title and related information using a web browser (e.g., Google Chrome, Mozilla Firefox) or a dedicated application. The user interface provides a form for entering occupational title and related information.

Database

The server queries a database (e.g., MySQL, PostgreSQL) based on the job title entered by the user to retrieve the following information:

Average annual income by occupation

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Calculating and displaying information

The server calculates average annual income and salary levels for each region based on the information it obtains. For example, let's say the national average annual income is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. It also simultaneously calculates factors that affect income based on industry trends, demand forecasts, and skills and experience. This information is displayed on the user's device.

Emotional Engine

As a user browses information, an emotion engine (e.g., Microsoft® Azure® Emotion API, IBM Watson® Tone Analyzer) recognizes the user's emotions. For example, if the emotion engine determines that the user is feeling stressed, the server adjusts the display method. Specifically, it makes the following adjustments:

Display average annual income and regional salary levels in graphs (e.g., bar graphs, pie charts)

Explain industry trends and demand forecasts in simple terms

Specific examples

If the user enters "software engineer," the server retrieves and displays the following information:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

If the emotion engine determines that the user is feeling stressed, the server adjusts the display as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

Example prompt

Examples of prompts to input to a generative AI model include:

The user entered "software engineer." Retrieve and display the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. Also, adjust the display method if the user is feeling stressed.

By inputting this prompt into a generative AI model, the system provides appropriate information to the user and adjusts the display method as needed.

The flow of the identification process in Example 2 will be explained using Figure 17.

Step 1:

The user enters their occupational title and related information using a web browser or dedicated application. The user enters "software engineer" and clicks the "Submit" button. The input data is the occupational title "software engineer."

Step 2:

The server receives the user's job title "Software Engineer" and sends a query to the database. The server retrieves the following information from the database:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

The data obtained is detailed information about occupations.

Step 3:

The server calculates the average annual salary and salary levels for each region based on the information obtained. For example, suppose the national average annual salary is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. The calculated data is the average annual salary and salary levels for each region.

Step 4:

The server also simultaneously calculates factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience. For example, advances in AI technology are expected to increase demand, with growth of 20% predicted over the next five years. The calculated data includes factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience.

Step 5:

The server sends the calculated information to the user's device and displays it. The following information is displayed on the user's device:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

Step 6:

As a user browses information, the emotion engine recognizes the user's emotions. For example, the emotion engine determines that the user is feeling stressed. The input data is the user's emotional state.

Step 7:

The server adjusts the display method based on the emotion engine's judgment. For example, if the user is feeling stressed, the display method will be adjusted as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

The adjusted data is in a format that is easy for users to understand.

Step 8:

The server then sends the adjusted information back to the user's device and displays it. The adjusted information is then displayed on the user's device.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional career information systems have the problem that the information obtained when a user inputs a career name is static, and the way the information is displayed cannot be adjusted to suit the user's emotions or level of understanding. Furthermore, in career counseling at brick-and-mortar stores, there is a lack of a way to provide career information in real time and display the information appropriately based on the user's emotions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for displaying information through a smart device. This makes it possible to provide appropriate information based on the user's emotions, and to provide information in real time even in career counseling at physical stores.

"User" means an individual or organization that uses the system to obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, including skills, experience, location, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that predicts future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

An "emotion engine" is software or hardware that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Smart device" means an internet-enabled device used to display information, including smart glasses and smartphones.

"Means to adjust the way information is displayed" is a function that allows you to change the way information is displayed depending on the user's emotions.

The following system configuration is described as an embodiment of this invention.

System Configuration

Hardware

Smart devices: Use internet-enabled devices such as smart glasses or smartphones.

Server: A server is used to manage occupational information and provide information in response to user requests.

Emotion engine: Includes hardware or software for recognizing user emotions.

Software

EmotionEngine: Software for recognizing user emotions in real time.

SmartGlass(R) esDisplay: Software for controlling the display of smart glasses.

API: External API for obtaining occupational information.

Program processing

User input

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist."

Getting information

Based on the entered occupation name, the server retrieves the occupation's average annual salary, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience via an external API.

Emotion recognition

The Emotion Engine recognizes the user's emotions in real time. For example, it determines whether the user is feeling stressed.

View information

The server adjusts the way the acquired information is displayed depending on the user's emotions. For example, if the user is feeling stressed, the information is displayed graphically. The information is displayed appropriately using software (SmartGlassesDisplay) that controls the smart glasses' display.

Specific examples

A career counselor wears smart glasses, and the user enters "data scientist." The system retrieves the average annual salary of data scientists, salary levels by region, industry trends, and more, and graphically displays if the user is feeling stressed.

Example prompt

"Please tell me the average annual salary of a data scientist, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

In this way, career counselors can provide users with more appropriate advice.

The flow of the specific processing in Application Example 2 is explained using Figure 18.

Step 1:

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist." This input information is sent from the smart device to the server.

Step 2:

The server sends a request to an external API based on the received occupation name. The API request includes the occupation name. The API response returns the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3:

The server stores the acquired occupational information in a database, which includes occupation titles, average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 4:

The Emotion Engine recognizes the user's emotions in real time. It uses the smart device's camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state. For example, it determines whether the user is feeling stressed.

Step 5:

The server receives emotional data from the emotion engine and adjusts how information is displayed based on the user's emotional state. For example, if the user is feeling stressed, the server can set the information to be displayed graphically.

Step 6:

The server sends the adjusted information to the smart device, which then displays the received information to the user. In the case of smart glasses, the SmartGlassesDisplay software is used to display the information appropriately.

Step 7:

Users can check the displayed information through their smart devices. For example, the average annual salary of a data scientist, salary levels by region, industry trends, and more are displayed graphically.

In this way, users can obtain occupational information in real time and receive appropriate information displayed according to their emotions.

The specific processing unit 290 transmits the results of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the results of the specific processing. The microphone 38B acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (registered trademark) (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (registered trademark) (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the smart device 14.

[Second embodiment]

Figure 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

As shown in FIG. 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I/F 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (e.g., an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

Figure 4 shows an example of the main functions of the data processing device 12 and smart glasses 214. As shown in Figure 4, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

"Example 2"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their occupation name through the system's user interface. This user interface can be provided through a web browser or dedicated application.

Step 2: Based on the entered occupation name, the system retrieves information on the corresponding occupation from a database. This database includes information such as the average annual salary for each occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3: Based on the information obtained, the system calculates the average annual salary and salary levels in each region. It also simultaneously obtains industry trends, demand forecasts, and factors that affect income based on skills and experience. Step 4: The system displays the calculated and obtained information to the user. As a specific example, if the user enters "software engineer," the system will display the average annual salary for software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous occupational information systems had the problem of making it difficult for users to quickly and accurately obtain detailed information even when they entered the name of an occupation. In particular, they were unable to provide a wide range of information in a unified manner, such as average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for transmitting the input information to the server, means for the server to obtain information about occupations from a database, means for calculating average annual income and regional salary levels based on the obtained information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, and means for displaying the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations.

"Means for users to input their occupation name and related information" refers to means that provide an interface for users to input their occupation name and related information, and is realized through a web browser or dedicated application.

"Means for sending input information to the server" refers to the means for sending the occupation name and related information input by the user to the server, and is realized using a communication protocol such as an HTTP request.

"Means by which the server retrieves information about occupations from the database" refers to the means by which the server executes queries against the database and retrieves information about occupations, and is realized using database technologies such as SQL or NoSQL.

"Means for calculating average annual income and regional salary levels based on acquired information" refers to the means by which the server calculates average annual income for each occupation and regional salary levels based on information acquired from the database.

"Means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience" refers to a means by which the server analyzes industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and provides these to users.

"Means for displaying calculated/obtained information to the user" refers to the means by which the server displays calculated/obtained information to the user through a user interface, and is realized using web technologies such as HTML, CSS, and JavaScript.

This invention is a system that allows users to input occupational titles and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. This system operates in cooperation with a server, terminal, and user.

Providing a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their job title and related information through this interface.

Accepting user input

The user enters their occupation and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server.

Submit input data

The device sends the occupation name entered by the user to the server. This is done via an HTTP request. Specifically, the input data is sent using the JavaScript fetch API.

Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it uses an SQL query to retrieve information about the occupation.

Data calculation and processing

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

Displaying information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

Specific examples and prompt sentence examples

As a concrete example, a user opens a web browser and types "software engineer" into the provided interface. The server retrieves information about software engineers from the database and calculates and displays the following information:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

An example prompt might be, "Please tell me the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily obtain detailed information about occupations.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Provide a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their occupation name and related information through this interface. The input includes the occupation name and related information, and the output is the data entered by the user.

Step 2: Accept user input

The user enters the job title and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server. The input includes the job title and related information entered by the user, and the output is the input data sent to the terminal.

Step 3: Send input data

The device sends the occupation name entered by the user to the server. This transmission is performed via an HTTP request. Specifically, the input data is sent using JavaScript's fetch API. The input includes the occupation name entered by the user and related information, and the output is the data sent to the server.

Step 4: Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it retrieves information about occupations using an SQL query. The input includes the occupation name sent to the server, and the output is the occupation information retrieved from the database.

Step 5: Calculate and process data

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

The input includes occupational information obtained from the database, and the output is various calculated information.

Step 6: Display information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

The input includes various calculated information, and the output is the information displayed on the user interface.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

In conventional occupational information systems, even if a user inputs the name of an occupation and related information, the information is simply displayed in text format, making it difficult for users to obtain information in a format that is intuitively easy to understand. Furthermore, because occupational information is not provided in virtual environments, users are unable to search for occupational information within virtual spaces.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual salary of the occupation and the salary level for each region based on the input information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, means for displaying occupational information within the virtual environment, and means for the user to acquire occupational information while moving within the virtual environment. This allows the user to intuitively search for occupational information within the virtual space and acquire information in an easy-to-understand format.

"User" refers to an individual or corporation that uses the system to enter and obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, such as location, skills, years of experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" refers to information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that shows a prediction of future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to the number of years and type of practical experience in a particular occupation.

"Income variables" refers to factors that cause income to fluctuate in a particular occupation, including skills and experience.

A "virtual environment" is a virtual space created using computer technology in which users can interact.

"Display means" refers to a method or device for visually presenting information to the user.

"Means of movement" refers to methods or devices that allow a user to move freely within a virtual environment.

A system for implementing this invention allows users to input occupational titles and related information, and based on that information, calculates the average annual salary for the occupation and regional salary levels, and provides industry trends, demand forecasts, and factors that affect income based on skills and experience. Furthermore, this information is displayed within a virtual environment, allowing users to obtain occupational information while moving around within the virtual environment.

Hardware and software configuration

Hardware: Smartphone, head-mounted display

Software: Flask (a Python web framework), database (a Python dictionary was used as a dummy database)

System Operation

1. User input:

Users use a smartphone or head-mounted display to enter their job title and related information within the virtual environment. For example, a user might enter "software engineer."

2. Data acquisition and calculation:

The server retrieves relevant occupational information from a database based on the entered occupation name, including average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Displaying information:

The server displays the retrieved information to the user within the virtual environment. The user can intuitively explore this information while moving around within the virtual environment.

Specific examples

When a user types "software engineer" in the virtual store, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 7.5 million yen, Osaka: 7 million yen, Fukuoka: 6.5 million yen

Industry Trends: Increasing Demand

Demand forecast: 20% increase over the next five years

Factors that affect income: years of experience, skill set

Example prompt

Please enter your job title: Software Engineer

This system allows users to intuitively search for occupational information in a virtual space and obtain information in an easy-to-understand format.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The user uses a smartphone or head-mounted display to input their job title and related information within the virtual environment. The input information is then sent to the server. The input data includes the job title (e.g., "software engineer") and related information (e.g., region, skills, years of experience).

Step 2:

The server retrieves the relevant occupational information from a database based on the received occupation name. Specifically, it searches the database using the occupation name as a key to retrieve average annual income, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. The input data is the occupation name, and the output data is a set of occupational information.

Step 3:

The server processes the data based on the acquired occupational information. For example, it converts regional salary levels into a format that makes them easier to compare, and graphs industry trends and demand forecasts. The input data is a set of occupational information, and the output data is the processed occupational information.

Step 4:

The server converts the processed occupational information into a data format for display within the virtual environment. Specifically, it generates data for display as 3D models and interactive UI elements. The input data is the processed occupational information, and the output data is the data for display.

Step 5:

The user explores the displayed occupational information while moving around the virtual environment. The user's movement information is sent to the server in real time, and the server updates the display content accordingly. The input data is the user's movement information, and the output data is the updated display content.

Step 6:

If the user wants more information about a specific occupation, they enter an additional prompt statement. The server retrieves more detailed information from the database based on this prompt statement and displays it in the virtual environment. The input data is the additional prompt statement, and the output data is the detailed occupation information.

Step 7:

When the user finishes searching for job information, the server saves the session data so the user can access it again later. The input data is the session data, and the output data is the saved session data.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

With conventional occupational information systems, even if users entered the name of an occupation, it was difficult to quickly and accurately obtain detailed salary information, industry trends, demand forecasts, or factors that affect income based on skills and experience. There was also a lack of ways to provide this information to users in an easy-to-understand manner. This meant that users were unable to obtain sufficient information for occupational selection and career planning, making it difficult for them to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes: a means for the user to input the name of an occupation and related information; a means for transmitting the input information to the server; a means for the server to obtain occupational information from a database; a means for calculating average annual income and regional salary levels based on the obtained information; a means for obtaining industry trends, demand forecasts, and income fluctuation factors based on skills and experience; and a means for providing the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations, enabling them to make appropriate decisions when choosing an occupation or planning their career.

"User" refers to an individual or organization that uses the system to enter occupational information and obtain the necessary information.

"Occupation name and related information" refers to the name of the occupation and information related to that occupation that the user enters into the system.

A "server" is a computer system that receives information sent by users, retrieves the necessary information from a database, processes and calculates the data, and provides it to users.

A "database" is an information management system for storing data such as occupational information, salary information, industry trends, demand forecasts, and factors that affect income based on skills and experience.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average or median salary for a particular occupation in each region.

"Industry trends" refers to information about the current situation and future predictions in a particular industry.

"Demand forecasting" is the prediction of future demand for specific occupations or skills.

"Skill- and experience-based income variables" are factors that show the impact that specific skill sets and years of experience have on income.

"Means of providing information" refers to the methods and technologies used by the server to communicate the information it has acquired and calculated to the user.

"Means of displaying information" refers to methods or technologies that allow users to visually confirm information.

This invention is a system that allows users to input occupation names and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. The system includes a user interface, a server, a database, and a means for displaying information.

The user enters their occupation name using a web browser or dedicated application. For example, they can use a web browser such as Google Chrome or Mozilla Firefox, or a dedicated mobile application. Once the user enters their occupation name, the device sends this information to the server. Specifically, the data is sent using an HTTP request.

The server retrieves the corresponding occupation information from a database based on the received occupation name. For example, it uses a database such as MySQL or PostgreSQL. The server performs the following data processing and calculations based on the retrieved information:

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

This information is sent from the server to the device and displayed to the user. The device then displays the results received from the server to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

As a concrete example, consider the case where a user enters "software engineer." The user enters their occupation in a web browser using Google Chrome. The device sends this information to a server, which retrieves information about software engineers from a database. The server calculates the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, and sends this information to the device. Finally, the device displays this information to the user.

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

Using this prompt, the generative AI model can obtain the necessary information and provide it to the user.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

User enters occupation name

The user enters their occupational name using a web browser or dedicated application. For example, they open Google Chrome, access the system's web page, and enter "software engineer" in the input field. The input data is their occupational name.

Step 2:

The device sends the input data to the server.

The device sends the occupation name entered by the user to the server. Specifically, it sends data using an HTTP request. The input is the occupation name entered by the user, and the output is the occupation name data sent to the server. For example, the device sends the following JSON-formatted data to the server:

json

{

"Occupation": "Software Engineer"

}

Step 3:

The server retrieves occupation information from the database.

The server retrieves the corresponding occupation information from the database based on the received occupation name. The input is the occupation name data sent to the server, and the output is the occupation information retrieved from the database. For example, run the following SQL query using a MySQL database:

sql

SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer';

Step 4:

The server processes and calculates the data.

The server performs the following data processing and calculations based on the acquired data. The input is occupational information acquired from the database, and the output is the processed and calculated results.

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

Step 5:

The server sends the results to the device.

The server sends the processed and calculated results to the terminal. The input is the processed and calculated results, and the output is the resulting data sent to the terminal. Specifically, the following JSON-formatted data is sent as an HTTP response:

json

{

"Average annual income": 7 million yen,

"Salary levels by region": {

"Tokyo": 8 million yen,

"Osaka": 7.5 million yen,

"Fukuoka": 7 million yen

},

"Industry Trends": "Demand is increasing due to advances in AI technology",

"Demand forecast": "20% increase over the next five years",

"Income fluctuation factors": "Python and Java skills are highly valued"

}

Step 6:

The device displays the results to the user.

The terminal displays the results received from the server to the user. The input is the result data sent from the server, and the output is the information displayed to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

With conventional career information systems, it was difficult for users to obtain detailed information about careers in real time, especially in a virtual environment. Furthermore, there was a lack of means to display information using smart devices, limiting the user experience. This meant that users were unable to obtain sufficient information when choosing a career or planning their career, making it difficult to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for calculating the average annual salary of an occupation and regional salary levels based on the input information, means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience, means for users to obtain information about occupations in real time within the virtual environment, and means for displaying the information via a smart device. This allows users to obtain detailed information about occupations in real time within the virtual environment and visually confirm it via a smart device.

"User" means an individual or corporation that uses the system to input and obtain occupational information.

"Occupation name" is a name used to identify a specific occupation.

"Related information" refers to detailed data and attribute information related to an occupation.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries for occupations in a particular region.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that shows future demand prospects for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

A "virtual environment" is a virtual space or environment created using computer technology.

"Real-time" means that data and information are processed immediately and provided without delay.

"Smart device" refers to an electronic device with internet connectivity and advanced computing capabilities.

"Means for displaying information" refers to a method or device for visually providing information to the user.

The system for implementing this invention includes a server, a user terminal, and a smart device. The specific configuration and operation of the system are described below.

System Configuration

1. Server:

Hardware: Any cloud server (e.g., AWS EC2)

Software: Python, Flask, SQLite

Function: Accepts user input of occupation name and related information, retrieves relevant occupation information from a database, and calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

2. User device:

Hardware: Smartphones, tablets

Software: Web browser or dedicated application

Function: The user enters their occupation and related information and displays the information retrieved from the server.

3. Smart Devices:

Hardware: Head-mounted display (e.g., Oculus Quest)

Software: Unity (head-mounted display application development)

Function: Allows users to obtain and visually display career information in real time within a virtual environment.

Data processing and calculation

The server receives the occupation name and related information entered by the user and performs the following processes:

1. Retrieving information from the database:

Retrieve the relevant occupation information from the SQLite database.

2. Information Calculation:

Calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Information provision:

The calculated information is sent to the user's terminal and smart device.

Specific examples

When a user types "software engineer" in the virtual environment, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 6.5 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase by 2025

Skill and experience-based income variables: AI and cloud technology skills are highly valued

Example prompt

Occupation: Software Engineer

Information obtained: average annual salary, regional salary levels, industry trends, demand forecasts, and factors affecting income based on skills and experience.

In this way, users can obtain detailed information about their occupation in real time within the virtual environment and visually view it via their smart device.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Users enter their occupation and related information.

Input: The user enters a job title (e.g., software engineer).

Operation: Enter your occupation and related information through the user's device interface.

Output: The entered occupation name and related information are sent to the server.

Step 2:

The server receives the entered information.

Input: Occupation name and related information sent from the user's device.

How it works: The server uses Flask to receive requests from users.

Output: The received occupation name and related information are processed within the server.

Step 3:

The server retrieves the relevant occupation information from the database.

Input: Received job name.

How it works: The server queries the SQLite database to retrieve information about the corresponding occupation.

Output: Average annual salary for occupations, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience are obtained.

Step 4:

Data processing and calculations are performed based on the information obtained by the server.

Input: Occupation information retrieved from the database.

How it works: The server uses Python to calculate average annual income and regional salary levels, and analyzes industry trends, demand forecasts, and factors that affect income based on skills and experience.

Output: Calculated and analyzed occupational information.

Step 5:

The server sends the calculated and analyzed information to the user's terminal and smart device.

Input: Calculated and analyzed occupational information.

How it works: The server uses Flask to send information to user terminals and smart devices.

Output: Occupation information is sent to the user's terminal and smart device.

Step 6:

Displays information received by user terminals and smart devices.

Input: Occupation information sent from the server.

How it works: User devices display information using a web browser or dedicated application, and smart devices use Unity to visually display information within the virtual environment.

Output: Users can view detailed occupation information in real time.

It is also possible to further combine an emotion engine that estimates the user's emotion. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

"Example 2"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their job title and related information into the system.

Step 2: Based on the information entered, the system calculates the average annual salary for each occupation and the salary level for each region.

Step 3: The system provides industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Step 4: The emotion engine recognizes the user's emotions.

Step 5: The emotion engine adjusts how average annual salaries and regional salary levels are displayed based on user sentiment.

Step 6: The sentiment engine uses user sentiment to adjust how it displays industry trends, demand forecasts, and income variables based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional occupational information systems had the problem that even when users input the name of an occupation and related information, the information provided was uniform and could not be flexibly displayed according to the user's emotions or level of understanding. Furthermore, when providing detailed information such as industry trends, demand forecasts, and factors that affect income based on skills and experience, users could feel stressed and find it difficult to understand the information.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means for recognizing the user's emotions; and means for adjusting the display method based on the recognized emotions. This enables flexible information provision according to the user's emotions and level of understanding, making it easier for the user to understand detailed information about occupations without feeling stressed.

"User" refers to an individual or organization that uses the system to enter their occupational title and related information and obtain information.

"Occupation name" is the name that indicates a specific occupation and is part of the information that a user enters into the system.

"Related information" is additional information related to the occupation title that users can enter into the system.

"Means" refers to a method or device for achieving a specific function or purpose.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries by region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecasting" refers to predicting future demand for a particular occupation or industry.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to work experience and history in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, region, industry trends, etc.

An "emotion engine" is a technology that recognizes a user's emotions and adjusts the system's behavior and display methods based on those emotions.

"Means for adjusting the display method" refers to a method or device for changing the display format of information based on the user's emotions.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their job title and related information using a web browser (e.g., Google Chrome) or a dedicated application (e.g., iOS app). The user interface is built using web technologies such as HTML, CSS, and JavaScript.

Database

The server retrieves information about the corresponding occupation from a database (e.g., MySQL) based on the occupation name entered by the user. The database stores information on the average annual salary for each occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Information calculation

The server calculates the average annual salary and salary levels for each region based on information obtained from the database. For example, it calculates the national average annual salary and then calculates the difference between regions.

Get industry trends and demand forecasts

The server sends requests to external APIs (e.g., economic data APIs) to obtain information on industry trends, demand forecasts, and income fluctuations based on skills and experience. It then analyzes the obtained data and prepares the information to provide to the user.

View information

The server displays the calculated and acquired information to the user. For example, it displays it in graph or table format on a web browser. Users can check the average annual salary of software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Adjusting display methods using the emotion engine

The server uses an emotion engine (e.g., emotion recognition software) to recognize the user's emotions. If the emotion engine determines that the user is feeling stressed, the server adjusts the way it displays information, for example, by presenting it graphically or explaining it in simpler terms.

Specific examples

If the user types "software engineer," the server displays the following information:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Furthermore, if the emotion engine determines that the user is feeling stressed, the server will display this information graphically or explain it in simple terms.

Example prompt

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily get detailed information about jobs.

The flow of the identification process in Example 1 will be explained using Figure 15.

Step 1:

Users enter their job title and related information using a web browser or dedicated application.

Enter: Occupation or related information (e.g., "Software Engineer")

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the occupation "Software Engineer" and clicks the submit button.

Step 2:

The server retrieves relevant occupation information from the database based on the occupation name entered by the user.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Specific operation: The server sends the query "SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer'" to the database and retrieves the results.

Step 3:

The server calculates the average annual salary and salary levels for each region based on information obtained from the database.

Input: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Output: Calculated average annual income and salary levels for each region

Specific operation: The server analyzes the data it acquires and calculates the national average annual salary and salary levels by region.

Step 4:

The server sends requests to external APIs to obtain industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Industry trends and demand forecast data obtained from external APIs

Specific operation: The server sends a request to an external API to obtain industry trends and demand forecast data.

Step 5:

The server displays the calculated and obtained information to the user.

Input: Calculated average annual salary, regional salary levels, industry trends and demand forecast data obtained from external APIs

Output: Information displayed to the user (e.g., occupational information displayed in graph or table format)

Specific operation: The server displays the information in graphs and tables on the web browser.

Step 6:

The server uses an emotion engine to recognize the user's emotions and adjust how they are displayed.

Input: User emotion data (e.g., whether they feel stressed)

Output: Tailored display (e.g., graphical display, simple explanation)

Specific operation: The server uses an emotion engine to analyze the user's emotions and displays information graphically or explains it in simple terms.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Traditional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, based on the occupation name and related information entered by the user. However, they lack the ability to adjust the way information is displayed based on the user's emotions. Furthermore, there is a lack of means to provide information visually within a virtual space, making it difficult to provide information in a way that is intuitively easy for users to understand.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for visually displaying occupation information within a virtual space. This makes it possible to adjust the information display method according to the user's emotions and provide information visually within a virtual space.

"User" means an individual or corporation that uses the system to enter occupational information and obtain related information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" refers to information related to the job title, such as region, skills, experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" refers to information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that predicts future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to practical experience in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, etc.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Virtual space" is a virtual space generated by a computer, an environment in which users can visually view information.

"Visually displaying" means presenting information to the user in a graphical format.

As an embodiment of this invention, we provide a system that allows users to input their occupation name and related information and visually confirm that information in a virtual space. Specific embodiments are described below.

System Configuration

The system consists of the following main components:

1. User terminal: A device such as a smartphone or head-mounted display that provides an interface for users to enter their occupation name and related information.

2. Server: Connects to the database to retrieve and process occupational information. Includes an emotion engine that adjusts the way information is displayed based on the user's emotions.

3. Database: Stores information such as average annual salary for occupations, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Program processing

The server performs the following process:

1. Accepting user input: Receive occupation name and related information from the user's device.

2. Retrieving information from the database: Retrieve relevant information from the database based on the entered occupation name.

3. Emotion Recognition: Use an emotion engine to recognize the user's emotions.

4. Adjusting how information is displayed: Adjust how information is displayed based on the user's emotions.

5. Display in virtual space: Display information visually in a virtual space.

Hardware and software used

Hardware: Smartphone, head-mounted display

Software: Python, EmotionRecognizer library, requests library, database API

Specific examples

When a user types "software engineer" on their smartphone, the server retrieves information about software engineers from the database. If the emotion engine recognizes the user's emotion as "stressed," the information is displayed concisely. For example, the average annual salary and regional salary levels are displayed graphically.

Example prompt

Example of a prompt to input to a generative AI model:

If a user types "software engineer" and the emotion engine identifies them as "stressed," briefly display the following information:

Average annual income

Salary levels by region

In this way, information can be provided in an easy-to-understand format even when users are feeling stressed.

The flow of the specific processing in Application Example 1 will be explained using Figure 16.

Step 1:

Users enter their occupation and related information.

Input: The user uses a smartphone or head-mounted display to enter their job title (e.g., "Software Engineer") and related information.

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the name of their occupation into the interface and presses the submit button.

Step 2:

The server retrieves occupation information from the database.

Input: Occupation name and related information submitted by the user.

Output: Average annual salary for occupations retrieved from the database, salary levels for each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Specific operation: The server calls the database API and retrieves relevant information based on the entered occupation name.

Step 3:

The server uses an emotion engine to recognize the user's emotions.

Input: Emotional information such as the user's facial expressions and voice data.

Output: Recognized user emotion (e.g., "I feel stressed").

Specific operation: The server uses the EmotionRecognizer library to analyze the user's emotions.

Step 4:

The server adjusts how information is displayed based on the user's emotions.

Input: Recognized user emotion and occupational information obtained from the database.

Output: Adjusted information display format (e.g., concise display format).

Specific behavior: The server determines whether to display information graphically or concisely in text based on the user's emotions.

Step 5:

The server visually displays occupation information within the virtual space.

Input: Adjusted information display format and occupation information.

Output: Occupational information visually displayed in a virtual space.

Specific operation: The server generates a virtual space and sends information to the user's device to display it visually.

In this way, occupational information can be provided to users in an intuitive and easy-to-understand format.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience based on the occupation name entered by the user, but they lack the ability to adjust the way information is displayed based on the user's emotional state. As a result, there is an issue where appropriate information is not provided when the user is feeling stressed or has difficulty understanding the information.

The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual income of the occupation and the salary level for each region based on the input information, means for providing factors that affect income based on industry trends, demand forecasts, skills, and experience, means including an emotion engine that recognizes the user's emotions, and means for adjusting the display method based on the emotion engine. This makes it possible to provide appropriate information according to the user's emotional state.

A "user interface" is a means by which a user enters their job title and related information, and is provided through a web browser or dedicated application.

The "database" is an information management system for storing information such as average annual income by occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Average annual income" refers to the average annual income of employees in a particular occupation.

"Salary level" refers to the general level of salary in a particular region or occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

A "demand forecast" is a forecast of future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

"Means for adjusting the display method" refers to a means for changing the display format of information depending on the user's emotional state.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their occupational title and related information using a web browser (e.g., Google Chrome, Mozilla Firefox) or a dedicated application. The user interface provides a form for entering occupational title and related information.

Database

The server queries a database (e.g., MySQL, PostgreSQL) based on the job title entered by the user to retrieve the following information:

Average annual income by occupation

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Calculating and displaying information

The server calculates average annual income and salary levels for each region based on the information it obtains. For example, let's say the national average annual income is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. It also simultaneously calculates factors that affect income based on industry trends, demand forecasts, and skills and experience. This information is displayed on the user's device.

Emotional Engine

As a user browses information, an emotion engine (e.g., Microsoft Azure Emotion API, IBM Watson Tone Analyzer) recognizes the user's emotions. For example, if the emotion engine determines that the user is feeling stressed, the server adjusts the display method. Specifically, it makes the following adjustments:

Display average annual income and regional salary levels in graphs (e.g., bar graphs, pie charts)

Explain industry trends and demand forecasts in simple terms

Specific examples

If the user enters "software engineer," the server retrieves and displays the following information:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

If the emotion engine determines that the user is feeling stressed, the server adjusts the display as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

Example prompt

Examples of prompts to input to a generative AI model include:

The user entered "software engineer." Retrieve and display the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. Also, adjust the display method if the user is feeling stressed.

By inputting this prompt into a generative AI model, the system provides appropriate information to the user and adjusts the display method as needed.

The flow of the identification process in Example 2 will be explained using Figure 17.

Step 1:

The user enters their occupational title and related information using a web browser or dedicated application. The user enters "software engineer" and clicks the "Submit" button. The input data is the occupational title "software engineer."

Step 2:

The server receives the user's job title "Software Engineer" and sends a query to the database. The server retrieves the following information from the database:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

The data obtained is detailed information about occupations.

Step 3:

The server calculates the average annual salary and salary levels for each region based on the information obtained. For example, suppose the national average annual salary is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. The calculated data is the average annual salary and salary levels for each region.

Step 4:

The server also simultaneously calculates factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience. For example, advances in AI technology are expected to increase demand, with growth of 20% predicted over the next five years. The calculated data includes factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience.

Step 5:

The server sends the calculated information to the user's device and displays it. The following information is displayed on the user's device:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

Step 6:

As a user browses information, the emotion engine recognizes the user's emotions. For example, the emotion engine determines that the user is feeling stressed. The input data is the user's emotional state.

Step 7:

The server adjusts the display method based on the emotion engine's judgment. For example, if the user is feeling stressed, the display method will be adjusted as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

The adjusted data is in a format that is easy for users to understand.

Step 8:

The server then sends the adjusted information back to the user's device and displays it. The adjusted information is then displayed on the user's device.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional career information systems have the problem that the information obtained when a user inputs a career name is static, and the way the information is displayed cannot be adjusted to suit the user's emotions or level of understanding. Furthermore, in career counseling at brick-and-mortar stores, there is a lack of a way to provide career information in real time and display the information appropriately based on the user's emotions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for displaying information through a smart device. This makes it possible to provide appropriate information based on the user's emotions, and to provide information in real time even in career counseling at physical stores.

"User" means an individual or organization that uses the system to obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, including skills, experience, location, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that predicts future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

An "emotion engine" is software or hardware that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Smart device" means an internet-enabled device used to display information, including smart glasses and smartphones.

"Means to adjust the way information is displayed" is a function that allows you to change the way information is displayed depending on the user's emotions.

The following system configuration is described as an embodiment of this invention.

System Configuration

Hardware

Smart devices: Use internet-enabled devices such as smart glasses or smartphones.

Server: A server is used to manage occupational information and provide information in response to user requests.

Emotion engine: Includes hardware or software for recognizing user emotions.

Software

EmotionEngine: Software for recognizing user emotions in real time.

SmartGlassesDisplay: Software for controlling the display of smart glasses.

API: External API for obtaining occupational information.

Program processing

User input

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist."

Getting information

Based on the entered occupation name, the server retrieves the occupation's average annual salary, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience via an external API.

Emotion recognition

The Emotion Engine recognizes the user's emotions in real time. For example, it determines whether the user is feeling stressed.

View information

The server adjusts the way the acquired information is displayed depending on the user's emotions. For example, if the user is feeling stressed, the information is displayed graphically. The information is displayed appropriately using software (SmartGlassesDisplay) that controls the smart glasses' display.

Specific examples

A career counselor wears smart glasses, and the user enters "data scientist." The system retrieves the average annual salary of data scientists, salary levels by region, industry trends, and more, and graphically displays if the user is feeling stressed.

Example prompt

"Please tell me the average annual salary of a data scientist, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

In this way, career counselors can provide users with more appropriate advice.

The flow of the specific processing in Application Example 2 is explained using Figure 18.

Step 1:

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist." This input information is sent from the smart device to the server.

Step 2:

The server sends a request to an external API based on the received occupation name. The API request includes the occupation name. The API response returns the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3:

The server stores the acquired occupational information in a database, which includes occupation titles, average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 4:

The Emotion Engine recognizes the user's emotions in real time. It uses the smart device's camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state. For example, it determines whether the user is feeling stressed.

Step 5:

The server receives emotional data from the emotion engine and adjusts how information is displayed based on the user's emotional state. For example, if the user is feeling stressed, the server can set the information to be displayed graphically.

Step 6:

The server sends the adjusted information to the smart device, which then displays the received information to the user. In the case of smart glasses, the SmartGlassesDisplay software is used to display the information appropriately.

Step 7:

Users can check the displayed information through their smart devices. For example, the average annual salary of a data scientist, salary levels by region, industry trends, and more are displayed graphically.

In this way, users can obtain occupational information in real time and receive appropriate information displayed according to their emotions.

The specific processing unit 290 transmits the results of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the smart glasses 214.

[Third embodiment]

Figure 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

As shown in FIG. 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I/F 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (e.g., an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

Figure 6 shows an example of the main functions of the data processing device 12 and headset terminal 314. As shown in Figure 6, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the headset terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

"Example 2"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their occupation name through the system's user interface. This user interface can be provided through a web browser or dedicated application.

Step 2: Based on the entered occupation name, the system retrieves information on the corresponding occupation from a database. This database includes information such as the average annual salary for each occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3: Based on the information obtained, the system calculates the average annual salary and salary levels in each region. It also simultaneously obtains industry trends, demand forecasts, and factors that affect income based on skills and experience. Step 4: The system displays the calculated and obtained information to the user. As a specific example, if the user enters "software engineer," the system will display the average annual salary for software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous occupational information systems had the problem of making it difficult for users to quickly and accurately obtain detailed information even when they entered the name of an occupation. In particular, they were unable to provide a wide range of information in a unified manner, such as average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for transmitting the input information to the server, means for the server to obtain information about occupations from a database, means for calculating average annual income and regional salary levels based on the obtained information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, and means for displaying the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations.

"Means for users to input their occupation name and related information" refers to means that provide an interface for users to input their occupation name and related information, and is realized through a web browser or dedicated application.

"Means for sending input information to the server" refers to the means for sending the occupation name and related information input by the user to the server, and is realized using a communication protocol such as an HTTP request.

"Means by which the server retrieves information about occupations from the database" refers to the means by which the server executes queries against the database and retrieves information about occupations, and is realized using database technologies such as SQL or NoSQL.

"Means for calculating average annual income and regional salary levels based on acquired information" refers to the means by which the server calculates average annual income for each occupation and regional salary levels based on information acquired from the database.

"Means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience" refers to a means by which the server analyzes industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and provides these to users.

"Means for displaying calculated/obtained information to the user" refers to the means by which the server displays calculated/obtained information to the user through a user interface, and is realized using web technologies such as HTML, CSS, and JavaScript.

This invention is a system that allows users to input occupational titles and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. This system operates in cooperation with a server, terminal, and user.

Providing a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their job title and related information through this interface.

Accepting user input

The user enters their occupation and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server.

Submit input data

The device sends the occupation name entered by the user to the server. This is done via an HTTP request. Specifically, the input data is sent using the JavaScript fetch API.

Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it retrieves information about occupations using SQL queries.

Data calculation and processing

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

Displaying information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

Specific examples and prompt sentence examples

As a concrete example, a user opens a web browser and types "software engineer" into the provided interface. The server retrieves information about software engineers from the database and calculates and displays the following information:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

An example prompt would be, "Please tell me the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily obtain detailed information about occupations.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Provide a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their occupation name and related information through this interface. The input includes the occupation name and related information, and the output is the data entered by the user.

Step 2: Accept user input

The user enters the job title and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server. The input includes the job title and related information entered by the user, and the output is the input data sent to the terminal.

Step 3: Send input data

The device sends the occupation name entered by the user to the server. This transmission is performed via an HTTP request. Specifically, the input data is sent using JavaScript's fetch API. The input includes the occupation name entered by the user and related information, and the output is the data sent to the server.

Step 4: Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it retrieves information about occupations using an SQL query. The input includes the occupation name sent to the server, and the output is the occupation information retrieved from the database.

Step 5: Calculate and process data

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

The input includes occupational information obtained from the database, and the output is various calculated information.

Step 6: Display information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

The input includes various calculated information, and the output is the information displayed on the user interface.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

In conventional occupational information systems, even if a user inputs the name of an occupation and related information, the information is simply displayed in text format, making it difficult for users to obtain information in a format that is intuitively easy to understand. Furthermore, because occupational information is not provided in virtual environments, users are unable to search for occupational information within virtual spaces.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual salary of the occupation and the salary level for each region based on the input information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, means for displaying occupational information within the virtual environment, and means for the user to acquire occupational information while moving within the virtual environment. This allows the user to intuitively search for occupational information within the virtual space and acquire information in an easy-to-understand format.

"User" refers to an individual or corporation that uses the system to enter and obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, such as location, skills, years of experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that shows a prediction of future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to the number of years and type of practical experience in a particular occupation.

"Income variables" refers to factors that cause income to fluctuate in a particular occupation, including skills and experience.

A "virtual environment" is a virtual space created using computer technology in which users can interact.

"Display means" refers to a method or device for visually presenting information to the user.

"Means of movement" refers to methods or devices that allow a user to move freely within a virtual environment.

A system for implementing this invention allows users to input occupational titles and related information, and based on that information, calculates the average annual salary for the occupation and regional salary levels, and provides industry trends, demand forecasts, and factors that affect income based on skills and experience. Furthermore, this information is displayed within a virtual environment, allowing users to obtain occupational information while moving around within the virtual environment.

Hardware and software configuration

Hardware: Smartphone, head-mounted display

Software: Flask (a Python web framework), database (a Python dictionary was used as a dummy database)

System Operation

1. User input:

Users use a smartphone or head-mounted display to enter their job title and related information within the virtual environment. For example, a user might enter "software engineer."

2. Data acquisition and calculation:

The server retrieves relevant occupational information from a database based on the entered occupation name, including average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Displaying information:

The server displays the retrieved information to the user within the virtual environment. The user can intuitively explore this information while moving around within the virtual environment.

Specific examples

When a user types "software engineer" in the virtual store, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 7.5 million yen, Osaka: 7 million yen, Fukuoka: 6.5 million yen

Industry Trends: Increasing Demand

Demand forecast: 20% increase over the next five years

Factors that affect income: years of experience, skill set

Example prompt

Please enter your job title: Software Engineer

This system allows users to intuitively search for occupational information in a virtual space and obtain information in an easy-to-understand format.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The user uses a smartphone or head-mounted display to input their job title and related information within the virtual environment. The input information is then sent to the server. The input data includes the job title (e.g., "software engineer") and related information (e.g., region, skills, years of experience).

Step 2:

The server retrieves the relevant occupational information from a database based on the received occupation name. Specifically, it searches the database using the occupation name as a key to retrieve average annual income, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. The input data is the occupation name, and the output data is a set of occupational information.

Step 3:

The server processes the data based on the acquired occupational information. For example, it converts regional salary levels into a format that makes them easier to compare, and graphs industry trends and demand forecasts. The input data is a set of occupational information, and the output data is the processed occupational information.

Step 4:

The server converts the processed occupational information into a data format for display within the virtual environment. Specifically, it generates data for display as 3D models and interactive UI elements. The input data is the processed occupational information, and the output data is the data for display.

Step 5:

The user explores the displayed occupational information while moving around the virtual environment. The user's movement information is sent to the server in real time, and the server updates the display content accordingly. The input data is the user's movement information, and the output data is the updated display content.

Step 6:

If the user wants more information about a specific occupation, they enter an additional prompt statement. The server retrieves more detailed information from the database based on this prompt statement and displays it in the virtual environment. The input data is the additional prompt statement, and the output data is the detailed occupation information.

Step 7:

When the user finishes searching for job information, the server saves the session data so the user can access it again later. The input data is the session data, and the output data is the saved session data.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

With conventional occupational information systems, even if users entered the name of an occupation, it was difficult to quickly and accurately obtain detailed salary information, industry trends, demand forecasts, or factors that affect income based on skills and experience. There was also a lack of ways to provide this information to users in an easy-to-understand manner. This meant that users were unable to obtain sufficient information for occupational selection and career planning, making it difficult for them to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes: a means for the user to input the name of an occupation and related information; a means for transmitting the input information to the server; a means for the server to obtain occupational information from a database; a means for calculating average annual income and regional salary levels based on the obtained information; a means for obtaining industry trends, demand forecasts, and income fluctuation factors based on skills and experience; and a means for providing the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations, enabling them to make appropriate decisions when choosing an occupation or planning their career.

"User" refers to an individual or organization that uses the system to enter occupational information and obtain the necessary information.

"Occupation name and related information" refers to the name of the occupation and information related to that occupation that the user enters into the system.

A "server" is a computer system that receives information sent by users, retrieves the necessary information from a database, processes and calculates the data, and provides it to users.

A "database" is an information management system for storing data such as occupational information, salary information, industry trends, demand forecasts, and factors that affect income based on skills and experience.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average or median salary for a particular occupation in each region.

"Industry trends" refers to information about the current situation and future predictions in a particular industry.

"Demand forecasting" is the prediction of future demand for specific occupations or skills.

"Skill- and experience-based income variables" are factors that show the impact that specific skill sets and years of experience have on income.

"Means of providing information" refers to the methods and technologies used by the server to communicate the information it has acquired and calculated to the user.

"Means of displaying information" refers to methods or technologies that allow users to visually confirm information.

This invention is a system that allows users to input occupation names and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. The system includes a user interface, a server, a database, and a means for displaying information.

The user enters their occupation name using a web browser or dedicated application. For example, they can use a web browser such as Google Chrome or Mozilla Firefox, or a dedicated mobile application. Once the user enters their occupation name, the device sends this information to the server. Specifically, the data is sent using an HTTP request.

The server retrieves the corresponding occupation information from a database based on the received occupation name. For example, it uses a database such as MySQL or PostgreSQL. The server performs the following data processing and calculations based on the retrieved information:

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

This information is sent from the server to the device and displayed to the user. The device then displays the results received from the server to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

As a concrete example, consider the case where a user enters "software engineer." The user enters their occupation in a web browser using Google Chrome. The device sends this information to a server, which retrieves information about software engineers from a database. The server calculates the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, and sends this information to the device. Finally, the device displays this information to the user.

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

Using this prompt, the generative AI model can obtain the necessary information and provide it to the user.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

User enters occupation name

The user enters their occupational name using a web browser or dedicated application. For example, they open Google Chrome, access the system's web page, and enter "software engineer" in the input field. The input data is their occupational name.

Step 2:

The device sends the input data to the server.

The device sends the occupation name entered by the user to the server. Specifically, it sends data using an HTTP request. The input is the occupation name entered by the user, and the output is the occupation name data sent to the server. For example, the device sends the following JSON-formatted data to the server:

json

{

"Occupation": "Software Engineer"

}

Step 3:

The server retrieves occupation information from the database.

The server retrieves the corresponding occupation information from the database based on the received occupation name. The input is the occupation name data sent to the server, and the output is the occupation information retrieved from the database. For example, run the following SQL query using a MySQL database:

sql

SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer';

Step 4:

The server processes and calculates the data.

The server performs the following data processing and calculations based on the acquired data. The input is occupational information acquired from the database, and the output is the processed and calculated results.

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

Step 5:

The server sends the results to the device.

The server sends the processed and calculated results to the terminal. The input is the processed and calculated results, and the output is the resulting data sent to the terminal. Specifically, the server sends the following JSON-formatted data as an HTTP response:

json

{

"Average annual income": 7 million yen,

"Salary levels by region": {

"Tokyo": 8 million yen,

"Osaka": 7.5 million yen,

"Fukuoka": 7 million yen

},

"Industry Trends": "Demand is increasing due to advances in AI technology",

"Demand forecast": "20% increase over the next five years",

"Income fluctuation factors": "Python and Java skills are highly valued"

}

Step 6:

The device displays the results to the user.

The terminal displays the results received from the server to the user. The input is the result data sent from the server, and the output is the information displayed to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

With conventional career information systems, it was difficult for users to obtain detailed information about careers in real time, especially in a virtual environment. Furthermore, there was a lack of means to display information using smart devices, limiting the user experience. This meant that users were unable to obtain sufficient information when choosing a career or planning their career, making it difficult to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for calculating the average annual salary of an occupation and regional salary levels based on the input information, means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience, means for users to obtain information about occupations in real time within the virtual environment, and means for displaying the information via a smart device. This allows users to obtain detailed information about occupations in real time within the virtual environment and visually confirm it via a smart device.

"User" means an individual or corporation that uses the system to input and obtain occupational information.

"Occupation name" is a name used to identify a specific occupation.

"Related information" refers to detailed data and attribute information related to an occupation.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries for occupations in a particular region.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that shows future demand prospects for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

A "virtual environment" is a virtual space or environment created using computer technology.

"Real-time" means that data and information are processed immediately and provided without delay.

"Smart device" refers to an electronic device with internet connectivity and advanced computing capabilities.

"Means for displaying information" refers to a method or device for visually providing information to the user.

The system for implementing this invention includes a server, a user terminal, and a smart device. The specific configuration and operation of the system are described below.

System Configuration

1. Server:

Hardware: Any cloud server (e.g., AWS EC2)

Software: Python, Flask, SQLite

Function: Accepts user input of occupation name and related information, retrieves relevant occupation information from a database, and calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

2. User device:

Hardware: Smartphones, tablets

Software: Web browser or dedicated application

Function: The user enters their occupation and related information and displays the information retrieved from the server.

3. Smart Devices:

Hardware: Head-mounted display (e.g., Oculus Quest)

Software: Unity (head-mounted display application development)

Function: Allows users to obtain and visually display career information in real time within a virtual environment.

Data processing and calculation

The server receives the occupation name and related information entered by the user and performs the following processes.

1. Retrieving information from the database:

Retrieve the relevant occupation information from the SQLite database.

2. Information Calculation:

Calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Information provision:

The calculated information is sent to the user's terminal and smart device.

Specific examples

When a user types "software engineer" in the virtual environment, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 6.5 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase by 2025

Skill and experience-based income variables: AI and cloud technology skills are highly valued

Example prompt

Occupation: Software Engineer

Information obtained: average annual salary, regional salary levels, industry trends, demand forecasts, and factors affecting income based on skills and experience.

In this way, users can obtain detailed information about their occupation in real time within the virtual environment and visually view it via their smart device.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Users enter their occupation and related information.

Input: The user enters a job title (e.g., software engineer).

Operation: Enter your occupation and related information through the user's device interface.

Output: The entered occupation name and related information are sent to the server.

Step 2:

The server receives the entered information.

Input: Occupation name and related information sent from the user's device.

How it works: The server uses Flask to receive requests from users.

Output: The received occupation name and related information are processed within the server.

Step 3:

The server retrieves the relevant occupation information from the database.

Input: Received job name.

How it works: The server queries the SQLite database to retrieve information about the corresponding occupation.

Output: Average annual salary for occupations, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience are obtained.

Step 4:

Data processing and calculations are performed based on the information obtained by the server.

Input: Occupation information retrieved from the database.

How it works: The server uses Python to calculate average annual income and regional salary levels, and analyzes industry trends, demand forecasts, and factors that affect income based on skills and experience.

Output: Calculated and analyzed occupational information.

Step 5:

The server sends the calculated and analyzed information to the user's terminal and smart device.

Input: Calculated and analyzed occupational information.

How it works: The server uses Flask to send information to user terminals and smart devices.

Output: Occupation information is sent to the user's terminal and smart device.

Step 6:

Displays information received by user terminals and smart devices.

Input: Occupation information sent from the server.

How it works: User devices display information using a web browser or dedicated application, and smart devices use Unity to visually display information within the virtual environment.

Output: Users can view detailed occupation information in real time.

It is also possible to further combine an emotion engine that estimates the user's emotion. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

"Example 2"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their job title and related information into the system.

Step 2: Based on the information entered, the system calculates the average annual salary for each occupation and the salary level for each region.

Step 3: The system provides industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Step 4: The emotion engine recognizes the user's emotions.

Step 5: The emotion engine adjusts the way average annual salaries and regional salary levels are displayed based on user sentiment.

Step 6: The sentiment engine uses user sentiment to adjust how it displays industry trends, demand forecasts, and income variables based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional occupational information systems had the problem that even when users input the name of an occupation and related information, the information provided was uniform and could not be flexibly displayed according to the user's emotions or level of understanding. Furthermore, when providing detailed information such as industry trends, demand forecasts, and factors that affect income based on skills and experience, users could feel stressed and find it difficult to understand the information.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means for recognizing the user's emotions; and means for adjusting the display method based on the recognized emotions. This enables flexible information provision according to the user's emotions and level of understanding, making it easier for the user to understand detailed information about occupations without feeling stressed.

"User" refers to an individual or organization that uses the system to enter their occupational title and related information and obtain information.

"Occupation name" is the name that indicates a specific occupation and is part of the information that a user enters into the system.

"Related information" is additional information related to the occupation title that users can enter into the system.

"Means" refers to a method or device for achieving a specific function or purpose.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries by region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecasting" refers to predicting future demand for a particular occupation or industry.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to work experience and history in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, region, industry trends, etc.

An "emotion engine" is a technology that recognizes a user's emotions and adjusts the system's behavior and display methods based on those emotions.

"Means for adjusting the display method" refers to a method or device for changing the display format of information based on the user's emotions.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their job title and related information using a web browser (e.g., Google Chrome) or a dedicated application (e.g., iOS app). The user interface is built using web technologies such as HTML, CSS, and JavaScript.

Database

The server retrieves information about the corresponding occupation from a database (e.g., MySQL) based on the occupation name entered by the user. The database stores information on the average annual salary for each occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Information calculation

The server calculates the average annual salary and salary levels for each region based on information obtained from the database. For example, it calculates the national average annual salary and then calculates the difference between regions.

Get industry trends and demand forecasts

The server sends requests to external APIs (e.g., economic data APIs) to obtain information on industry trends, demand forecasts, and income fluctuations based on skills and experience. It then analyzes the obtained data and prepares the information to provide to the user.

View information

The server displays the calculated and acquired information to the user. For example, it displays it in graph or table format on a web browser. Users can check the average annual salary of software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Adjusting display methods using the emotion engine

The server uses an emotion engine (e.g., emotion recognition software) to recognize the user's emotions. If the emotion engine determines that the user is feeling stressed, the server adjusts the way it displays information, for example, by presenting it graphically or explaining it in simpler terms.

Specific examples

If the user types "software engineer," the server displays the following information:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Furthermore, if the emotion engine determines that the user is feeling stressed, the server will display this information graphically or explain it in simple terms.

Example prompt

"Please tell me the average annual salary of software engineers, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily get detailed information about jobs.

The flow of the identification process in Example 1 will be explained using Figure 15.

Step 1:

Users enter their job title and related information using a web browser or dedicated application.

Enter: Occupation or related information (e.g., "Software Engineer")

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the occupation "Software Engineer" and clicks the submit button.

Step 2:

The server retrieves relevant occupation information from the database based on the occupation name entered by the user.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Specific operation: The server sends the query "SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer'" to the database and retrieves the results.

Step 3:

The server calculates the average annual salary and salary levels for each region based on information obtained from the database.

Input: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Output: Calculated average annual income and salary levels for each region

Specific operation: The server analyzes the data it acquires and calculates the national average annual salary and salary levels by region.

Step 4:

The server sends requests to external APIs to obtain industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Industry trends and demand forecast data obtained from external APIs

Specific operation: The server sends a request to an external API to obtain industry trends and demand forecast data.

Step 5:

The server displays the calculated and obtained information to the user.

Input: Calculated average annual salary, regional salary levels, industry trends and demand forecast data obtained from external APIs

Output: Information displayed to the user (e.g., occupational information displayed in graph or table format)

Specific operation: The server displays the information in graphs and tables on the web browser.

Step 6:

The server uses an emotion engine to recognize the user's emotions and adjust how they are displayed.

Input: User emotion data (e.g., whether they feel stressed)

Output: Tailored display (e.g., graphical display, simple explanation)

Specific operation: The server uses an emotion engine to analyze the user's emotions and displays information graphically or explains it in simple terms.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Traditional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, based on the occupation name and related information entered by the user. However, they lack the ability to adjust the way information is displayed based on the user's emotions. Furthermore, there is a lack of means to provide information visually within a virtual space, making it difficult to provide information in a way that is intuitively easy for users to understand.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for visually displaying occupation information within a virtual space. This makes it possible to adjust the information display method according to the user's emotions and provide information visually within a virtual space.

"User" means an individual or corporation that uses the system to enter occupational information and obtain related information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" refers to information related to the job title, such as region, skills, experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" refers to information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that predicts future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to practical experience in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, etc.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Virtual space" is a virtual space generated by a computer, an environment in which users can visually view information.

"Visually displaying" means presenting information to the user in a graphical format.

As an embodiment of this invention, we provide a system that allows users to input their occupation name and related information and visually confirm that information in a virtual space. Specific embodiments are described below.

System Configuration

The system consists of the following main components:

1. User terminal: A device such as a smartphone or head-mounted display that provides an interface for users to enter their occupation name and related information.

2. Server: Connects to the database to retrieve and process occupational information. Includes an emotion engine that adjusts the way information is displayed based on the user's emotions.

3. Database: Stores information such as average annual salary for occupations, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Program processing

The server performs the following process:

1. Accepting user input: Receive occupation name and related information from the user's device.

2. Retrieving information from the database: Retrieve relevant information from the database based on the entered occupation name.

3. Emotion Recognition: Use an emotion engine to recognize the user's emotions.

4. Adjusting how information is displayed: Adjust how information is displayed based on the user's emotions.

5. Display in virtual space: Display information visually in a virtual space.

Hardware and software used

Hardware: Smartphone, head-mounted display

Software: Python, EmotionRecognizer library, requests library, database API

Specific examples

When a user types "software engineer" on their smartphone, the server retrieves information about software engineers from the database. If the emotion engine recognizes the user's emotion as "stressed," the information is displayed concisely. For example, the average annual salary and regional salary levels are displayed graphically.

Example prompt

Example of a prompt to input to a generative AI model:

If a user types "software engineer" and the emotion engine identifies them as "stressed," briefly display the following information:

Average annual income

Salary levels by region

In this way, information can be provided in an easy-to-understand format even when users are feeling stressed.

The flow of the specific processing in Application Example 1 will be explained using Figure 16.

Step 1:

Users enter their occupation and related information.

Input: The user uses a smartphone or head-mounted display to enter their job title (e.g., "Software Engineer") and related information.

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the name of their occupation into the interface and presses the submit button.

Step 2:

The server retrieves occupation information from the database.

Input: Occupation name and related information submitted by the user.

Output: Average annual salary for occupations retrieved from the database, salary levels for each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Specific operation: The server calls the database API and retrieves relevant information based on the entered occupation name.

Step 3:

The server uses an emotion engine to recognize the user's emotions.

Input: Emotional information such as the user's facial expressions and voice data.

Output: Recognized user emotion (e.g., "I feel stressed").

Specific operation: The server uses the EmotionRecognizer library to analyze the user's emotions.

Step 4:

The server adjusts how information is displayed based on the user's emotions.

Input: Recognized user emotion and occupational information obtained from the database.

Output: Adjusted information display format (e.g., concise display format).

Specific behavior: The server determines whether to display information graphically or concisely in text based on the user's emotions.

Step 5:

The server visually displays occupation information within the virtual space.

Input: Adjusted information display format and occupation information.

Output: Occupational information visually displayed in a virtual space.

Specific operation: The server generates a virtual space and sends information to the user's device to display it visually.

In this way, occupational information can be provided to users in an intuitive and easy-to-understand format.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience based on the occupation name entered by the user, but they lack the ability to adjust the way information is displayed based on the user's emotional state. As a result, there is an issue where appropriate information is not provided when the user is feeling stressed or has difficulty understanding the information.

The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual income of the occupation and the salary level for each region based on the input information, means for providing factors that affect income based on industry trends, demand forecasts, skills, and experience, means including an emotion engine that recognizes the user's emotions, and means for adjusting the display method based on the emotion engine. This makes it possible to provide appropriate information according to the user's emotional state.

A "user interface" is a means by which a user enters their job title and related information, and is provided through a web browser or dedicated application.

The "database" is an information management system for storing information such as average annual income by occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Average annual income" refers to the average annual income of employees in a particular occupation.

"Salary level" refers to the general level of salary in a particular region or occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

A "demand forecast" is a forecast of future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

"Means for adjusting the display method" refers to a means for changing the display format of information depending on the user's emotional state.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their occupational title and related information using a web browser (e.g., Google Chrome, Mozilla Firefox) or a dedicated application. The user interface provides a form for entering occupational title and related information.

Database

The server queries a database (e.g., MySQL, PostgreSQL) based on the job title entered by the user to retrieve the following information:

Average annual income by occupation

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Calculating and displaying information

The server calculates average annual income and salary levels for each region based on the information it obtains. For example, let's say the national average annual income is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. It also simultaneously calculates factors that affect income based on industry trends, demand forecasts, and skills and experience. This information is displayed on the user's device.

Emotional Engine

As a user browses information, an emotion engine (e.g., Microsoft Azure Emotion API, IBM Watson Tone Analyzer) recognizes the user's emotions. For example, if the emotion engine determines that the user is feeling stressed, the server adjusts the display method. Specifically, it makes the following adjustments:

Display average annual income and regional salary levels in graphs (e.g., bar graphs, pie charts)

Explain industry trends and demand forecasts in simple terms

Specific examples

If the user enters "software engineer," the server retrieves and displays the following information:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

If the emotion engine determines that the user is feeling stressed, the server adjusts the display as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

Example prompt

Examples of prompts to input to a generative AI model include:

The user entered "software engineer." Retrieve and display the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. Also, adjust the display method if the user is feeling stressed.

By inputting this prompt into a generative AI model, the system provides appropriate information to the user and adjusts the display method as needed.

The flow of the identification process in Example 2 will be explained using Figure 17.

Step 1:

The user enters their occupational title and related information using a web browser or dedicated application. The user enters "software engineer" and clicks the "Submit" button. The input data is the occupational title "software engineer."

Step 2:

The server receives the user's job title "Software Engineer" and sends a query to the database. The server retrieves the following information from the database:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

The data obtained is detailed information about occupations.

Step 3:

The server calculates the average annual salary and salary levels for each region based on the information obtained. For example, suppose the national average annual salary is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. The calculated data is the average annual salary and salary levels for each region.

Step 4:

The server also simultaneously calculates factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience. For example, advances in AI technology are expected to increase demand, with growth of 20% predicted over the next five years. The calculated data includes factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience.

Step 5:

The server sends the calculated information to the user's device and displays it. The following information is displayed on the user's device:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

Step 6:

As a user browses information, the emotion engine recognizes the user's emotions. For example, the emotion engine determines that the user is feeling stressed. The input data is the user's emotional state.

Step 7:

The server adjusts the display method based on the emotion engine's judgment. For example, if the user is feeling stressed, the display method will be adjusted as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

The adjusted data is in a format that is easy for users to understand.

Step 8:

The server then sends the adjusted information back to the user's device and displays it. The adjusted information is then displayed on the user's device.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional career information systems have the problem that the information obtained when a user inputs a career name is static, and the way the information is displayed cannot be adjusted to suit the user's emotions or level of understanding. Furthermore, in career counseling at brick-and-mortar stores, there is a lack of a way to provide career information in real time and display the information appropriately based on the user's emotions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for displaying information through a smart device. This makes it possible to provide appropriate information based on the user's emotions, and to provide information in real time even in career counseling at physical stores.

"User" means an individual or organization that uses the system to obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, including skills, experience, location, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that predicts future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

An "emotion engine" is software or hardware that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Smart device" means an internet-enabled device used to display information, including smart glasses and smartphones.

"Means to adjust the way information is displayed" is a function that allows you to change the way information is displayed depending on the user's emotions.

The following system configuration is described as an embodiment of this invention.

System Configuration

Hardware

Smart devices: Use internet-enabled devices such as smart glasses or smartphones.

Server: A server is used to manage occupational information and provide information in response to user requests.

Emotion engine: Includes hardware or software for recognizing user emotions.

Software

EmotionEngine: Software for recognizing user emotions in real time.

SmartGlassesDisplay: Software for controlling the display of smart glasses.

API: External API for obtaining occupational information.

Program processing

User input

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist."

Getting information

Based on the entered occupation name, the server retrieves the occupation's average annual salary, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience via an external API.

Emotion recognition

The Emotion Engine recognizes the user's emotions in real time. For example, it determines whether the user is feeling stressed.

View information

The server adjusts the way the acquired information is displayed depending on the user's emotions. For example, if the user is feeling stressed, the information is displayed graphically. The software that controls the smart glasses' display (SmartGlassesDisplay) is used to display the information appropriately.

Specific examples

A career counselor wears smart glasses, and the user enters "data scientist." The system retrieves the average annual salary of data scientists, salary levels by region, industry trends, and more, and graphically displays if the user is feeling stressed.

Example prompt

"Please tell me the average annual salary of a data scientist, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

In this way, career counselors can provide users with more appropriate advice.

The flow of the specific processing in Application Example 2 is explained using Figure 18.

Step 1:

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist." This input information is sent from the smart device to the server.

Step 2:

The server sends a request to an external API based on the received occupation name. The API request includes the occupation name. The API response returns the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3:

The server stores the acquired occupational information in a database, which includes occupation titles, average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 4:

The Emotion Engine recognizes the user's emotions in real time. It uses the smart device's camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state. For example, it determines whether the user is feeling stressed.

Step 5:

The server receives emotional data from the emotion engine and adjusts how information is displayed based on the user's emotional state. For example, if the user is feeling stressed, the server can set the information to be displayed graphically.

Step 6:

The server sends the adjusted information to the smart device, which then displays the received information to the user. In the case of smart glasses, the SmartGlassesDisplay software is used to display the information appropriately.

Step 7:

Users can check the displayed information through their smart devices. For example, the average annual salary of a data scientist, salary levels by region, industry trends, and more are displayed graphically.

In this way, users can obtain occupational information in real time and receive appropriate information displayed according to their emotions.

The specific processing unit 290 transmits the results of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the headset-type terminal 314.

[Fourth embodiment]

Figure 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

As shown in FIG. 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I/F 44, and a control target 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and control target 443 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (e.g., an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

Figure 8 shows an example of the main functions of the data processing device 12 and robot 414.

As shown in FIG. 8, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the robot 414, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

"Example 2"

The system of the present invention accepts input of occupational titles and related information from users through a user interface. This user interface is provided via a web browser or dedicated application. When a user inputs an occupational title, the system retrieves information on the corresponding occupation from a database and calculates the average annual salary and regional salary levels. It also simultaneously retrieves industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user. As a specific example, if a user inputs "software engineer," the system calculates and retrieves the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and displays this information to the user.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their occupation name through the system's user interface. This user interface can be provided through a web browser or dedicated application.

Step 2: Based on the entered occupation name, the system retrieves information on the corresponding occupation from a database. This database includes information such as the average annual salary for each occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3: Based on the information obtained, the system calculates the average annual salary and salary levels in each region. It also simultaneously obtains industry trends, demand forecasts, and factors that affect income based on skills and experience. Step 4: The system displays the calculated and obtained information to the user. As a specific example, if the user enters "software engineer," the system will display the average annual salary for software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous occupational information systems had the problem of making it difficult for users to quickly and accurately obtain detailed information even when they entered the name of an occupation. In particular, they were unable to provide a wide range of information in a unified manner, such as average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for transmitting the input information to the server, means for the server to obtain information about occupations from a database, means for calculating average annual income and regional salary levels based on the obtained information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, and means for displaying the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations.

"Means for users to input their occupation name and related information" refers to means that provide an interface for users to input their occupation name and related information, and is realized through a web browser or dedicated application.

"Means for sending input information to the server" refers to the means for sending the occupation name and related information input by the user to the server, and is realized using a communication protocol such as an HTTP request.

"Means by which the server retrieves information about occupations from the database" refers to the means by which the server executes queries against the database and retrieves information about occupations, and is realized using database technologies such as SQL or NoSQL.

"Means for calculating average annual income and regional salary levels based on acquired information" refers to the means by which the server calculates average annual income for each occupation and regional salary levels based on information acquired from the database.

"Means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience" refers to a means by which the server analyzes industry trends, demand forecasts, and income fluctuation factors based on skills and experience, and provides these to users.

"Means for displaying calculated/obtained information to the user" refers to the means by which the server displays calculated/obtained information to the user through a user interface, and is realized using web technologies such as HTML, CSS, and JavaScript.

This invention is a system that allows users to input occupational titles and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. This system operates in cooperation with a server, terminal, and user.

Providing a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their job title and related information through this interface.

Accepting user input

The user enters their occupation and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server.

Submit input data

The device sends the occupation name entered by the user to the server. This is done via an HTTP request. Specifically, the input data is sent using the JavaScript fetch API.

Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it uses an SQL query to retrieve information about the occupation.

Data calculation and processing

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

Displaying information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

Specific examples and prompt sentence examples

As a concrete example, a user opens a web browser and types "software engineer" into the provided interface. The server retrieves information about software engineers from the database and calculates and displays the following information:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

An example prompt might be, "Please tell me the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily obtain detailed information about occupations.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Provide a user interface

The server provides a user interface through a web browser or dedicated application. This interface is built using web technologies such as HTML, CSS, and JavaScript. Users can enter their occupation name and related information through this interface. The input includes the occupation name and related information, and the output is the data entered by the user.

Step 2: Accept user input

The user enters the job title and related information into the provided interface. For example, they enter "software engineer" into a text box. This input data is sent by the terminal to the server. The input includes the job title and related information entered by the user, and the output is the input data sent to the terminal.

Step 3: Send input data

The device sends the occupation name entered by the user to the server. This transmission is performed via an HTTP request. Specifically, the input data is sent using JavaScript's fetch API. The input includes the occupation name entered by the user and related information, and the output is the data sent to the server.

Step 4: Retrieving information from the database

The server searches a database based on the received occupation name. The database is built using technologies such as SQL and NoSQL. For example, it retrieves information about occupations using an SQL query. The input includes the occupation name sent to the server, and the output is the occupation information retrieved from the database.

Step 5: Calculate and process data

The server calculates the following information based on the information obtained from the database:

Average annual income: Aggregate the annual income data in the database and calculate the average value.

Salary levels by region: Calculated by aggregating salary data by region.

Industry trends: Conduct trend analysis based on past data.

Demand forecasting: Predict future demand using generative AI models.

Factors that affect income based on skills and experience: Analyze factors that affect income based on data on skills and experience.

The input includes occupational information obtained from the database, and the output is various calculated information.

Step 6: Display information to users

The server sends the calculated and acquired information to the device in JSON format. The device displays the received data in a user interface. For example, it might display something like this using HTML and JavaScript:

Average annual income: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 7 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase in demand over the next five years

Income variability based on skill and experience: Knowledge of AI technology increases annual income by 10%

The input includes various calculated information, and the output is the information displayed on the user interface.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

In conventional occupational information systems, even if a user inputs the name of an occupation and related information, the information is simply displayed in text format, making it difficult for users to obtain information in a format that is intuitively easy to understand. Furthermore, because occupational information is not provided in virtual environments, users are unable to search for occupational information within virtual spaces.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual salary of the occupation and the salary level for each region based on the input information, means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience, means for displaying occupational information within the virtual environment, and means for the user to acquire occupational information while moving within the virtual environment. This allows the user to intuitively search for occupational information within the virtual space and acquire information in an easy-to-understand format.

"User" refers to an individual or corporation that uses the system to enter and obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, such as location, skills, years of experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that shows a prediction of future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to the number of years and type of practical experience in a particular occupation.

"Income variables" refers to factors that cause income to fluctuate in a particular occupation, including skills and experience.

A "virtual environment" is a virtual space created using computer technology in which users can interact.

"Display means" refers to a method or device for visually presenting information to the user.

"Means of movement" refers to methods or devices that allow a user to move freely within a virtual environment.

A system for implementing this invention allows users to input occupational titles and related information, and based on that information, calculates the average annual salary for the occupation and regional salary levels, and provides industry trends, demand forecasts, and factors that affect income based on skills and experience. Furthermore, this information is displayed within a virtual environment, allowing users to obtain occupational information while moving around within the virtual environment.

Hardware and software configuration

Hardware: Smartphone, head-mounted display

Software: Flask (a Python web framework), database (a Python dictionary was used as a dummy database)

System Operation

1. User input:

Users use a smartphone or head-mounted display to enter their job title and related information within the virtual environment. For example, a user might enter "software engineer."

2. Data acquisition and calculation:

The server retrieves relevant occupational information from a database based on the entered occupation name, including average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Displaying information:

The server displays the retrieved information to the user within the virtual environment. The user can intuitively explore this information while moving around within the virtual environment.

Specific examples

When a user types "software engineer" in the virtual store, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 7.5 million yen, Osaka: 7 million yen, Fukuoka: 6.5 million yen

Industry Trends: Increasing Demand

Demand forecast: 20% increase over the next five years

Factors that affect income: years of experience, skill set

Example prompt

Please enter your job title: Software Engineer

This system allows users to intuitively search for occupational information in a virtual space and obtain information in an easy-to-understand format.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The user uses a smartphone or head-mounted display to input their job title and related information within the virtual environment. The input information is then sent to the server. The input data includes the job title (e.g., "software engineer") and related information (e.g., region, skills, years of experience).

Step 2:

The server retrieves the relevant occupational information from a database based on the received occupation name. Specifically, it searches the database using the occupation name as a key to retrieve average annual income, regional salary levels, industry trends, demand forecasts, and factors that affect income fluctuations based on skills and experience. The input data is the occupation name, and the output data is a set of occupational information.

Step 3:

The server processes the data based on the acquired occupational information. For example, it converts regional salary levels into a format that makes them easier to compare, and graphs industry trends and demand forecasts. The input data is a set of occupational information, and the output data is the processed occupational information.

Step 4:

The server converts the processed occupational information into a data format for display within the virtual environment. Specifically, it generates data for display as 3D models and interactive UI elements. The input data is the processed occupational information, and the output data is the data for display.

Step 5:

The user explores the displayed occupational information while moving around the virtual environment. The user's movement information is sent to the server in real time, and the server updates the display content accordingly. The input data is the user's movement information, and the output data is the updated display content.

Step 6:

If the user wants more information about a specific occupation, they enter an additional prompt statement. The server retrieves more detailed information from the database based on this prompt statement and displays it in the virtual environment. The input data is the additional prompt statement, and the output data is the detailed occupation information.

Step 7:

When the user finishes searching for job information, the server saves the session data so the user can access it again later. The input data is the session data, and the output data is the saved session data.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

With conventional occupational information systems, even if users entered the name of an occupation, it was difficult to quickly and accurately obtain detailed salary information, industry trends, demand forecasts, or factors that affect income based on skills and experience. There was also a lack of ways to provide this information to users in an easy-to-understand manner. This meant that users were unable to obtain sufficient information for occupational selection and career planning, making it difficult for them to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes: a means for the user to input the name of an occupation and related information; a means for transmitting the input information to the server; a means for the server to obtain occupational information from a database; a means for calculating average annual income and regional salary levels based on the obtained information; a means for obtaining industry trends, demand forecasts, and income fluctuation factors based on skills and experience; and a means for providing the calculated and obtained information to the user. This allows users to quickly and accurately obtain detailed information about occupations, enabling them to make appropriate decisions when choosing an occupation or planning their career.

"User" refers to an individual or organization that uses the system to enter occupational information and obtain the necessary information.

"Occupation name and related information" refers to the name of the occupation and information related to that occupation that the user enters into the system.

A "server" is a computer system that receives information sent by users, retrieves the necessary information from a database, processes and calculates the data, and provides it to users.

A "database" is an information management system for storing data such as occupational information, salary information, industry trends, demand forecasts, and factors that affect income based on skills and experience.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average or median salary for a particular occupation in each region.

"Industry trends" refers to information about the current situation and future predictions in a particular industry.

"Demand forecasting" is the prediction of future demand for specific occupations or skills.

"Skill- and experience-based income variables" are factors that show the impact that specific skill sets and years of experience have on income.

"Means of providing information" refers to the methods and technologies used by the server to communicate the information it has acquired and calculated to the user.

"Means of displaying information" refers to methods or technologies that allow users to visually confirm information.

This invention is a system that allows users to input occupation names and related information, and based on that information, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. The system includes a user interface, a server, a database, and a means for displaying information.

The user enters their occupation name using a web browser or dedicated application. For example, they can use a web browser such as Google Chrome or Mozilla Firefox, or a dedicated mobile application. Once the user enters their occupation name, the device sends this information to the server. Specifically, the data is sent using an HTTP request.

The server retrieves the corresponding occupation information from a database based on the received occupation name. For example, it uses a database such as MySQL or PostgreSQL. The server performs the following data processing and calculations based on the retrieved information:

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

This information is sent from the server to the device and displayed to the user. The device then displays the results received from the server to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

As a concrete example, consider the case where a user enters "software engineer." The user enters their occupation in a web browser using Google Chrome. The device sends this information to a server, which retrieves information about software engineers from a database. The server calculates the average annual salary of software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, and sends this information to the device. Finally, the device displays this information to the user.

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

Using this prompt, the generative AI model can obtain the necessary information and provide it to the user.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

User enters occupation name

The user enters their occupational name using a web browser or dedicated application. For example, they open Google Chrome, access the system's web page, and enter "software engineer" in the input field. The input data is their occupational name.

Step 2:

The device sends the input data to the server.

The device sends the occupation name entered by the user to the server. Specifically, it sends data using an HTTP request. The input is the occupation name entered by the user, and the output is the occupation name data sent to the server. For example, the device sends the following JSON-formatted data to the server:

json

{

"Occupation": "Software Engineer"

}

Step 3:

The server retrieves occupation information from the database.

The server retrieves the corresponding occupation information from the database based on the received occupation name. The input is the occupation name data sent to the server, and the output is the occupation information retrieved from the database. For example, run the following SQL query using a MySQL database:

sql

SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer';

Step 4:

The server processes and calculates the data.

The server performs the following data processing and calculations based on the acquired data. The input is occupational information acquired from the database, and the output is the processed and calculated results.

Calculating average annual salary: Average the salary information obtained from the database.

Calculating salary levels for each region: Aggregating salary data by region.

Stay on top of the industry: Browse the latest industry reports and news.

Obtaining demand forecasts: Predict future demand based on past data.

Understanding factors that influence income fluctuations based on skills and experience: Analyze income fluctuations based on skill sets and years of experience.

Step 5:

The server sends the results to the device.

The server sends the processed and calculated results to the terminal. The input is the processed and calculated results, and the output is the resulting data sent to the terminal. Specifically, the server sends the following JSON-formatted data as an HTTP response:

json

{

"Average annual income": 7 million yen,

"Salary levels by region": {

"Tokyo": 8 million yen,

"Osaka": 7.5 million yen,

"Fukuoka": 7 million yen

},

"Industry Trends": "Demand is increasing due to advances in AI technology",

"Demand forecast": "20% increase over the next five years",

"Income fluctuation factors": "Python and Java skills are highly valued"

}

Step 6:

The device displays the results to the user.

The terminal displays the results received from the server to the user. The input is the result data sent from the server, and the output is the information displayed to the user. For example, the information might be displayed on a web page in the following format:

Software Engineer Information:

Average annual income: 7 million yen

Salary levels by region:

Tokyo: 8 million yen

Osaka: 7.5 million yen

Fukuoka: 7 million yen

Industry Trends: Demand is increasing due to advances in AI technology

Demand forecast: 20% increase over the next five years

Income fluctuation factors: Python and Java skills are highly valued

Example of a prompt to input to a generative AI model:

"Please tell me the average annual salary of a software engineer, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

With conventional career information systems, it was difficult for users to obtain detailed information about careers in real time, especially in a virtual environment. Furthermore, there was a lack of means to display information using smart devices, limiting the user experience. This meant that users were unable to obtain sufficient information when choosing a career or planning their career, making it difficult to make appropriate decisions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes means for users to input occupation names and related information, means for calculating the average annual salary of an occupation and regional salary levels based on the input information, means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience, means for users to obtain information about occupations in real time within the virtual environment, and means for displaying the information via a smart device. This allows users to obtain detailed information about occupations in real time within the virtual environment and visually confirm it via a smart device.

"User" means an individual or corporation that uses the system to input and obtain occupational information.

"Occupation name" is a name used to identify a specific occupation.

"Related information" refers to detailed data and attribute information related to an occupation.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries for occupations in a particular region.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that shows future demand prospects for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

A "virtual environment" is a virtual space or environment created using computer technology.

"Real-time" means that data and information are processed immediately and provided without delay.

"Smart device" refers to an electronic device with internet connectivity and advanced computing capabilities.

"Means for displaying information" refers to a method or device for visually providing information to the user.

The system for implementing this invention includes a server, a user terminal, and a smart device. The specific configuration and operation of the system are described below.

System Configuration

1. Server:

Hardware: Any cloud server (e.g., AWS EC2)

Software: Python, Flask, SQLite

Function: Accepts user input of occupation name and related information, retrieves relevant occupation information from a database, and calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

2. User device:

Hardware: Smartphones, tablets

Software: Web browser or dedicated application

Function: The user enters their occupation and related information and displays the information retrieved from the server.

3. Smart Devices:

Hardware: Head-mounted display (e.g., Oculus Quest)

Software: Unity (head-mounted display application development)

Function: Allows users to obtain and visually display career information in real time within a virtual environment.

Data processing and calculation

The server receives the occupation name and related information entered by the user and performs the following processes.

1. Retrieving information from the database:

Retrieve the relevant occupation information from the SQLite database.

2. Information Calculation:

Calculates average annual salary, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

3. Information provision:

The calculated information is sent to the user's terminal and smart device.

Specific examples

When a user types "software engineer" in the virtual environment, the following information is displayed:

Average annual salary: 7 million yen

Salary levels by region: Tokyo: 8 million yen, Osaka: 7.5 million yen, Fukuoka: 6.5 million yen

Industry Trends: Demand Increases Due to Advances in AI Technology

Demand forecast: 20% increase by 2025

Skill and experience-based income variables: AI and cloud technology skills are highly valued

Example prompt

Occupation: Software Engineer

Information obtained: average annual salary, regional salary levels, industry trends, demand forecasts, and factors affecting income based on skills and experience.

In this way, users can obtain detailed information about their occupation in real time within the virtual environment and visually view it via their smart device.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Users enter their occupation and related information.

Input: The user enters a job title (e.g., software engineer).

Operation: Enter your occupation and related information through the user's device interface.

Output: The entered occupation name and related information are sent to the server.

Step 2:

The server receives the entered information.

Input: Occupation name and related information sent from the user's device.

How it works: The server uses Flask to receive requests from users.

Output: The received occupation name and related information are processed within the server.

Step 3:

The server retrieves the relevant occupation information from the database.

Input: Received job name.

How it works: The server queries the SQLite database to retrieve information about the corresponding occupation.

Output: Average annual salary for occupations, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience are obtained.

Step 4:

Data processing and calculations are performed based on the information obtained by the server.

Input: Occupation information retrieved from the database.

How it works: The server uses Python to calculate average annual income and regional salary levels, and analyzes industry trends, demand forecasts, and factors that affect income based on skills and experience.

Output: Calculated and analyzed occupational information.

Step 5:

The server sends the calculated and analyzed information to the user's terminal and smart device.

Input: Calculated and analyzed occupational information.

How it works: The server uses Flask to send information to user terminals and smart devices.

Output: Occupation information is sent to the user's terminal and smart device.

Step 6:

Displays information received by user terminals and smart devices.

Input: Occupation information sent from the server.

How it works: The user's device displays information using a web browser or dedicated application, and the smart device uses Unity to visually display information within the virtual environment.

Output: Users can view detailed occupation information in real time.

In addition, an emotion engine that estimates the user's emotion may also be combined. That is, the identification processing unit 290 estimates the user's emotion using the emotion identification model 59, and the user's emotion

Specific processing may be performed using

"Example 1"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

"Example 2"

One embodiment of the present invention provides a system incorporating an emotion engine. This system includes a means for a user to input an occupation name and related information, a means for calculating the average annual salary for the occupation and the salary level for each region based on the input information, and a means for providing factors that affect income based on industry trends, demand forecasts, and skills and experience. Furthermore, the system includes an emotion engine that recognizes the user's emotions. This emotion engine includes a means for adjusting the display method of the average annual salary and the salary level for each region based on the user's emotions, and a means for adjusting the display method of the factors that affect income based on industry trends, demand forecasts, and skills and experience. Specifically, if the user feels stressed, the emotion engine adjusts the display method to provide information in a form that is easier for the user to understand. For example, adjustments are possible, such as displaying the average annual salary and the salary level for each region graphically, or explaining industry trends and demand forecasts in simple terms.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user enters their job title and related information into the system.

Step 2: Based on the information entered, the system calculates the average annual salary for each occupation and the salary level for each region.

Step 3: The system provides industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Step 4: The emotion engine recognizes the user's emotions.

Step 5: The emotion engine adjusts the way average annual salaries and regional salary levels are displayed based on user sentiment.

Step 6: The emotion engine uses user sentiment to adjust how it displays industry trends, demand forecasts, and income variables based on skills and experience.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional occupational information systems had the problem that even when users input the name of an occupation and related information, the information provided was uniform and could not be flexibly displayed according to the user's emotions or level of understanding. Furthermore, when providing detailed information such as industry trends, demand forecasts, and factors that affect income based on skills and experience, users could feel stressed and find it difficult to understand the information.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means for recognizing the user's emotions; and means for adjusting the display method based on the recognized emotions. This enables flexible information provision according to the user's emotions and level of understanding, making it easier for the user to understand detailed information about occupations without feeling stressed.

"User" refers to an individual or organization that uses the system to enter their occupational title and related information and obtain information.

"Occupation name" is the name that indicates a specific occupation and is part of the information that a user enters into the system.

"Related information" is additional information related to the occupation title that users can enter into the system.

"Means" refers to a method or device for achieving a specific function or purpose.

"Average annual income" is the average annual income of people engaged in a particular occupation.

"Regional salary levels" refers to the average and distribution of salaries by region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecasting" refers to predicting future demand for a particular occupation or industry.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to work experience and history in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, region, industry trends, etc.

An "emotion engine" is a technology that recognizes a user's emotions and adjusts the system's behavior and display methods based on those emotions.

"Means for adjusting the display method" refers to a method or device for changing the display format of information based on the user's emotions.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their job title and related information using a web browser (e.g., Google Chrome) or a dedicated application (e.g., iOS app). The user interface is built using web technologies such as HTML, CSS, and JavaScript.

Database

The server retrieves information about the corresponding occupation from a database (e.g., MySQL) based on the occupation name entered by the user. The database stores information on the average annual salary for each occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Information calculation

The server calculates the average annual salary and salary levels for each region based on information obtained from the database. For example, it calculates the national average annual salary and then calculates the difference between regions.

Get industry trends and demand forecasts

The server sends requests to external APIs (e.g., economic data APIs) to obtain information on industry trends, demand forecasts, and income fluctuations based on skills and experience. It then analyzes the obtained data and prepares the information to provide to the user.

View information

The server displays the calculated and acquired information to the user. For example, it displays it in graph or table format on a web browser. Users can check the average annual salary of software engineers, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Adjusting display methods using the emotion engine

The server uses an emotion engine (e.g., emotion recognition software) to recognize the user's emotions. If the emotion engine determines that the user is feeling stressed, the server adjusts the way it displays information, for example, by presenting it graphically or explaining it in simpler terms.

Specific examples

If the user types "software engineer," the server displays the following information:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Furthermore, if the emotion engine determines that the user is feeling stressed, the server will display this information graphically or explain it in simple terms.

Example prompt

"Please tell me the average annual salary of software engineers, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

This way, users can easily get detailed information about jobs.

The flow of the identification process in Example 1 will be explained using Figure 15.

Step 1:

Users enter their job title and related information using a web browser or dedicated application.

Enter: Occupation or related information (e.g., "Software Engineer")

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the occupation "Software Engineer" and clicks the submit button.

Step 2:

The server retrieves relevant occupation information from the database based on the occupation name entered by the user.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Specific operation: The server sends the query "SELECT FROM Occupation Information WHERE Occupation Name = 'Software Engineer'" to the database and retrieves the results.

Step 3:

The server calculates the average annual salary and salary levels for each region based on information obtained from the database.

Input: Occupational information obtained from the database (e.g., average annual salary, salary level by region)

Output: Calculated average annual income and salary levels for each region

Specific operation: The server analyzes the data it acquires and calculates the national average annual salary and salary levels by region.

Step 4:

The server sends requests to external APIs to obtain industry trends, demand forecasts, and income fluctuation factors based on skills and experience.

Input: User-entered occupation (e.g., "Software Engineer")

Output: Industry trends and demand forecast data obtained from external APIs

Specific operation: The server sends a request to an external API to obtain industry trends and demand forecast data.

Step 5:

The server displays the calculated and obtained information to the user.

Input: Calculated average annual salary, regional salary levels, industry trends and demand forecast data obtained from external APIs

Output: Information displayed to the user (e.g., occupational information displayed in graph or table format)

Specific operation: The server displays the information in graphs and tables on the web browser.

Step 6:

The server uses an emotion engine to recognize the user's emotions and adjust how they are displayed.

Input: User emotion data (e.g., whether they feel stressed)

Output: Tailored display (e.g., graphical display, simple explanation)

Specific operation: The server uses an emotion engine to analyze the user's emotions and displays information graphically or explains it in simple terms.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Traditional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience, based on the occupation name and related information entered by the user. However, they lack the ability to adjust the way information is displayed based on the user's emotions. Furthermore, there is a lack of means to provide information visually within a virtual space, making it difficult to provide information in a way that is intuitively easy for users to understand.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for visually displaying occupation information within a virtual space. This makes it possible to adjust the information display method according to the user's emotions and provide information visually within a virtual space.

"User" means an individual or corporation that uses the system to enter occupational information and obtain related information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" refers to information related to the job title, such as region, skills, experience, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" refers to information that shows the current situation and future predictions for the industry to which a particular occupation belongs.

"Demand forecast" is information that predicts future demand for a particular occupation.

"Skills" refer to the techniques and abilities required for a particular occupation.

"Experience" refers to practical experience in a particular occupation.

"Factors that affect income" refers to factors that affect income based on skills, experience, etc.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Virtual space" is a virtual space generated by a computer, an environment in which users can visually view information.

"Visually displaying" means presenting information to the user in a graphical format.

As an embodiment of this invention, we provide a system that allows users to input their occupation name and related information and visually confirm that information in a virtual space. Specific embodiments are described below.

System Configuration

The system consists of the following main components:

1. User terminal: A device such as a smartphone or head-mounted display that provides an interface for users to enter their occupation name and related information.

2. Server: Connects to the database to retrieve and process occupational information. Includes an emotion engine that adjusts the way information is displayed based on the user's emotions.

3. Database: Stores information such as average annual salary for occupations, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Program processing

The server performs the following process:

1. Accepting user input: Receive occupation name and related information from the user's device.

2. Retrieving information from the database: Retrieve relevant information from the database based on the entered occupation name.

3. Emotion Recognition: Use an emotion engine to recognize the user's emotions.

4. Adjusting how information is displayed: Adjust how information is displayed based on the user's emotions.

5. Display in virtual space: Display information visually in a virtual space.

Hardware and software used

Hardware: Smartphone, head-mounted display

Software: Python, EmotionRecognizer library, requests library, database API

Specific examples

When a user types "software engineer" on their smartphone, the server retrieves information about software engineers from the database. If the emotion engine recognizes the user's emotion as "stressed," the information is displayed concisely. For example, the average annual salary and regional salary levels are displayed graphically.

Example prompt

Example of a prompt to input to a generative AI model:

If a user types "software engineer" and the emotion engine identifies them as "stressed," briefly display the following information:

Average annual income

Salary levels by region

In this way, information can be provided in an easy-to-understand format even when users are feeling stressed.

The flow of the specific processing in Application Example 1 will be explained using Figure 16.

Step 1:

Users enter their occupation and related information.

Input: The user uses a smartphone or head-mounted display to enter their job title (e.g., "Software Engineer") and related information.

Output: The entered occupation name and related information are sent to the server.

Specific action: The user enters the name of their occupation into the interface and presses the submit button.

Step 2:

The server retrieves occupation information from the database.

Input: Occupation name and related information submitted by the user.

Output: Average annual salary for occupations retrieved from the database, salary levels for each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Specific operation: The server calls the database API and retrieves relevant information based on the entered occupation name.

Step 3:

The server uses an emotion engine to recognize the user's emotions.

Input: Emotional information such as the user's facial expressions and voice data.

Output: Recognized user emotion (e.g., "I feel stressed").

Specific operation: The server uses the EmotionRecognizer library to analyze the user's emotions.

Step 4:

The server adjusts how information is displayed based on the user's emotions.

Input: Recognized user emotion and occupational information obtained from the database.

Output: Adjusted information display format (e.g., concise display format).

Specific behavior: The server determines whether to display information graphically or concisely in text based on the user's emotions.

Step 5:

The server visually displays occupation information within the virtual space.

Input: Adjusted information display format and occupation information.

Output: Occupational information visually displayed in a virtual space.

Specific operation: The server generates a virtual space and sends information to the user's device to display it visually.

In this way, occupational information can be provided to users in an intuitive and easy-to-understand format.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional occupational information systems can provide average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience based on the occupation name entered by the user, but they lack the ability to adjust the way information is displayed based on the user's emotional state. As a result, there is an issue where appropriate information is not provided when the user is feeling stressed or has difficulty understanding the information.

The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input the name of an occupation and related information, means for calculating the average annual income of the occupation and the salary level for each region based on the input information, means for providing factors that affect income based on industry trends, demand forecasts, skills, and experience, means including an emotion engine that recognizes the user's emotions, and means for adjusting the display method based on the emotion engine. This makes it possible to provide appropriate information according to the user's emotional state.

A "user interface" is a means by which a user enters their job title and related information, and is provided through a web browser or dedicated application.

The "database" is an information management system for storing information such as average annual income by occupation, salary levels in each region, industry trends, demand forecasts, and factors that affect income based on skills and experience.

An "emotion engine" is a system that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Average annual income" refers to the average annual income of employees in a particular occupation.

"Salary level" refers to the general level of salary in a particular region or occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

A "demand forecast" is a forecast of future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

"Means for adjusting the display method" refers to means for changing the display format of information depending on the user's emotional state.

This invention is a system that allows users to input occupation names and related information and, based on that, provides the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. It also includes a function that recognizes the user's emotions and adjusts the way information is displayed based on those emotions.

System Configuration

User Interface

Users enter their occupational title and related information using a web browser (e.g., Google Chrome, Mozilla Firefox) or a dedicated application. The user interface provides a form for entering occupational title and related information.

Database

The server queries a database (e.g., MySQL, PostgreSQL) based on the job title entered by the user to retrieve the following information:

Average annual income by occupation

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

Calculating and displaying information

The server calculates average annual income and salary levels for each region based on the information it obtains. For example, let's say the national average annual income is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. It also simultaneously calculates factors that affect income based on industry trends, demand forecasts, and skills and experience. This information is displayed on the user's device.

Emotional Engine

As a user browses information, an emotion engine (e.g., Microsoft Azure Emotion API, IBM Watson Tone Analyzer) recognizes the user's emotions. For example, if the emotion engine determines that the user is feeling stressed, the server adjusts the display method. Specifically, it makes the following adjustments:

Display average annual income and regional salary levels in graphs (e.g., bar graphs, pie charts)

Explain industry trends and demand forecasts in simple terms

Specific examples

If the user enters "software engineer," the server retrieves and displays the following information:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

If the emotion engine determines that the user is feeling stressed, the server adjusts the display as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

Example prompt

Examples of prompts to input to a generative AI model include:

The user entered "software engineer." Retrieve and display the average annual salary for software engineers, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience. Also, adjust the display method if the user is feeling stressed.

By inputting this prompt into a generative AI model, the system provides appropriate information to the user and adjusts the display method as needed.

The flow of the identification process in Example 2 will be explained using Figure 17.

Step 1:

The user enters their occupational title and related information using a web browser or dedicated application. The user enters "software engineer" and clicks the "Submit" button. The input data is the occupational title "software engineer."

Step 2:

The server receives the user's job title "Software Engineer" and sends a query to the database. The server retrieves the following information from the database:

Average annual salary for software engineers

Salary levels by region

Industry trends

Demand forecast

Factors that affect income based on skills and experience

The data obtained is detailed information about occupations.

Step 3:

The server calculates the average annual salary and salary levels for each region based on the information obtained. For example, suppose the national average annual salary is 7 million yen, the average for the Tokyo region is 8 million yen, and the average for the Osaka region is 7.5 million yen. The calculated data is the average annual salary and salary levels for each region.

Step 4:

The server also simultaneously calculates factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience. For example, advances in AI technology are expected to increase demand, with growth of 20% predicted over the next five years. The calculated data includes factors that affect income fluctuations based on industry trends, demand forecasts, and skills and experience.

Step 5:

The server sends the calculated information to the user's device and displays it. The following information is displayed on the user's device:

Average annual salary for a software engineer (e.g., 7 million yen)

Salary levels by region (e.g., Tokyo: 8 million yen, Osaka: 7.5 million yen)

Industry trends (e.g., increased demand due to advances in AI technology)

Demand forecast (e.g., 20% growth predicted over the next five years)

Income fluctuations based on skills and experience (e.g., Python and Java skills are highly valued)

Step 6:

As a user browses information, the emotion engine recognizes the user's emotions. For example, the emotion engine determines that the user is feeling stressed. The input data is the user's emotional state.

Step 7:

The server adjusts the display method based on the emotion engine's judgment. For example, if the user is feeling stressed, the server adjusts the display method as follows:

Displays average annual income and regional salary levels in a bar graph.

Explain industry trends and demand forecasts in simple terms

The adjusted data is in a format that is easy for users to understand.

Step 8:

The server then sends the adjusted information back to the user's device and displays it. The adjusted information is then displayed on the user's device.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional career information systems have the problem that the information obtained when a user inputs a career name is static, and the way the information is displayed cannot be adjusted to suit the user's emotions or level of understanding. Furthermore, in career counseling at brick-and-mortar stores, there is a lack of a way to provide career information in real time and display the information appropriately based on the user's emotions.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes: means for the user to input the name of an occupation and related information; means for calculating the average annual salary of the occupation and the salary level for each region based on the input information; means for providing industry trends, demand forecasts, and income fluctuation factors based on skills and experience; means including an emotion engine that recognizes the user's emotions; means for adjusting the information display method based on the user's emotions; and means for displaying information through a smart device. This makes it possible to provide appropriate information based on the user's emotions, and to provide information in real time even in career counseling at physical stores.

"User" means an individual or organization that uses the system to obtain occupational information.

"Occupation name" is the name entered by the user to indicate a specific occupation.

"Related information" is additional information related to the job title, including skills, experience, location, etc.

"Average annual income" is a number that indicates the average annual income for a particular occupation.

"Salary levels in each region" is a number that indicates the average salary in each region for a particular occupation.

"Industry trends" is information that shows the current situation and future predictions in a particular industry.

"Demand forecast" is information that predicts future demand for a particular occupation or industry.

"Income variability factors based on skill and experience" are factors that show the impact that specific skills and experience have on income.

An "emotion engine" is software or hardware that recognizes a user's emotions and adjusts the way information is displayed based on those emotions.

"Smart device" means an internet-enabled device used to display information, including smart glasses and smartphones.

"Means to adjust the way information is displayed" is a function that allows you to change the way information is displayed depending on the user's emotions.

The following system configuration is described as an embodiment of this invention.

System Configuration

Hardware

Smart devices: Use internet-enabled devices such as smart glasses or smartphones.

Server: A server is used to manage occupational information and provide information in response to user requests.

Emotion engine: Includes hardware or software for recognizing user emotions.

Software

EmotionEngine: Software for recognizing user emotions in real time.

SmartGlassesDisplay: Software for controlling the display of smart glasses.

API: External API for obtaining occupational information.

Program processing

User input

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist."

Getting information

Based on the entered occupation name, the server retrieves the occupation's average annual salary, regional salary levels, industry trends, demand forecasts, and income fluctuation factors based on skills and experience via an external API.

Emotion recognition

The Emotion Engine recognizes the user's emotions in real time. For example, it determines whether the user is feeling stressed.

View information

The server adjusts the way the acquired information is displayed depending on the user's emotions. For example, if the user is feeling stressed, the information is displayed graphically. The software that controls the smart glasses' display (SmartGlassesDisplay) is used to display the information appropriately.

Specific examples

A career counselor wears smart glasses, and the user enters "data scientist." The system retrieves the average annual salary of data scientists, salary levels by region, industry trends, and more, and graphically displays if the user is feeling stressed.

Example prompt

"Please tell me the average annual salary of a data scientist, salary levels by region, industry trends, demand forecasts, and factors that affect income based on skills and experience."

In this way, career counselors can provide more appropriate advice to users.

The flow of the specific processing in Application Example 2 will be explained using Figure 18.

Step 1:

A user uses a smart device to enter their job title and related information. For example, the user enters "data scientist." This input information is sent from the smart device to the server.

Step 2:

The server sends a request to an external API based on the received occupation name. The API request includes the occupation name. The API response returns the average annual salary for the occupation, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 3:

The server stores the acquired occupational information in a database, which includes occupation titles, average annual salaries, regional salary levels, industry trends, demand forecasts, and factors that affect income based on skills and experience.

Step 4:

The Emotion Engine recognizes the user's emotions in real time. It uses the smart device's camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state. For example, it determines whether the user is feeling stressed.

Step 5:

The server receives emotional data from the emotion engine and adjusts how information is displayed based on the user's emotional state. For example, if the user is feeling stressed, the server can set the information to be displayed graphically.

Step 6:

The server sends the adjusted information to the smart device, which then displays the received information to the user. In the case of smart glasses, the SmartGlassesDisplay software is used to display the information appropriately.

Step 7:

Users can check the displayed information through their smart devices. For example, the average annual salary of a data scientist, salary levels by region, industry trends, and more are displayed graphically.

In this way, users can obtain occupational information in real time and receive appropriate information displayed according to their emotions.

The specific processing unit 290 transmits the results of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the robot 414.

The emotion identification model 59, which serves as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see Figure 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

Figure 9 shows an emotion map 400 on which multiple emotions are mapped. In emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both emotions and mental states. Emotions that are generally generated from reactions that occur in the brain are arranged on the left side of the concentric circles. Emotions that are generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged above and below the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the top side of the concentric circles, and the emotion of "discomfort" is arranged on the bottom side. In this way, emotion map 400 maps multiple emotions based on the structure by which emotions are generated, with emotions that tend to occur simultaneously being mapped close together.

These emotions are distributed in the 3 o'clock direction on emotion map 400, and usually fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness takes precedence over internal sensations, resulting in a sense of calm.

The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible (expressed in behavior) the emotion becomes.

Here, human emotions are based on various balances such as posture and blood sugar levels, and when these balances deviate from the ideal, it indicates discomfort, and when they approach the ideal, it indicates pleasure. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and remaining battery life, so that when these balances deviate from the ideal, it indicates discomfort, and when they approach the ideal, it indicates pleasure. Emotion maps may be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and emotional brain physiological signal analysis systems, Tokushima University, doctoral dissertation: https://ci.nii.ac.jp/naid/500000375379). The left half of the emotion map is lined with emotions belonging to an area called "reaction," where sensation is dominant. The right half of the emotion map is lined with emotions belonging to an area called "situation," where situational awareness is dominant.

The emotion map defines two emotions that encourage learning. One is the negative emotion around the middle of "repentance" or "reflection" on the situation side. In other words, this is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the positive emotion around "desire" on the response side. In other words, this is when the robot experiences positive feelings such as "I want more" or "I want to know more."

The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are close to each other have similar values, as in the emotion map 900 shown in Figure 10. Figure 10 shows an example in which multiple emotions, such as "relieved," "calm," and "reassuring," have similar emotion values.

In the above embodiment, an example was given in which a specific process is performed by a single computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may also be performed by multiple computers, including computer 22.

In the above embodiment, an example was described in which the specific processing program 56 is stored in the storage 32, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

It is not necessary to store the entire specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entire specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

The following types of processors can be used as hardware resources for executing specific processes. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource for executing specific processes by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which are processors with a circuit configuration designed specifically for executing specific processes. All processors have built-in or connected memory, and all use the memory to execute specific processes.

The hardware resource that executes the specific processing may be composed of one of these various processors, or may be composed of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). The hardware resource that executes the specific processing may also be a single processor.

As an example of a configuration using a single processor, first, there is a configuration in which one processor is configured using a combination of one or more CPUs and software, and this processor functions as a hardware resource that executes specific processing. Second, there is a configuration in which a processor is used to realize the functions of an entire system, including multiple hardware resources that execute specific processing, on a single IC chip, as typified by SoC (System-on-a-chip). In this way, specific processing is realized using one or more of the various processors listed above as hardware resources.

More specifically, the hardware structure of these various processors can be an electrical circuit that combines circuit elements such as semiconductor devices. Furthermore, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps can be added, or the processing order can be rearranged, all within the scope of the spirit of the invention.

The above-described written content and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above explanation of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or substitutions may be made to the above-described written content and illustrations, as long as they do not deviate from the spirit of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described written content and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

All publications, patent applications, and technical standards mentioned in this specification are incorporated by reference herein to the same extent as if each individual publication, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

The following is further disclosed regarding the above embodiments.

(Claim 1)
A system that includes a means for a user to input the name of an occupation and related information, a means for calculating the average annual salary for an occupation and the salary level for each region based on the input information, and a means for providing industry trends, demand forecasts, and factors that affect income based on skills and experience.

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

(Claim 4)
The system of claim 1 , further comprising an emotion engine that recognizes emotions of the user.

(Claim 5)
The system of claim 4 , wherein the emotion engine further comprises means for adjusting how average annual salaries and regional salary levels are displayed based on the user's emotions.

(Claim 6)
The system of claim 4 , wherein the emotion engine further comprises means for adjusting a display method of industry trends, demand forecasts, and skill- and experience-based income fluctuation factors based on the user's emotions.

"Example 1"

(Claim 1)
A means for users to enter their job title and related information;
means for transmitting the input information to a server;
a means for the server to retrieve information about occupations from a database;
A method for calculating average annual income and salary levels in each region based on the information obtained,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
A means for displaying the calculated and acquired information to the user;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

"Application Example 1"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
a means for displaying occupational information within the virtual environment;
a means for users to obtain occupational information while moving through the virtual environment;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

"Example 2"

(Claim 1)
A means for users to enter their job title and related information;
means for transmitting the input information to a server;
A means for the server to retrieve occupational information from a database;
A method for calculating average annual income and salary levels in each region based on the information obtained,
A means of obtaining industry trends, demand forecasts, and income fluctuation factors based on skills and experience;
a means for providing the calculated and obtained information to the user;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual salary or salary level to the user.

(Claim 3)
The system of claim 1 further comprising means for displaying to the user industry trends and demand forecasts provided, as well as factors that may affect income based on skills and experience.

"Application Example 2"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
a means for users to obtain real-time information about occupations within the virtual environment;
a means of displaying information through a smart device;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

"Example 1: Combining Emotion Engines"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
a means of recognizing a user's emotions;
means for adjusting the display method based on the recognized emotion;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual salary or salary level to the user.

(Claim 3)
The system of claim 1 further comprising means for displaying to the user industry trends and demand forecasts provided, as well as factors that may affect income based on skills and experience.

"Application example 1 when combining emotion engines"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
means including an emotion engine for recognizing an emotion of a user;
a means for adjusting how information is displayed based on user sentiment;
a means for visually displaying occupational information within the virtual space;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

"Example 2: Combining Emotion Engines"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
means including an emotion engine for recognizing an emotion of a user;
a means for adjusting the display method based on the emotion engine;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

"Application Example 2: Combining Emotion Engines"

(Claim 1)
A means for users to enter their job title and related information;
A means to calculate the average annual salary of an occupation and the salary level of each region based on the input information,
A means of providing industry trends, demand forecasts, and income variables based on skills and experience;
means including an emotion engine for recognizing an emotion of a user;
a means for adjusting how information is displayed based on user sentiment;
a means of displaying information through a smart device;
A system including:

(Claim 2)
The system of claim 1 further comprising means for displaying the calculated annual income or salary level to a user.

(Claim 3)
The system according to claim 1 , further comprising means for displaying to a user the provided industry trends, demand forecasts, and factors that may affect income based on skills and experience.

10, 210, 310, 410 Data processing system 12 Data processing device 14 Smart device 214 Smart glasses 314 Headset type terminal 414 Robot

Claims (3)

A means for accepting input of occupation name and related information;
a means for identifying user emotions using an emotion engine;
means for generating a prompt sentence that instructs the generation of an analysis result that takes into account factors that change income, based on the input occupation name and related information;
A means for generating the analysis result by a generative AI model using the generated prompt sentence and an AI model capable of performing at least one of analysis, classification, prediction, and summarization inferences ;
and means for displaying the analysis results as a 3D model or an element of an interactive user interface in a virtual environment by adjusting the display method according to the user's emotions, and updating the display content of the analysis results in real time based on the user's movement information . The system described in claim 1, wherein the means for adjusting the display method according to the user's emotions displays the analysis results in a display method that is visually easy for the user to understand, or in words that are linguistically easy for the user to understand. The system of claim 1, further comprising means for displaying the analysis results in a manner that allows comparisons to be made depending on factors that cause fluctuations in the income.