JP7764028B2 - Information processing device, information processing method, and program - Google Patents

Description

The present invention relates to an information processing device that acquires and outputs a recruitment score using job information.

In the past, there were recruitment support servers that could prove that a job seeker had the skills, knowledge, and qualifications based on documents related to the job seeker, in order to match them with personnel for a variety of jobs that require a high level of expertise (see Patent Document 1).

Japanese Patent Application Laid-Open No. 2021-056883

However, conventional technology only supports matching of personnel recruitment, and it is difficult to provide support when recruiting or opening a new store. More specifically, conventional technology does not allow for the acquisition of scores related to recruitment or store openings using recruitment information from other companies. Examples of recruitment scores include the difficulty of recruitment (described below) and the recommendation level for opening a store (described below).

The information processing device of the first invention is an information processing device that includes a other company's job information acquisition unit that acquires other company's job information regarding job openings at one or more other companies, a score acquisition unit that acquires a hiring score using the one or more other company's job information acquired by the other company's job information acquisition unit, and a score output unit that outputs the score.

This configuration allows you to obtain a recruitment score using job information from other companies.

In addition, the information processing device of the second invention is an information processing device that, compared to the first invention, further includes a company recruitment information acquisition unit that acquires company recruitment information related to job openings at the company, and the score acquisition unit acquires a recruitment score using one or more other company recruitment information and the company's recruitment information.

With this configuration, you can obtain a recruitment score using job information from other companies and your own job information.

In addition, the information processing device of the third invention is an information processing device that, compared to the second invention, further comprises an appeal information acquisition unit that acquires appeal information that identifies differences between the employer's own job information and one or more other companies' job information that are advantageous to the employer, and an appeal information output unit that outputs the appeal information.

With this configuration, you can use job information from other companies and your own job information to propose your company's selling points.

The information processing device of the fourth invention is an information processing device according to any one of the first to third inventions, wherein the other company's job information acquisition unit acquires, for each of one or more areas, job information from one or more other companies relating to job openings at each of the one or more areas; the score acquisition unit acquires a score for each of the one or more areas; and the score output unit outputs the score for each area on a map.

This configuration allows us to clearly present recruitment scores for each area using job information from other companies.

In addition, the information processing device of the fifth invention is different from the information processing device of the fourth invention in that the job information of other companies corresponds to one or more attribute values including an area identifier that identifies the area, and further includes an attribute value receiving unit that receives the one or more attribute values, and an area determination unit that uses the one or more attribute values received by the attribute value receiving unit to determine one or more areas from which to obtain job information of other companies, and the other company's job information acquisition unit acquires one or more job information of other companies that corresponds to any of the one or more areas determined by the area determination unit.

This configuration allows us to suggest appropriate areas for obtaining recruitment scores.

Furthermore, the information processing device of the sixth invention is an information processing device according to any one of the first to fifth inventions, wherein the other company's job information acquisition unit acquires two or more other company's job information in chronological order from at least one other company, and the score acquisition unit acquires a score using the two or more other company's job information in chronological order.

This configuration allows you to obtain a recruitment score using time-series job information from other companies.

Furthermore, the information processing device of the seventh invention is an information processing device according to any one of the first to fifth inventions, wherein the job information from other companies includes salary information or working hours information, and the score acquisition unit acquires one or more element information from the salary information contained in the job information from other companies, the working hours information contained in the job information from other companies, the number of other companies in the target area, and salary increase information acquired from the salary information contained in the time-series job information from other companies, and acquires a score using the element information.

With this configuration, appropriate factor information obtained using job information from other companies can be used to obtain an appropriate recruitment score.

The information processing device of the present invention allows you to obtain a recruitment score using job information from other companies.

Conceptual diagram of information system A in embodiment 1 Block diagram of the information system A Flowchart illustrating an example of the operation of the broadcast processing device 1 10 is a flowchart illustrating an example of the first area determination process. 10 is a flowchart illustrating an example of the second area determination process. A flowchart illustrating an example of a process for acquiring the score Flowchart for explaining an example of a process for acquiring job information from other companies A flowchart illustrating an example of the appeal information acquisition process Flowchart illustrating an example of the output information configuration process A diagram showing the area information management table A diagram showing the job information management table Figure showing an example of output information A diagram explaining the algorithm for determining the area A diagram explaining the algorithm for determining the area Figure showing an example of output information Figure showing an example of output information A diagram showing the appeal information management table Figure showing an example of output of the appeal information, etc. Overview of the computer system Block diagram of the computer system

Embodiments of information processing devices and the like will be described below with reference to the drawings. Note that components with the same reference numerals in the embodiments perform similar operations, and therefore may not be described again.

(Embodiment 1)
In this embodiment, an information processing device is described that obtains and outputs a recruitment score (for example, referred to as the difficulty of recruitment) using recruitment information from one or more other companies. Note that the element information used to obtain the score is, for example, salary, the number of other companies in the area, length of working hours, salary increase rate, etc. Recruitment information from other companies is information about recruitment from other companies. Recruitment information from other companies is, for example, recruitment information entered by referring to recruitment information posted on a website or in a free paper. Recruitment information from two or more other companies may include recruitment information from the company that is posted on a website, a free paper, etc.

In addition, in this embodiment, we will describe an information processing device that uses job information from one or more other companies located in one or more areas to obtain and output a score related to recruitment in each of one or more areas.

In this embodiment, we will also describe an information processing device that acquires and outputs scores using the company's own recruitment information. The company's own recruitment information is information about recruitment within the company. The company's own recruitment information does not have to have the same data structure as the recruitment information of other companies. The company's own recruitment information may be a portion of the information of other companies' recruitment information (for example, only salary, or only salary and working hours).

In this embodiment, an information processing device will be described that uses other company's job information and one's own company's job information to acquire and output one's own company's selling points.
An information processing device will be described.

In this embodiment, we will also describe an information processing device that graphically outputs the scores for one or more areas on a map.

In this embodiment, we will also describe an information processing device that automatically determines the area in which the score should be obtained.

Furthermore, in this embodiment, we will describe an information processing device that uses two or more time-series job information from other companies to obtain and output a score (e.g., a store recommendation rating).

In this embodiment, information A being associated with information B means that information B can be obtained from information A, or information A can be obtained from information B, and the method of association is not important. Information A and information B may be linked, may exist in the same buffer, information A may be included in information B, or information B may be included in information A, etc.

Figure 1 is a conceptual diagram of information system A in this embodiment. Information system A includes an information processing device 1, one or more job information management devices 2, and one or more terminal devices 3.

The information processing device 1 is a device that uses recruitment information from other companies to obtain and output a recruitment score. The meaning of the score is not important. The score is, for example, a recruitment difficulty level that indicates the difficulty or ease of recruiting. The score is, for example, a store opening recommendation level that indicates the ease or difficulty of opening a store.

The job information management device 2 is a device that manages job information. The job information management device 2 is typically a device that manages publicly available job information. The job information management device 2 may be considered the same as, for example, a website that publishes job information.

The information processing device 1 and the job information management device 2 are typically so-called servers, such as cloud servers or ASP servers. Note that the types of the information processing device 1 and the job information management device 2 are not important.

The terminal device 3 is a terminal used by a user. The user may be, for example, a person in charge or a manager of a company that is looking to hire. The user may be, for example, a person who wants to obtain a score or an appeal point, as described below. The terminal device 3 may be, for example, a personal computer, tablet device, smartphone, etc., and the type does not matter.

The information processing device 1 and one or more job information management devices 2, and the information processing device 1 and one or more terminal devices 3, can communicate via a network such as the Internet or a LAN.

Figure 2 is a block diagram of information system A in this embodiment.

The information processing device 1 includes a storage unit 11, a reception unit 12, a processing unit 13, and an output unit 14. The storage unit 11 includes an area information storage unit 111 and a job information storage unit 112. The reception unit 12 includes an attribute value reception unit 121. The processing unit 13 includes an other company's job information acquisition unit 131, a company's own job information acquisition unit 132, an area determination unit 133, a score acquisition unit 134, and an appeal information acquisition unit 135. The output unit 14 includes a score output unit 141 and an appeal information output unit 142.

The terminal device 3 includes a terminal storage unit 31, a terminal reception unit 32, a terminal processing unit 33, a terminal transmission unit 34, a terminal reception unit 35, and a terminal output unit 36.

The storage unit 11 that constitutes the information processing device 1 stores various types of information. The various types of information include, for example, one or more pieces of area information (described below), one or more pieces of job information (described below), one or more attribute values (described below), two or more pieces of training data, a learning device, a correspondence table, map information, one or more pieces of station information, a key word dictionary, a level table (described below), appeal conditions (described below), and appeal information (described below). The one or more pieces of job information include other companies' job information (described below). The one or more pieces of job information may also include the company's own job information (described below).

The training data includes one or more element information and a score. The training data is, for example, the information that forms the basis for constructing a learning device for calculating a score. The training data is, for example, the information that forms the basis for constructing the correspondence table described below. The element information is the information that is the basis for obtaining a score. The element information is information that can be obtained from other companies' job information, or from your own company's job information, or from other companies' job information and your own company's job information. The job information from other companies may also be chronologically arranged job information from other companies. The chronologically arranged job information from other companies is job information from the same organization, but from two or more other companies with different posting dates. The chronologically arranged job information from other companies is appropriately referred to as a set of other companies' job information. The element information is, for example, salary information contained in the job information from other companies, working hours information contained in the job information from other companies, the number of other companies in the target area, and salary increase information obtained from two or more salary information contained in the set of job information from other companies.

A learner is information used to obtain a score through machine learning prediction processing. A learner is information obtained as a result of machine learning learning processing using two or more pieces of training data. Note that the algorithms used for the machine learning learning processing and machine learning prediction processing are not important. Examples of machine learning methods that can be used include deep learning, random forests, decision trees, and SVR.

The correspondence table contains two or more pieces of correspondence information. The correspondence information is information that indicates the correspondence between a vector whose elements are one or more pieces of element information and a score. The correspondence information, for example, contains a vector whose elements are one or more pieces of element information and a score. The correspondence information is, for example, training data.

Map information is information used to display the score for each area on a map. The data structure of the map information is not important.

A key word dictionary contains a collection of key words for obtaining element information. A key word dictionary contains, for example, two or more records of key words and ideal values. Examples of (key word, ideal value) pairs are (newly opened, True), (year opened, 0), (working hours, 10:00-14:00), (direct commute, Treu), (driving, False), and (night shift, False). The ideal value "True" means that the corresponding key word is included in the job information. The ideal value "False" means that the corresponding key word is not included in the job information.

The area information storage unit 111 stores one or more pieces of area information. Area information is information about an area on a map. Area information includes, for example, an area identifier, range specification information, and one or more pieces of station information. The area identifier is information that specifies an area. The area identifier is, for example, an area name or an area ID. The area name is, for example, a city, town, village, ward, or prefecture name. Range specification information is information that specifies the range of an area. Range specification information is, for example, information that specifies the position information (e.g., (latitude, longitude)) of three or more vertices of a polygonal (e.g., rectangular) area. Range specification information is, for example, the position information (e.g., (latitude, longitude)) of the center point of the area. Station information is information about stations. The station information included in the area information is information about stations within the area. Station information includes, for example, a station identifier, a station name, the name of the station's line, station position information (e.g., (latitude, longitude)), and the station's address. The station identifier is information that identifies a station. The station identifier is, for example, the station ID or station name. The area may be the area where the job information is posted, the area where the hiring organization is located, or the area where the job seeker lives. The area may be a mechanically divided part of the map information, or it may be a city, town, ward, prefecture, etc.

The job information storage unit 112 contains one or more job information items. The job information in the job information storage unit 112 is, for example, job information obtained from the job information management device 2 or job information received from the terminal device 3. The job information in the job information storage unit 112 includes job information from other companies.

Job information is information related to job openings. Job information includes, for example, salary information, working hours information, nearest station information, address information, area identifiers, and character string information.

Salary information is information related to salary. Salary information is, for example, information indicating monthly or hourly salary.

Working hour information is information related to working hours. Examples of working hour information include information indicating the length of working hours (e.g., "7.5 hours" or "8 hours"), information indicating the working time period (e.g., "9:00-18:00" or "10:00-14:00"), and information indicating that it is a "night shift."

The nearest station information is information that identifies the nearest station. For example, the nearest station ID and the nearest station name are included.

Address information is information that indicates an address. Address information may include the street number, or may include only part of the address (for example, the street name).

Character string information is information about a string of characters. Examples of character string information include information indicating that the establishment is a "newly opened establishment," information indicating the number of years since the establishment, information about the age range of employees, information indicating whether "reduced working hours" are possible, information indicating whether direct commutes are possible, and information indicating whether driving is required.

The reception unit 12 receives various instructions and information. The various instructions and information include, for example, output instructions, attribute values (described below), and one or more pieces of access information. The output instructions are instructions to output a score, appeal information, or a score and appeal information. The output instructions include, for example, the company's job information.

Access information is information for obtaining job information from the job information management device 2. One or more pieces of access information correspond to a job information management device 2. The access information is, for example, information about the API for obtaining job information from the job information management device 2, or an execution module for obtaining job information from the job information management device 2.

Here, "reception" typically refers to the reception from terminal device 3 of information, instructions, etc. transmitted via a wired or wireless communication line, but the concept may also include the reception of information entered from input devices such as a keyboard, mouse, or touch panel, or the reception of information read from recording media such as optical disks, magnetic disks, or semiconductor memories.

The attribute value receiving unit 121 receives one or more attribute values. Each of the one or more attribute values is an attribute value of the organization (here, referred to as the company) to which the user who outputs the score belongs. Examples of attribute values include the company's industry, the company's train line, the company's nearest station, and the company's address. Each of the one or more attribute values received by the attribute value receiving unit 121 can be thought of as the company's job information.

The processing unit 13 performs various processes. These processes are, for example, processes performed by the other company's job information acquisition unit 131, the company's job information acquisition unit 132, the area determination unit 133, the score acquisition unit 134, and the appeal information acquisition unit 135.

The other company's job information acquisition unit 131 acquires one or more pieces of other company's job information. The other company's job information acquisition unit 131 acquires one or more pieces of other company's job information, for example, from the job information management device 2. The other company's job information acquisition unit 131 receives one or more pieces of other company's job information, for example, from the terminal device 3. The other company's job information acquisition unit 131 acquires one or more pieces of other company's job information, for example, from the job information storage unit 112.

Other company job information is job information from other companies. Other company job information typically has a other company identifier, which is the identifier of the other organization. The organization is typically a company, but it can also be an association, a sole proprietorship, or any other type.

It is preferable that other company's job information be associated with one or more attribute values including an area identifier. Attribute values include, for example, a media identifier, industry, job, address, salary, working hours, train line, nearest station, and publication date. The media identifier is information that identifies the media in which the other company's job information was published. The media identifier is, for example, an identifier for the job site or the identifier for the free paper in which the job information was published. The job is information that indicates the content of the job. The publication date is the date the job information was published on the job site, free paper, etc.

The other company's job information acquisition unit 131 acquires, for example, for each of one or more areas, job information from one or more other companies relating to each area. The job information from other companies acquired for each area is typically associated with an area identifier. Note that the job information from one or more other companies relating to one or more jobs corresponding to an area is, for example, job information from one or more other companies located in the area. The job information from one or more other companies relating to an area is, for example, job information from other companies located in one or more areas that meet the commuting conditions for the area.

The other company's job information acquisition unit 131 acquires, for example, one or more pieces of other company's job information corresponding to one of the one or more areas determined by the area determination unit 133.

It is preferable that the other company's job information acquisition unit 131 acquires two or more other company's job information in chronological order for at least one other company.

The other company's job information acquisition unit 131, for example, acquires one or more pieces of other company's job information from one or more job information management devices 2. The other company's job information acquisition unit 131, for example, crawls to acquire one or more pieces of other company's job information from one or more job information management devices 2. Note that the other company's job information acquisition unit 131, for example, acquires access information corresponding to the other company's job information acquisition unit 131 from the storage unit 11 and uses the access information to acquire one or more pieces of other company's job information from the job information management device 2. The technology by which the other company's job information acquisition unit 131 crawls and acquires one or more pieces of other company's job information from one or more job information management devices 2 is publicly known, so a detailed explanation will be omitted.

The company's own recruitment information acquisition unit 132 acquires company's own recruitment information. Company's own recruitment information is information related to recruitment within the company. Company's own recruitment information includes, for example, salary, working hours, nearest station, address, and area identifier. Note that company's own recruitment information may include information that is different from other companies' recruitment information, or may not include information included in other companies' recruitment information. Company's own recruitment information may, for example, include only salary information or only working hours information.

The company's job information acquisition unit 132 acquires company's job information received by the reception unit 12 from the terminal device 3, for example. The company's job information acquisition unit 132 receives company's job information from the terminal device 3, for example.

The area determination unit 133 determines one or more areas from which to obtain other company job information, using one or more attribute values accepted by the attribute value acceptance unit 121. Note that the one or more attribute values may be, for example, the company's own job information.

The area determination unit 133 determines, for example, the area that includes the company's company and the areas that are commutable to that area. A commutable area is an area that meets the commutability conditions. Areas that are commutable to a certain point or area (for example, the company) are, for example, areas that can be traveled to from a certain point or area within a threshold amount of time, areas that are within a threshold distance from a certain point or area, areas along the same train line as the nearest station to a certain point or area, and areas along the same train line as the nearest station to a certain point or area, and that include stations where the travel time from the nearest station is within a threshold amount of time. Note that any algorithm can be used to determine areas that are commutable to a certain point or area.

The area determination unit 133 determines one or more areas, for example, using the company's nearest station accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, references one or more pieces of area information in the storage unit 11 to determine an area that includes the company's nearest station accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, references one or more pieces of area information in the storage unit 11 to determine two or more areas that include an area that includes the company's nearest station accepted by the attribute value acceptance unit 121 and one or more areas that include stations on the same line as the nearest station. The area determination unit 133, for example, references one or more pieces of area information in the storage unit 11 to determine one or more areas whose distance from the location of the company's nearest station accepted by the attribute value acceptance unit 121 is within a threshold.

The area determination unit 133 determines one or more areas, for example, using the company's train lines accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, references one or more area information in the storage unit 11 and determines two or more areas including one or more areas that include stations along the same train line as the company's train lines accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, references one or more area information in the storage unit 11 and determines two or more areas including one or more areas that include stations along the same train line as the company's train lines accepted by the attribute value acceptance unit 121 and that are within a threshold travel time from the company's nearest station.

The area determination unit 133 determines one or more areas, for example, using the company's address accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, references one or more pieces of area information in the storage unit 11 to determine one or more areas whose distance from the company's address is within a threshold value.

The area determination unit 133 may, for example, determine one or more areas that are commutable to the area in which the company is located, and then determine, for each of the one or more areas, an area that is commutable to each of the one or more determined areas.

The score acquisition unit 134 acquires a recruitment score using one or more pieces of other company recruitment information acquired by the other company recruitment information acquisition unit 131. The score acquisition unit 134 typically acquires one or more pieces of element information from one or more pieces of other company recruitment information, and acquires a score using the one or more pieces of element information. The score may be, for example, the difficulty of recruitment or the degree of recommendation for opening a store.

The score acquisition unit 134 acquires a score, for example, using one or more other company's job information and the company's own job information. The score acquisition unit 134 acquires one or more element information, for example, using one or more other company's job information and the company's own job information, and acquires a score using the one or more element information.

The score acquisition unit 134 acquires a score, for example, using a set of job information from one or more other companies. The set of job information from other companies contains job information from two or more other companies in chronological order. The score acquisition unit 134 acquires one or more pieces of element information, for example, using the set of job information from one or more other companies, and acquires a score using the one or more pieces of element information.

It is preferable that the score acquisition unit 134 acquires a score for each of one or more areas. It is preferable that the score acquisition unit 134 acquires a score for each of one or more areas determined by the area determination unit 133. For example, the score acquisition unit 134 acquires one or more pieces of element information from one or more other company's job information for each area, and acquires a score using the one or more pieces of element information. For example, the score acquisition unit 134 acquires one or more pieces of element information from one or more other company's job information and the company's own job information for each area, and acquires a score using the one or more pieces of element information.

The score acquisition unit 134 acquires one or more element information from, for example, the salary included in other companies' job information, the working hours included in other companies' job information, the number of other companies in the target area, and salary increase information acquired from the salaries included in other companies' job information in time series, and acquires a score using the element information. Note that the score acquisition unit 134 acquires a higher hiring difficulty level the more the information in the other companies' job information indicates a higher salary. The score acquisition unit 134 acquires a higher hiring difficulty level the more the information in the other companies' job information indicates a shorter working hours. The score acquisition unit 134 acquires a higher hiring difficulty level the more other companies there are in the target area. The score acquisition unit 134 acquires a higher hiring difficulty level the more the salary increase indicated by the salary increase information.

The one or more pieces of element information acquired by the score acquisition unit 134 may be information contained in other companies' job information or the company's own job information, or may be information acquired using information contained in other companies' job information, the company's own job information, or a collection of other companies' job information.

Elemental information acquired by the score acquisition unit 134 includes, for example, salary (e.g., hourly wage, monthly salary), working hours information (e.g., working hours, working hours), number of other companies in the target area, upgrade information in the target area, salary rank, salary increase information acquired from salary information contained in chronological job information from other companies, number of companies in the target area with salary increases, information indicating that the company is a "newly opened" company, information indicating the number of years since opening, information about the age range of employees, information indicating whether or not the company has "reduced working hours," information indicating whether or not direct commutes to and from work are possible, and information indicating whether or not driving is required.

The score acquisition unit 134, for example, performs morphological analysis on the character string information contained in the job information, and uses the acquired morphemes (e.g., "newly opened," "direct commute," "driving," "night shift") to refer to a key word dictionary and acquire element information such as information indicating that the job is "newly opened," information indicating whether "reduced working hours" are available, information indicating whether direct commute is possible, and information indicating whether driving is required.

The score acquisition unit 134 may, for example, acquire working time information (working time zones) included in the job information, and use the working time zones to refer to a keyword dictionary to determine whether they match an ideal value (e.g., "10:00-14:00"), thereby acquiring element information indicating that the working time is an ideal value.

The number of other companies is the number of organizations corresponding to the job information. All other company identifiers contained in one or more other company job information acquired by the other company job information acquisition unit 131 are acquired, and the one or more other company identifiers are processed to be unique, thereby acquiring the number of other company identifiers. The number of other companies may also be the number of other company job information acquired by the other company job information acquisition unit 131. Note that if there is two or more other company job information for one organization among the other company job information acquired by the other company job information acquisition unit 131, the number of other companies may be considered to be "1," or the number of other companies may be considered to be "the number of other company job information for one organization."

Upgrade information is the number of job postings with higher salaries than the base salary. The base salary is, for example, the salary (e.g., hourly wage or monthly salary) included in the company's job posting. The base salary is, for example, a representative value (e.g., average, median) of the salaries (e.g., hourly wage) included in one or more other company's job postings acquired by the other company's job posting acquisition unit 131.

The salary rank is the ranking of the salary in your company's job information among the salaries (e.g., hourly wage or monthly wage) in one or more other company's job information acquired by the other company's job information acquisition unit 131 and the salaries in your company's job information. Here, the higher the salary, the higher the ranking, and the highest ranking is a salary rank of "1."

Salary increase information is information about salary increases or decreases within an organization. Salary increase information includes, for example, the amount of salary increase, the rate of salary increase, the amount of salary increase per unit period, and the rate of salary increase per unit period.

The number of companies with salary increases is the number of organizations where salaries are increasing. The number of companies with salary increases is information obtained using the salary information contained in the time-series job information of each company for one or more organizations.

The score acquisition unit 134 acquires the score by, for example, one of the following three methods.
(1) Method using calculation formula (1-1) When using only other companies' job information

The score acquisition unit 134 acquires one or more other company's job information of organizations included in one or more areas from the other company's job information acquired by the other company's job information acquisition unit 131. Next, the score acquisition unit 134 acquires one or more element information for each area using the acquired one or more other company's job information. Next, the score acquisition unit 134 substitutes the acquired one or more element information into an arithmetic expression, executes the arithmetic expression, and acquires a score. Note that the arithmetic expression for acquiring the score for each area is, for example, an increasing function in which the number of other companies in the target area and the average salary in the target area are element information, such as "score = f (number of other companies in the target area, average salary in the target area)." Note that the other company's job information acquired by the other company's job information acquisition unit 131 is, for example, job information stored in the job information storage unit 112.
(1-2) When using other companies' job information and your own job information

The score acquisition unit 134 acquires one or more pieces of other company's job information of organizations included in one or more areas from the other company's job information acquired by the other company's job information acquisition unit 131. Next, the score acquisition unit 134 acquires one or more pieces of element information for each area using the acquired one or more pieces of other company's job information. Furthermore, the score acquisition unit 134 acquires the company's job information acquired by the company's job information acquisition unit 132. Next, the score acquisition unit 134 acquires one or more pieces of element information using the company's job information. Next, the score acquisition unit 134 substitutes the acquired one or more pieces of element information into an arithmetic expression, executes the arithmetic expression, and acquires a score. Note that the arithmetic expression for acquiring the score for each area is, for example, an increasing function with the number of other companies in the target area, the upgrade information for the target area, and the salary rank as element information, such as "score = w3 × number of other companies in the target area + w4 × upgrade information for the target area + w5 × salary rank (w3, w4, and w5 are weights and positive numbers)."
(1-3) Using a time series of job information from other companies

The score acquisition unit 134 acquires one or more sets of other company's job information for organizations included in one or more areas from the other company's job information acquired by the other company's job information acquisition unit 131. Next, the score acquisition unit 134 acquires one or more element information for each area using the acquired one or more sets of company's job information. Next, the score acquisition unit 134 substitutes the acquired one or more element information into an arithmetic expression, executes the arithmetic expression, and acquires a score. Note that an arithmetic expression for acquiring the score for each area is, for example, "score = f (number of other companies in the target area, average salary increase information for the target area, recent average salary information for the target area)." Furthermore, the arithmetic expression f is an increasing function with the number of other companies in the target area, average salary increase information for the target area, and recent average salary information for the target area (e.g., average hourly wage) as element information, and is, for example, "score = w6 × number of other companies in the target area + w7 × average salary increase information for the target area + w8 × recent average salary information for the target area) (w6, w7, and w8 are weights and positive numbers).
(1-4) When using a time series of job information from other companies and your own job information

The score acquisition unit 134 acquires one or more sets of other company's job information for organizations included in one or more areas from the other company's job information acquired by the other company's job information acquisition unit 131. Next, the score acquisition unit 134 acquires one or more element information for each area using the acquired one or more sets of company's job information and the company's job information. Next, the score acquisition unit 134 substitutes the acquired one or more element information into an arithmetic expression, executes the arithmetic expression, and acquires a score. Note that an arithmetic expression for acquiring the score for each area is, for example, "score = f (number of other companies in the target area, average salary increase information for the target area, salary rank)." Furthermore, the arithmetic expression f is an increasing function with the number of other companies in the target area, average salary increase information for the target area, and salary rank as element information, for example, "score = w9 × number of other companies in the target area + w10 × average salary increase information for the target area + w11 × salary rank (w9, w10, and w11 are weights and positive numbers)." The salary rank is the rank when salaries are sorted in descending order, and the highest salary is assigned a salary rank of "1."
(2) Machine learning method

A learning unit (not shown) acquires two or more pieces of teacher data stored in the storage unit 11. Next, the learning unit performs machine learning learning processing using the two or more pieces of teacher data, acquires a learner, and stores it in the storage unit 11. For example, the learning unit provides the two or more pieces of teacher data to a module that performs machine learning learning processing, executes the module, acquires a learner, and stores it in the storage unit 11. Note that machine learning can be performed using, for example, deep learning, random forest, decision tree, SVR, etc. Also, the module can be, for example, a learning module in the TensorFlow library, a learning module in the R language random forest library, or a TinySVM learning module. Note that the learning unit may be the score acquisition unit 134. In other words, the score acquisition unit 134 may perform machine learning learning processing and acquire the learner.

The element information contained in the training data may be element information obtained using only other companies' job information, or element information obtained using other companies' job information and your own company's job information, or element information obtained using a time-series set of other companies' job information, or element information obtained using a time-series set of other companies' job information and your own company's job information.

Next, the score acquisition unit 134 performs a score prediction process as follows. That is, the score acquisition unit 134 acquires one or more job listings to be used for calculating the score for each area. Note that the job listings here include one or more job listings from other companies. The job listings may also include the company's own job listings. Next, the score acquisition unit 134 acquires one or more element information for each area using one or more job listings for each area. Note that the two or more element information here is the same type of information as the element information contained in the training data used to create the learning device. Next, the score acquisition unit 134 acquires the learning device from the storage unit 11. Next, the score acquisition unit 134 provides the one or more element information and the learning device to a machine learning prediction module, executes the module, and acquires a score. Note that the prediction module is, for example, a prediction module in the TensorFlow library, a prediction module in the Random Forest library of the R language, or a TinySVM prediction module. Then, the score acquisition unit 134 stores the acquired scores in the storage unit 11 or a buffer (not shown) in association with the area identifier of each area.
(3) Method using a correspondence table

The score acquisition unit 134 acquires one or more pieces of job information to be used in calculating the score for each area. Note that the job information here includes one or more pieces of job information from other companies. The job information may also include the company's own job information. Next, the score acquisition unit 134 uses one or more pieces of job information from each area to acquire two or more pieces of element information for each area, and constructs a vector with each piece of element information as an element.

The element information having a vector may be element information obtained using only other companies' job information, or element information obtained using other companies' job information and your own company's job information, or element information obtained using a time-series set of other companies' job information, or element information obtained using a time-series set of other companies' job information and your own company's job information.

Next, the score acquisition unit 134 refers to the correspondence table stored in the storage unit 11 and determines the vector that is most similar to the constructed vector. Next, the score acquisition unit 134 acquires the score that pairs with the determined vector.

The appeal information acquisition unit 135 acquires appeal information that identifies differences between the company's own recruitment information and the recruitment information of one or more other companies, differences that are advantageous to the employer. The employer is the company itself. It is preferable that the appeal information acquisition unit 135 acquires appeal information for each of one or more areas.

The appeal information acquisition unit 135, for example, uses one or more other companies' job information corresponding to each area to acquire representative values (e.g., maximum value, average value, median value) of one or more elements (e.g., salary, working hours, walking time from the nearest station). Next, the appeal information acquisition unit 135, for example, uses the company's own job information to acquire one or more element information (e.g., salary, working hours, distance from the nearest station). Next, the appeal information acquisition unit 135 compares the representative values of other companies with the company's own element information for each element information, determines the element information that satisfies the appeal conditions, and acquires appeal information using that element information. Note that the appeal conditions are, for example, conditions related to the difference between the representative values of other companies and the company's own element information. Examples of appeal conditions are "company's salary (hourly wage) - other companies' average salary (hourly wage) >= 100 yen," "salary is the highest," "average working hours of other companies - company's working hours >= 2 hours," and "average walking time from other companies' nearest station - walking time from the company's nearest station >= 5 minutes." Furthermore, the appeal information includes, for example, an element identifier that identifies the element information. The appeal information includes, for example, element information. For example, the appeal information is "Promote your company's salary" using the element identifier "your company's salary." For example, the appeal information is "The fact that your company's working hours are four hours is attractive" using the element information.

The output unit 14 outputs various types of information. Examples of such information include scores, appeal information, and output information.

Output information is information to be output, and typically includes one or more of the score and appeal information. For example, output information includes map information. For example, output information is information in which the score of each area is clearly displayed on top of the map information. Displaying the score can take any form as long as the score can be grasped. Displaying the score can be, for example, displaying the score (e.g., numerically) or displaying the rank corresponding to the score. Displaying the rank can, for example, be displaying the background color of the area on the map in a color that corresponds to the rank.

In addition, output here typically means transmission to terminal device 3, but it may also be a concept that includes display on a display, projection using a projector, printing on a printer, sound output, storage on a recording medium, and delivery of processing results to other processing devices or other programs.

The score output unit 141 outputs the scores acquired by the score acquisition unit 134. It is preferable that the score output unit 141 output the scores for each area on a map. The score output unit 141 may also output output information.

The score output unit 141, for example, acquires map information and one or more pieces of area information from the storage unit 11, and draws the boundary lines of each area that can be determined from one or more pieces of area information on a map composed of the map information. Next, the score output unit 141, for example, determines the hiring difficulty rank (for example, 1 to 4) of each area using the score for each area. Next, the score output unit 141 composes a map (which may also be called output information) in which the background color of each area is a color corresponding to the rank of each area. Next, the score output unit 141 outputs the output information.

The appeal information output unit 142 outputs the appeal information acquired by the appeal information acquisition unit 135.

The job information management device 2 is a device that manages job information. In response to a request from the information processing device 1, the job information management device 2 transmits one or more pieces of job information to the information processing device 1. The job information management device 2 receives and stores job information from, for example, a terminal device 3. The job information management device 2 is, for example, a Hello Work server or a server equipped with a job site.

The terminal storage unit 31 that constitutes the terminal device 3 stores various types of information. Examples of such information include the company's job information and one or more attribute values.

The terminal reception unit 32 receives various information or instructions. Examples of such information or instructions include company recruitment information and output instructions. The means for inputting such information or instructions may be any means, such as a touch panel, keyboard, mouse, or menu screen.

The device processing unit 33 performs various types of processing. For example, various types of processing include converting instructions and information received by the device receiving unit 32 into instructions and information with a data structure to be transmitted. For example, various types of processing include converting information received by the device receiving unit 35 into information with a data structure to be output.

The terminal transmission unit 34 transmits various instructions and information. Examples of such instructions and information include the company's job information.

The terminal receiving unit 35 receives various types of information. Examples of such information include scores, appeal information, and output information.

The terminal output unit 36 outputs various types of information. Examples of such information include scores, appeal information, and output information.

The storage unit 11, area information storage unit 111, job information storage unit 112, and terminal storage unit 31 are preferably non-volatile recording media, but can also be implemented as volatile recording media.

The process by which information is stored in the storage unit 11, etc. is not important. For example, information may be stored in the storage unit 11, etc. via a recording medium, information transmitted via a communication line, etc. may be stored in the storage unit 11, etc., or information input via an input device may be stored in the storage unit 11, etc.

The reception unit 12, attribute value reception unit 121, terminal reception unit 35, other company job information acquisition unit 131, and company job information acquisition unit 132 are realized, for example, by wireless or wired communication means.

The processing unit 13, other company job information acquisition unit 131, company job information acquisition unit 132, area determination unit 133, score acquisition unit 134, appeal information acquisition unit 135, and device processing unit 33 may be realized, for example, by a processor, memory, etc. The processing procedures of the processing unit 13, etc. are typically realized by software, and the software is recorded on a recording medium such as a ROM. However, they may also be realized by hardware (dedicated circuitry). The processor may be a CPU, MPU, GPU, etc., and the type does not matter.

The output unit 14, score output unit 141, appeal information output unit 142, and terminal transmission unit 34 are realized, for example, by wireless or wired communication means.

The terminal reception unit 32 is realized by device drivers for input means such as touch panels and keyboards, and control software for menu screens.

The terminal output unit 36 may or may not include output devices such as a display or speaker. The terminal output unit 36 may be realized by driver software for an output device, or by a combination of driver software for an output device and an output device, etc.

Next, an example of the operation of information system A will be described. First, an example of the operation of information processing device 1 will be described using the flowchart in Figure 3.

(Step S301) The reception unit 12 determines whether or not an output instruction has been received. If an output instruction has been received, the process proceeds to step S302; if an output instruction has not been received, the process proceeds to step S311. Note that here, the reception unit 12 receives the output instruction from, for example, the terminal device 3.

(Step S302) The area determination unit 133 acquires the company's job information corresponding to the output instruction received in step S301. Note that the company's job information may be included in the output instruction, or may be managed in the storage unit 11 in pair with the user identifier included in the output instruction.

(Step S303) The area determination unit 133 determines one or more areas using the company's job information acquired in step S302. An example of such area determination processing will be described using the flowcharts in Figures 4 and 5. Note that the one or more areas are areas for which a score will be acquired.

(Step S304) The score acquisition unit 134 assigns 1 to counter i.

(Step S305) The score acquisition unit 134 determines whether the i-th area exists among the one or more areas determined in step S303. If the i-th area exists, the process proceeds to step S306; if the i-th area does not exist, the process proceeds to step S308.

(Step S306) The score acquisition unit 134 acquires the score for the i-th area. An example of the score acquisition process will be described using the flowchart in Figure 6.

(Step S307) The score acquisition unit 134 increments the counter i by 1. Return to step S305.

(Step S308) The appeal information acquisition unit 135 acquires appeal information. An example of the appeal information acquisition process is described using the flowchart in Figure 8.

(Step S309) The output unit 14 composes output information. An example of this output information composition process is described using the flowchart in Figure 9.

(Step S310) The output unit 14 outputs the output information constructed in step S309. The process returns to step S301. Note that here, the output unit 14 transmits the output information to, for example, the terminal device 3.

(Step S311) The other company's job information acquisition unit 131 determines whether it is the right time to acquire job information. If it is the right time to acquire job information, the process proceeds to step S312; if it is not the right time to acquire job information, the process proceeds to step S317. The processing unit 13 determines that it is the right time to acquire job information, for example, when a predetermined time has arrived. The processing unit 13 determines that it is the right time to acquire job information, for example, when an instruction to acquire job information is received from the terminal device 3. The processing unit 13 determines that it is the right time to acquire job information, for example, periodically (for example, once a week). The processing unit 13 may determine that it is the right time to acquire job information under any conditions.

(Step S312) The other company's job information acquisition unit 131 assigns 1 to counter i.

(Step S313) The other company's job information acquisition unit 131 determines whether the i-th job information management device 2 from which to acquire other company's job information exists. If the i-th job information management device 2 exists, proceed to step S314; if not, return to step S301.

Here, the other company's job information acquisition unit 131 determines, for example, whether the i-th access information exists in the storage unit 11.

(Step S314) The other company's job information acquisition unit 131 acquires access information for the i-th job information management device 2 from the storage unit 11. Next, the other company's job information acquisition unit 131 uses the access information to acquire the above job information from the i-th job information management device 2. Note that the one or more job information acquired here is other company's job information, but may also include the company's own job information.

(Step S315) The other company's job information acquisition unit 131 stores the one or more pieces of job information acquired in step S314 in association with the identifier of the i-th job information management device 2. The one or more pieces of job information may be stored in the storage unit 11 or in a buffer (not shown).

(Step S316) The other company's job information acquisition unit 131 increments counter i by 1. Return to step S313.

(Step S317) The reception unit 12 determines whether one or more job information items have been received from the job information management device 2. If job information items have been received, the process proceeds to step S318; if no job information items have been received, the process returns to step S301. Note that the job information received here may be, for example, job information items from other companies published in free papers.

(Step S318) The other company's job information acquisition unit 131 stores the one or more job information received in step S317. Return to step S301. Note that the storage destination for the one or more job information may be the storage unit 11 or a buffer (not shown).

In the flowchart of FIG. 3, an area for which a score is to be obtained is selected in step S303, but scores may also be obtained for all areas corresponding to each piece of area information stored in the storage unit 11. In such a case, the area determination unit 133, for example, obtains all area information stored in the storage unit 11.

In the flowchart in Figure 3, processing ends when the power is turned off or an interrupt occurs to end processing.

Next, an example of the first area determination process in step S303 will be explained using the flowchart in Figure 4. The first area determination process is an example of area determination process from the perspective of the recruiter (your company).

(Step S401) The area determination unit 133 obtains the company's address included in the company's job information.

(Step S402) The area determination unit 133 assigns 1 to counter i.

(Step S403) The area determination unit 133 determines whether the i-th area information exists in the storage unit 11. If the i-th area information exists, the process proceeds to step S404; if not, the process returns to the upper level processing.

(Step S404) The area determination unit 133 acquires the representative position contained in the i-th area information. The representative position is information that identifies the position that represents the area, and is, for example, information on the center of gravity of the area (e.g., (latitude, longitude)), information on the position among the vertices of the polygonal area that is farthest from the company's address (e.g., (latitude, longitude)), or information on the position closest to the company's address (e.g., (latitude, longitude)).

(Step S405) The area determination unit 133 obtains the distance between the company's address and the representative location contained in the i-th area information. Note that the technology for obtaining the distance between two points is publicly known, so a detailed explanation will be omitted. Furthermore, the distance here may be a physical distance (e.g., "1.2 km") or a temporal distance (travel time). Furthermore, the technology for obtaining the travel time between two points is also publicly known.

(Step S406) The area determination unit 133 determines whether the distance acquired in step S405 satisfies the distance condition. If the distance condition is satisfied, the process proceeds to step S407; if the distance condition is not satisfied, the process proceeds to step S408. The distance condition is, for example, "distance <= threshold" or "distance < threshold." The distance condition is a condition that the distance must be short.

(Step S407) The area determination unit 133 acquires the area identifier contained in the i-th area information and temporarily stores it in a buffer (not shown). Note that this area identifier is the identifier of the area determined by the area determination unit 133.

(Step S408) The area determination unit 133 increments counter i by 1. Return to step S403.

In the flowchart of Figure 4, the area determination unit 133 may determine the area using another area determination algorithm that determines the commutable area for the company's address.

Next, an example of the second area determination process in step S303 will be described using the flowchart in Figure 5. In the flowchart in Figure 5, descriptions of steps that are the same as those in the flowchart in Figure 5 will be omitted.

(Step S501) The area determination unit 133 acquires the nearest station to the company. Note that the area determination unit 133 acquires, for example, the nearest station included in the company's job information. Also, the area determination unit 133 acquires, for example, the nearest station using the address included in the company's job information. Note that the technology for acquiring the nearest station using an address is publicly known, so a detailed explanation will be omitted.

(Step S502) The area determination unit 133 acquires the name of the railway line of the company's nearest station. Note that the area determination unit 133 acquires, for example, the name of the railway line contained in the company's job information. Also, the area determination unit 133 acquires, for example, the name of the railway line using the company's nearest station. Note that the technology for acquiring the name of the railway line using the nearest station is publicly known technology, so a detailed explanation will be omitted.

(Step S503) The area determination unit 133 uses the line name acquired in step S502 to acquire two or more station names along the line identified by the line name. The area determination unit 133, for example, references the station information in the storage unit 11 and acquires two or more station names that are paired with the line name acquired in step S502. Note that the station information may be stored in an external device (not shown).

(Step S504) The area determination unit 133 assigns 1 to counter j. Note that step S504 is reached by jumping from step S403.

(Step S505) The area determination unit 133 determines whether the jth station name is present among the two or more station names obtained in step S503. If the jth station name is present, the process proceeds to step S506; if not, the process returns to the upper level processing.

(Step S506) The area determination unit 133 obtains the travel time between the jth station and the company's nearest station obtained in step S501. Note that the technology for obtaining such travel time is publicly known.

(Step S507) The area determination unit 133 determines whether the ride time acquired in step S506 is within or less than the threshold. If it is within the threshold, the process proceeds to step S508; if it is not within the threshold, the process proceeds to step S511.

(Step S508) The area determination unit 133 obtains the location of the station with the jth station name and obtains the area identifier of the area that includes that location.

(Step S509) The area determination unit 133 determines whether the area identifier acquired in step S507 has already been registered in step S407. If it has already been registered, the process proceeds to step S511; if it has not already been registered, the process proceeds to step S510.

(Step S510) The area determination unit 133 stores the area identifier obtained in step S507 in a buffer (not shown).

(Step S511) The area determination unit 133 increments counter j by 1. Return to step S505.

Next, an example of the score acquisition process in step S306 will be explained using the flowchart in Figure 6.

(Step S601) The other company's job information acquisition unit 131 acquires one or more other company's job information. An example of this other company's job information acquisition process is described using the flowchart in Figure 7.

(Step S602) The score acquisition unit 134 assigns 1 to counter i.

(Step S603) The score acquisition unit 134 determines whether to acquire the i-th element information using one or more other company's job information acquired in step S601. If the i-th element information is to be acquired, the process proceeds to step S604; if the i-th element information is not to be acquired, the process proceeds to step S606. Note that the element information to be acquired using one or more other company's job information is usually determined in advance.

(Step S604) The score acquisition unit 134 acquires the i-th element information using one or more other company's job information acquired in step S601, and stores it in a buffer (not shown). The i-th element information is, for example, the salary included in the other company's job information, the average salary, the working hours included in the other company's job information, the average working hours, the number of other company's job information, the number of other companies in the target area, information indicating that the company is a "newly opened" company, information indicating the number of years since opening, information about the age range of employees, information indicating whether the company offers "reduced working hours," information indicating whether direct commutes are possible, and information indicating whether driving is required.

(Step S605) The score acquisition unit 134 increments the counter i by 1. Return to step S603.

(Step S606) The score acquisition unit 134 determines whether or not to use the company's own recruitment information when acquiring the score. If the company's own recruitment information is to be used, the process proceeds to step S607; if the company's own recruitment information is not to be used, the process proceeds to step S612. Note that whether or not to use the company's own recruitment information is usually determined in advance.

(Step S607) The score acquisition unit 134 acquires the company's job information.

(Step S608) The score acquisition unit 134 assigns 1 to counter j.

(Step S609) The core acquisition unit 134 uses the company's job information acquired in step S607 to determine whether or not to acquire the jth element information. If the jth element information is to be acquired, the process proceeds to step S610; if the jth element information is not to be acquired, the process proceeds to step S612. Note that the element information to be acquired using the company's job information is usually determined in advance.

(Step S610) The score acquisition unit 134 acquires the jth element information using the company's own job information acquired in step S607 and one or more other companies' job information acquired in step S601, and stores it in a buffer (not shown). Note that here, the score acquisition unit 134 may acquire the jth element information using the company's own job information acquired in step S607 and one or more other companies' job information acquired in step S601, and store it in a buffer (not shown). The jth element information may be, for example, the company's salary, the company's working hours, information indicating that the company is a "newly opened" company, information indicating the number of years since opening, information about the age range of employees, information indicating whether "reduced working hours" are available, information indicating whether direct commutes are possible, information indicating whether driving is required, information on the rank of the target area, and salary rank.

(Step S611) The score acquisition unit 134 increments counter j by 1. Return to step S609.

(Step S612) The score acquisition unit 134 determines whether or not to use the time-series set of other companies' job information when acquiring the score. If the set of other companies' job information is to be used, the process proceeds to step S613; if the set of other companies' job information is not to be used, the process proceeds to step S617. Note that whether or not to use the set of other companies' job information is usually determined in advance.

(Step S613) The score acquisition unit 134 assigns 1 to counter k.

(Step S614) The core acquisition unit 134 uses the time-series set of other companies' job information acquired in step S601 to determine whether to acquire the kth element information. If the kth element information is to be acquired, proceed to step S615; if the kth element information is not to be acquired, proceed to step S617. Note that the element information to be acquired using the time-series set of other companies' job information is usually determined in advance.

(Step S615) The score acquisition unit 134 acquires the kth element information using the time-series job information of other companies acquired in step S601 and stores it in a buffer not shown. Note that here, the score acquisition unit 134 may also acquire the kth element information using the company's own job information acquired in step S607 and the time-series job information of other companies acquired in step S601 and store it in a buffer not shown. Furthermore, the kth element information may be, for example, salary increase information or the number of companies in the target area that have increased salaries.

(Step S616) The score acquisition unit 134 increments the counter k by 1. Return to step S614.

(Step S617) The score acquisition unit 134 acquires one or more pieces of element information stored in a buffer (not shown).

(Step S618) The score acquisition unit 134 acquires a score using one or more pieces of element information acquired in step S617. As described above, specific methods for acquiring a score include, for example, (1) a method using an arithmetic formula, (2) a method using machine learning, or (3) a method using a correspondence table.

(Step S619) The score acquisition unit 134 stores the score acquired in step S618 in association with the area identifier. The process returns to the upper level process. The score is stored in, for example, the storage unit 11 or a buffer (not shown).

Next, an example of the process for obtaining job information from other companies in step S601 will be explained using the flowchart in Figure 7.

(Step S701) The other company's job information acquisition unit 131 acquires the location information contained in the area information for the area of interest.

(Step S702) The other company job information acquisition unit 131 assigns 1 to counter i.

(Step S703) The other company job information acquisition unit 131 determines whether the i-th other area exists. If the i-th other area exists, proceed to step S704; if the i-th other area does not exist, proceed to step S708.

(Step S704) The other company's job information acquisition unit 131 acquires area information for the i-th other area from the storage unit 11.

(Step S705) The other company job information acquisition unit 131 uses the location information acquired in step S701 and the area information acquired in step S704 to determine whether the commuting conditions for determining whether commuting to the company from the i-th other area are met. If the commuting conditions are met, proceed to step S706; if the commuting conditions are not met, proceed to step S707.

(Step S706) The other company's job information acquisition unit 131 acquires one or more other company's job information for the i-th other area from the storage unit 11.

(Step S707) The other company's job information acquisition unit 131 increments counter i by 1. Return to step S703.

(Step S708) The other company's job information acquisition unit 131 acquires one or more other company's job information items for the area of interest from the storage unit 11. The process returns to the upper level processing.

In the flowchart of Figure 7, the algorithm for determining whether the commutable conditions are met may be other algorithms, such as the algorithm for determining whether the area includes stations that are on the same line as stations in the area of interest and that are commutable, as described above.

Next, an example of the appeal information acquisition process in step S308 will be explained using the flowchart in Figure 8.

(Step S801) The appeal information acquisition unit 135 assigns 1 to counter i.

(Step S802) The appeal information acquisition unit 135 determines whether the i-th area exists among the areas determined by the area determination unit 133. If the i-th area exists, the process proceeds to step S803; if the i-th area does not exist, the process returns to the upper level processing.

(Step S803) The appeal information acquisition unit 135 assigns 1 to counter j.

(Step S804) The appeal information acquisition unit 135 determines whether the jth appeal candidate exists. If the jth appeal candidate exists, the process proceeds to step S805; if not, the process proceeds to step S810. Note that whether the jth appeal candidate exists is determined in advance. Appeal candidates are, for example, "salary" and "working hours."

(Step S805) The appeal information acquisition unit 135 acquires a representative value for the i-th area, which is information using element information corresponding to the j-th appeal candidate. The representative value is an average value (e.g., average salary) or a maximum value (e.g., highest salary).

(Step S806) The appeal information acquisition unit 135 acquires element information (e.g., the company's salary) corresponding to the company's jth appeal candidate.

(Step S807) The appeal information acquisition unit 135 uses the representative value acquired in step S805 and the element information acquired in step S806 to determine whether the company's element information satisfies the appeal conditions. If the appeal conditions are met, the process proceeds to step S808; if the appeal conditions are not met, the process proceeds to step S809. Note that the appeal conditions are, for example, "company's salary - average salary >= threshold" or "company's salary > highest salary."

(Step S808) The appeal information acquisition unit 135 acquires the appeal information, associates it with the area identifier of the i-th area, and temporarily stores it in a buffer (not shown). The appeal information may be, for example, "The salary is '$ company salary', which is high." Note that "$ company salary" is a variable, and is assigned the company's salary (e.g., hourly wage).

(Step S809) The appeal information acquisition unit 135 increments counter j by 1. Return to step S804.

(Step S810) The appeal information acquisition unit 135 increments counter i by 1. Return to step S802.

In the flowchart of Figure 8, appeal information may be obtained for all target areas rather than for each area.

Next, an example of the output information configuration process in step S309 will be explained using the flowchart in Figure 9.

(Step S901) The output unit 14 reads map information from the storage unit 11 and places the map information in the output information.

(Step S902) The output unit 14 assigns 1 to counter i.

(Step S903) The output unit 14 determines whether the i-th area for which a score or the like has been calculated exists. If the i-th area exists, the process proceeds to step S904; if not, the process returns to the upper level processing.

(Step S904) The output unit 14 obtains the score paired with the area identifier of the i-th area from a buffer (not shown).

(Step S905) The output unit 14 obtains the level corresponding to the score obtained in step S904 from the level table in the storage unit 11. The level table is a table having two or more records each containing score range, level, and color information. The level may also be considered as the score.

(Step S906) The output unit 14 obtains color information paired with the level obtained in step S905 from the level table.

(Step S907) The output unit 14 acquires area information paired with the area identifier of the i-th area. Next, the output unit 14 changes the color of the area identified by the area information and located above the map information acquired in step S901 to the color of the color information acquired in step S906. Note that the color change is, for example, a change of background color.

(Step S908) The output unit 14 determines whether appeal information exists that pairs with the area identifier of the i-th area. If appeal information exists, proceed to step S909; if not, proceed to step S910.

(Step S909) The output unit 14 places the appeal information in the output information in a manner corresponding to the i-th area.

(Step S910) The output unit 14 increments counter i by 1. Return to step S903.

The following describes a specific example of the operation of information system A in this embodiment.

Currently, the area information storage unit 111 of the information processing device 1 stores the area information management table shown in Figure 10. The area information management table is a table that manages one or more pieces of area information. The area information management table has two or more records, each containing an "ID," "area identifier," "range specification information," and "station information." "Station information" includes "station name," "railway name," and "station location information." "ID" is information that identifies the record. "Range specification information" here is information specified by three or more pieces of location information (latitude, longitude). "Station information" is the status of a station within the corresponding area. "Station location information" is information (latitude, longitude) that indicates the representative location of the station.

The job information storage unit 112 also stores the job information management table shown in FIG. 11. The job information management table is a table for managing one or more job information entries. The job information management table has one or more records each having an "ID," "medium identifier," "organization identifier," "industry," "job," "address," "salary," "working hours," "remarks," and "posting date." The "medium identifier" is information that identifies the medium in which the job information was posted. The medium is, for example, a website managed by the job information management device 2, a paper medium such as a free paper, or a website managed by the job information management device 2. Here, the "organization identifier" is typically the company name. The "industry" is the industry of the organization that is hiring. The "industry" can also be referred to as the industry. The "job" is information that identifies the content of the job being recruited. Here, the "salary" is an hourly wage in yen. The "remarks" contains character string information. The "posting date" is the date the job information was posted, but it can also be the date the job information was acquired.

The job information in the job information management table is information acquired by the other company's job information acquisition unit 131 from the job information management device 2, or information received by the reception unit 12 from the terminal device 3. The job information in the job information management table is typically job information from other companies, but may also include the company's own job information.

In this situation, the following four specific examples will be explained. Specific example 1 is a case where the score is the difficulty of hiring, and the score is obtained from the perspective of "neighboring competition." Specific example 1 is a case where the score is calculated using job information from other companies and your own company's job information. Specific example 2 is a case where the score is the difficulty of hiring, and the score is obtained from the perspective of "the job seeker's residential area." Specific example 2 is a case where the score is calculated using job information from other companies and your own company's job information. Specific example 3 is a case where a time-series set of other companies' job information is used to obtain the degree of recommendation for opening a store, which is a score for each area. Specific example 4 is a case where promotional information is also output.

(Specific Example 1)
In specific example 1, it is assumed that the storage unit 11 stores the following formula for calculating the score: "Score of each area = w1 × number of job openings + w2 × number of upgrades (w1 and w2 are weights)." The number of upgrades is the number of organizations with a higher rank. An upgrade means that the salary (hourly wage) is higher. In this example, the element information is the number of job openings and the number of upgrades.

Then, a user of company A who wants to post a job enters into terminal device 3 the company's job information, including "<organization identifier> company A <salary> 1,000 yen/hour <address> A _3rd city B _5th town... <industry> nursing care <job> nursing care worker."

The terminal device 3 then accepts the job information, constructs an output instruction including the company's job information, and transmits the output instruction to the information processing device 1. Note that because the output instruction includes "<Industry> Nursing Care," the job information of other companies used when calculating the score is limited to job information of other companies that includes the "Nursing Care" industry.

Next, the reception unit 12 of the information processing device 1 receives the output instruction. Next, the area determination unit 133 acquires the company's job information "<organization identifier> Company A <salary> 1,000 yen/hour <address> A _3rd city B _5th town ... <industry> nursing care <job> nursing care worker" corresponding to the received output instruction.

Next, the area determination unit 133 uses the range specification information in the area information management table of FIG. 10 to determine 10 areas that are close enough to the "<Address> A _3rd city B _5th town ..." contained in the acquired company's job information to satisfy a distance condition (for example, "distance (here, travel time) <= 1 hour"). The 10 areas are area (1), area (2), ..., area (10). It is assumed that the area corresponding to the company's job information is area (5).

Next, the score acquisition unit 134 acquires, for each area, job information (job information from other companies) that corresponds to the area identifier that identifies each area, job information that includes the "nursing care" industry, and job information that is currently hiring (for example, posted on or after "2021/10/1").

Next, the score acquisition unit 134 acquires the number of job postings (number of job openings) corresponding to each area identifier, associates it with the area identifier, and temporarily stores this number of job postings in a buffer not shown. The score acquisition unit 134 also acquires the salaries included in the job postings corresponding to each area identifier. Next, the score acquisition unit 134 acquires, for each area, the number of salaries (number of upgrades) that are higher than the salary of "1,000 yen/hour" included in the company's job posting, from the acquired salaries, and associates it with the area identifier and temporarily stores this number of upgrades in a buffer not shown.

Next, the score acquisition unit 134 acquires the number of job openings and the number of upgrades corresponding to the area identifier for each area, and substitutes the number of job openings and the number of upgrades into the calculation formula "Score of each area = w1 × number of job openings + w2 × number of upgrades (w1 and w2 are weights)," executes the calculation formula, calculates the score for each area, and temporarily stores the score in a buffer (not shown) in association with the area identifier.

Next, the score acquisition unit 134 divides the scores into four groups (rank 1, rank 2, rank 3, and rank 4), for example, with 25% of the scores starting from the highest, and temporarily stores the ranks in a buffer (not shown) in association with the area identifier. Note that the rank here (any of "1" to "4") may be considered the score. Also, the way the ranks are divided here is an example and is not restrictive.

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads map information from the storage unit 11. For each area on the map information, the output unit 14 obtains color information corresponding to the rank associated with the area identifier. Next, the output unit 14 paints the range indicated by the range identification information for each area in the color specified by the obtained color information. Furthermore, for each area, the output unit 14 uses the address contained in the job information to place a symbol (here, a "・") that identifies the location at the address, and places an organization identifier (e.g., "B") and salary (e.g., "990/h") around the symbol. Through the above processing, the output unit 14 has been able to compose the output information.

The output unit 14 then transmits the constructed output information to the terminal device 3.

The terminal device 3 then receives and outputs the output information. An example of such output information is shown in Figure 12.

(Specific Example 2)
In specific example 2, the element information for calculating the score is a salary ranking of areas within commuting distance of residents of each area. The salary ranking is a ranking of salaries of the recruiting organization (usually a company), with organizations with higher rankings being ranked higher. The higher a company's salary ranking, the lower its score (lower the difficulty of hiring). When the score is calculated using an arithmetic formula, the formula is "score of each area = f (salary ranking of areas within commuting distance of residents of the area)," where the function f is a decreasing function with the salary ranking (salary ranking) as a parameter.

Then, as in specific example 1, it is assumed that the reception unit 12 of the information processing device 1 receives an output instruction including the company's job information "<organization identifier> Company A <salary> 1,000 yen/hour <address> A _3rd city B _5th town ... <industry> nursing care <job> nursing care worker" from the terminal device 3. Next, the area determination unit 133 acquires the company's job information "<organization identifier> Company A <salary> 1,000 yen/hour <address> A _3rd city B _5th town ... <industry> nursing care <job> nursing care worker" that corresponds to the received output instruction.

Next, the area determination unit 133 uses the area information management table of Fig. 10 to determine one or more areas within a commutable range for the location indicated by "<Address> A _3rd city B _5th town ..." in the company's job information. Here, it is assumed that the area determination unit 133 has determined, for example, by the process described using the flowchart of Fig. 5, an area including other stations along the line nearest to the nearest station to company A that are within commutable range. Here, it is assumed that the area determination unit 133 has determined the shaded area including the colored areas (1) to (9) in Fig. 13.

Next, the score acquisition unit 134 etc. acquires a score for each of the 13 areas determined by the area determination unit 133 as follows. In other words, for each area, the area determination unit 133 determines areas to which residents of that area can commute by performing the process described using the flowchart in Figure 5.

For example, for area (6), the area determination unit 133 determines areas that are commutable to residents of that area, as shown in Figure 14. In other words, the idea here is that job information from other companies that are in commutable areas to people who can commute to the company that is hiring becomes rival information. Then, for area (6), the area determination unit 133 determines 13 areas, including the colored areas shown in Figure 14 and area (6), as commutable areas.

Next, the score acquisition unit 134 refers to the job information management table of FIG. 11 and acquires the salary and organization identifier included in job information that is paired with an address included in any of the 13 areas determined for area (6), that includes the industry of "nursing care," and that is currently hiring (for example, posted on or after "2021/10/1"). Next, the score acquisition unit 134 acquires the salary of "1,000 yen/hour" and the organization identifier "Company A" included in the company's job information. Next, the score acquisition unit 134 sorts the acquired information using salary as a key to acquire the ranking "8" of Company A, and associates this ranking "8" with the area identifier "Area (6)" and temporarily stores it in a buffer (not shown) (see 1401 in FIG. 14).
As with area (6), the score acquisition unit 134 acquires the salary ranking of company A relative to the other 13 areas, associates it with the area identifier, and temporarily stores it in a buffer (not shown).

Next, the score acquisition unit 134 ranks the 13 areas in descending order of company A's salary. The score acquisition unit 134 temporarily stores the rank in this case in a buffer (not shown) in pairs with the area identifier. The score acquisition unit 134 may also use the rank as an area score. The higher the rank, the easier it is to hire.

Next, the score acquisition unit 134 divides the areas into four groups based on the rank of the areas. That is, the score acquisition unit 134 determines Group 1, which includes the bottom 25% of areas (1), (2), and (5) where Company A is ranked lowest; Group 2, which includes the 25% of areas (3), (6), and (7) where Company A is ranked next lowest; Group 3, which includes the 25% of areas (8) and (9) where Company A is ranked next lowest; and Group 4, which includes the top 25% of areas (4) where Company A is ranked highest, and associates each area identifier with a group identifier. Note that in Group 1, Company A's salary is ranked low and recruitment is the most difficult, while in Group 4, Company A's salary is ranked high and recruitment is the easiest. Note that the group identifier here is, for example, Group 1, Group 2, Group 3, or Group 4.

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads map information from the storage unit 11. For each area on the map information, the output unit 14 obtains color information corresponding to the group identifier associated with the area identifier. Next, the output unit 14 paints the range indicated by the range identification information for each area in the color specified by the obtained color information, thereby constructing the output information. Note that group 1 including areas (1), (2), and (5) is 1501 in Figure 15b, group 2 including areas (3), (6), and (7) is 1502, group 3 including areas (8) and (9) is 1503, and group 4 including area (4) is 1504.

The output unit 14 then transmits the constructed output information to the terminal device 3.

The terminal device 3 then receives and outputs the output information. An example of such output information is shown in Figure 15.

(Specific Example 3)
In specific example 3, the element information used to calculate the score is the salary increase rate over a unit period (for example, one year) and the number of companies with a salary increase trend.

Then, assume that the reception unit 12 of the information processing device 1 receives an output instruction containing only the industry "caregiving" from the terminal device 3. Next, the area determination unit 133 obtains the area identifiers of all areas in the area information management table (Figure 10).

Next, the score acquisition unit 134 acquires, for each area, job information from the job information management table (Figure 11) that includes the "nursing care" industry from among the job information from organizations located in each area. Note that the acquired job information also includes past job information.

Next, the score acquisition unit 134 acquires two or more job postings for each area and organization identifier. Next, the score acquisition unit 134 calculates the salary increase rate for a unit period for each area and organization identifier (for example, "(salary corresponding to the most recent posting date - salary corresponding to the oldest posting date) / ((year included in the most recent posting date - year included in the oldest posting date) * salary corresponding to the oldest posting date"). The score acquisition unit 134 also calculates the average salary increase rate for each area (for example, "(sum of salary increase rates) / number of organizations for which a salary increase rate could be calculated"). The score acquisition unit 134 also acquires the number of organizations for each area with a positive salary increase rate (salaries are on an upward trend).

Next, the score acquisition unit 134 temporarily stores the average salary increase rate for each area and the number of organizations where salaries are on an upward trend in a buffer (not shown), in association with the area identifier.

Next, the score acquisition unit 134 determines whether the salary increase rate stored in the buffer is "low," "medium," or "high" for each area identifier. Note that the score acquisition unit 134 may determine whether it is "low," "medium," or "high" based on the salary increase rate value, or may determine whether it is "low," "medium," or "high" based on the ranking of the salary increase rates.

Next, the score acquisition unit 134 determines, for each area identifier, whether the number of organizations where salaries are on an upward trend is "low," "medium," or "high." Note that the score acquisition unit 134 may determine whether the number is "low," "medium," or "high" based on the number of organizations where salaries are on an upward trend, or may determine whether the number is "low," "medium," or "high" based on the ranking of the number of organizations where salaries are on an upward trend.

Next, the score acquisition unit 134 determines an area with a low salary increase rate and a low number of companies with a salary increase trend as a "recommended area (e.g., value "1")," an area with a low salary increase rate and a medium number of companies with a salary increase trend as a "low difficulty area (e.g., value "2")," an area with a medium salary increase rate and a low number of companies with a salary increase trend as a "medium difficulty area (e.g., value "3")," and areas other than the above as a "high difficulty area (e.g., value "4")."

Next, the score acquisition unit 134 associates a score (e.g., a value between "1" and "4") with each area identifier and temporarily stores it in a buffer (not shown). Note that the score indicates, for example, the degree of recommendation for opening a store, and the lower the score, the more recommended the area is for opening a store.

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads map information from the storage unit 11. Next, the output unit 14 determines the area of the acquired map information using the range specification information corresponding to each area identifier, paints the color of the area in a color corresponding to the area's score, and composes the output information. Note that the score here can be considered to be the store's recommendation level.

The output unit 14 then transmits the constructed output information to the terminal device 3.

The terminal device 3 then receives and outputs the output information. An example of such output information is shown in Figure 16. Figure 16 is a diagram that allows users to understand recommended areas for opening new stores.

(Specific Example 4)
Currently, the storage unit 11 of the information processing device 1 stores the appeal information management table shown in FIG. 17. The appeal information management is a table that manages one or more pieces of appeal information. The appeal information management table manages one or more records that have "ID,""appealconditions," and "appeal information.""ID" is information that identifies a record. "ID=1" indicates that "salary" becomes the appeal information when the salary is the highest in the area. "ID=2" indicates that "working hours" becomes the appeal information when the working hours are between 9:00 and 16:00 and there are no other job openings in the area that have working hours between 9:00 and 16:00. "ID=3" indicates that "new business establishment" becomes the appeal information when the business has been open for less than two years and there are no other job openings in the area that have been open for less than two years.

In this situation, the reception unit 12 of the information processing device 1 receives an output instruction from the terminal device 3 including the company's job information "<Organization identifier> Company A <Salary> 1,000 yen/hour <Working hours> 10:00-14:00 <Address> A _3rd city B _5th town... <Industry> Nursing care <Job> Nursing care worker <Notes> Reduced hours OK."

Next, the area determination unit 133 determines one or more areas using any of the algorithms in specific examples 1 to 3 above.

Next, the score acquisition unit 134 acquires a score for each area using any of the algorithms in specific examples 1 to 3 above. The score (difficulty of adoption) here may be, for example, "low difficulty (e.g., 1)," "medium difficulty (e.g., 2)," or "high difficulty (e.g., 3)."

Next, the appeal information acquisition unit 135 references the appeal information management table (Figure 17) for each area and determines whether one or more other company's job listings and the company's job listing corresponding to each area match each appeal condition. For example, let's say that the appeal condition for "ID=2" is met for area (3). This is because the working hours in the company's job listing satisfy the appeal condition "between 9:00 and 16:00," which includes "10:00-14:00," and there is no other company's job listing containing information on working hours that meets the "between 9:00 and 16:00" range among the job listings corresponding to area (3). Next, the appeal information acquisition unit 135 acquires the appeal information "salary" that pairs with the appeal condition. The appeal information acquisition unit 135 then associates the appeal information "salary" with the area identifier "area (3)" and stores it in a buffer (not shown).

The appeal information acquisition unit 135 also performs similar processing for areas other than area (3).

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads map information from the storage unit 11. For each area on the map information, the output unit 14 obtains color information corresponding to the score associated with the area identifier. Next, the output unit 14 paints the range indicated by the range identification information for each area in the color specified by the obtained color information. In addition, the output unit 14 adds, for each area, appeal information associated with the area. Through the above processing, the output unit 14 has been able to compose the output information.

The output unit 14 then transmits the constructed output information to the terminal device 3.

Next, the terminal device 3 receives and outputs the output information. An example of such output information is shown in Figure 18. In Figure 18, when a user uses an input means such as a mouse to point to 1801 on the screen of the terminal device 3, appeal information for the area corresponding to that point is output as shown in 1802 in Figure 18.

As described above, according to this embodiment, a recruitment score can be obtained using job information from other companies. The score may be, for example, the difficulty of recruiting or the degree of recommendation for opening a store.

Furthermore, according to this embodiment, a recruitment score can be obtained using job information from other companies and your own company's job information.

Furthermore, according to this embodiment, you can propose your company's selling points using job information from other companies and your own job information.

Furthermore, according to this embodiment, recruitment information from other companies can be used to clearly present the recruitment scores for each area using maps, etc.

Furthermore, this embodiment can suggest appropriate areas for obtaining recruitment scores.

The processing in this embodiment may be implemented using software. This software may be distributed by software download, etc. The software may also be recorded on a recording medium such as a CD-ROM and distributed. This also applies to the other embodiments in this specification. The software that implements the information processing device 1 in this embodiment is the following program. In other words, this program causes a computer to function as a other company's job information acquisition unit that acquires other company's job information related to job openings at one or more other companies, a score acquisition unit that acquires a hiring score using the one or more other company's job information acquired by the other company's job information acquisition unit, and a score output unit that outputs the score.

Furthermore, Figure 19 shows the external appearance of a computer that executes the programs described herein to realize the information processing devices and the like of the various embodiments described above. The above-described embodiments can be realized by computer hardware and computer programs executed on the computer hardware. Figure 19 is an overview diagram of this computer system 300, and Figure 20 is a block diagram of system 300.

In Figure 19, computer system 300 includes computer 301, which includes a CD-ROM drive, keyboard 302, mouse 303, and monitor 304.

In FIG. 20, computer 301 includes, in addition to CD-ROM drive 3012, MPU 3013, bus 3014 connected to CD-ROM drive 3012 etc., ROM 3015 for storing programs such as boot-up programs, RAM 3016 connected to MPU 3013 for temporarily storing application program instructions and providing temporary storage space, and hard disk 3017 for storing application programs, system programs, and data. Although not shown here, computer 301 may also include a network card that provides connection to a LAN.

A program that causes the computer system 300 to execute the functions of the information processing device 1 and the like of the above-described embodiment may be stored on CD-ROM 3101, inserted into CD-ROM drive 3012, and then transferred to hard disk 3017. Alternatively, the program may be sent to computer 301 via a network (not shown) and stored on hard disk 3017. The program is loaded into RAM 3016 when executed. The program may also be loaded directly from CD-ROM 3101 or the network.

The program does not necessarily have to include an operating system (OS) or third-party programs that cause the computer 301 to execute the functions of the information processing device 1 of the above-described embodiment. The program need only include instructions that call appropriate functions (modules) in a controlled manner and achieve the desired results. How the computer system 300 operates is well known, so a detailed description will be omitted.

Note that in the above program, the steps of transmitting information and receiving information do not include processing performed by hardware, such as processing performed by a modem or interface card in the transmission step (processing that can only be performed by hardware).

Furthermore, the computer that executes the above program may be a single computer or multiple computers. In other words, it may perform centralized processing or distributed processing.

It goes without saying that in each of the above embodiments, two or more communication means present in one device may be physically realized using a single medium.

Furthermore, in each of the above embodiments, each process may be realized by centralized processing on a single device, or may be realized by distributed processing on multiple devices.

The present invention is not limited to the above-described embodiments, and various modifications are possible, and it goes without saying that these modifications are also included within the scope of the present invention.

As described above, the information processing device 1 of the present invention has the effect of being able to obtain a recruitment score using job information from other companies, and is useful as a server or the like that obtains a score using job information.

REFERENCE SIGNS LIST 1 Information processing device 2 Recruitment information management device 3 Terminal device 11 Storage unit 12 Reception unit 13 Processing unit 14 Output unit 31 Terminal storage unit 32 Terminal reception unit 33 Terminal processing unit 34 Terminal transmission unit 35 Terminal reception unit 36 Terminal output unit 111 Area information storage unit 112 Recruitment information storage unit 121 Attribute value reception unit 131 Other company recruitment information acquisition unit 132 Company recruitment information acquisition unit 133 Area determination unit 134 Score acquisition unit 135 Appeal information acquisition unit 141 Score output unit 142 Appeal information output unit

Claims (8)

a company employment information acquisition unit that acquires other company employment information relating to job offers from two or more other companies;
a score acquisition unit that acquires two or more pieces of element information from the two or more pieces of other company's job information acquired by the other company's job information acquisition unit, and acquires a score that is a recruitment difficulty level that indicates the difficulty or ease of recruitment for the company using the two or more pieces of element information ;
a score output unit that outputs the score ,
The other company job information acquisition unit
Acquire two or more pieces of other company's job information from one or two or more job information management devices that manage job information, or receive two or more pieces of other company's job information from a terminal device, or acquire two or more pieces of other company's job information from a job information storage unit in which two or more pieces of job information are stored,
The two or more pieces of element information are
The information includes one or more of salary information, working hours information, the number of other companies, or salary increase information obtained from salary information contained in time-series job information of other companies,
The score acquisition unit
Substituting the acquired two or more pieces of element information into an arithmetic expression for acquiring the score, and acquiring the score.
Alternatively, a learning device is acquired by performing machine learning learning using two or more pieces of teacher data each having two or more pieces of element information and a score, and the acquired two or more pieces of element information are used to perform machine learning prediction processing, thereby acquiring the score.
Alternatively, a vector is constructed using the two or more pieces of element information acquired as elements, and a vector that is most similar to the vector is determined from a correspondence table having two or more pieces of correspondence information that is information indicating the correspondence between a vector using one or more pieces of element information as elements and a score, and the score that is paired with the determined vector is obtained.
The score acquisition unit
The information processing device obtains the score , which indicates the difficulty of recruitment, such that the higher the salary indicated by the salary information of other companies, the shorter the working hours indicated by the information of other companies, the greater the number of other companies, or the greater the salary increase indicated by the salary increase information of other companies . The company further includes a company recruitment information acquisition unit that acquires company recruitment information related to recruitment in the company;
The score acquisition unit
The information processing device of claim 1, wherein the company's job information acquisition unit acquires one or more element information from the company's job information acquired, and acquires the score using the two or more element information acquired from the other company's job information and the one or more element information acquired from the company's job information . an appeal information acquisition unit that acquires appeal information that identifies differences between the company's job information and the two or more other companies' job information, the differences being advantageous to employers;
an appeal information output unit that outputs the appeal information ;
The appeal information acquisition unit
3. An information processing device as described in claim 2, which obtains a representative value of each of two or more element information of the two or more other companies, compares the representative value with the company's own element information for each of the two or more element information, determines element information that satisfies an appeal condition that is a condition regarding the difference between the other company's representative value and the company's own element information, and obtains the appeal information using the element information . The other company job information acquisition unit
For each of one or more areas, obtain job information of one or more other companies that corresponds to each area;
The score acquisition unit
obtaining a score for each of the one or more areas;
The score output unit
The information processing device according to claim 1 , wherein the score for each of the areas is output on a map. The job information of other companies is associated with one or more attribute values including an area identifier that identifies an area,
an attribute value receiving unit that receives one or more attribute values of the company's train line, the company's nearest station, or the company's address ;
an area determination unit that determines one or more areas from which other company's job information is to be obtained, using the one or more attribute values received by the attribute value reception unit;
The area determination unit
Determine areas that meet the commuting conditions for the area in which the company is located;
Alternatively, an area including the nearest station accepted by the attribute value accepting unit is determined.
Alternatively, an area including stations on the same line as the nearest station accepted by the attribute value accepting unit is determined.
Alternatively, the area is determined using the railroad line information received by the attribute value receiving unit.
Alternatively, the attribute value receiving unit determines an area whose distance from the address received is within a threshold value,
The other company job information acquisition unit
The information processing device according to claim 4 , wherein the area determining unit acquires the two or more other companies' job information corresponding to the area determined by the area determining unit. The other company job information acquisition unit
Obtain job information from two or more other companies in a time series from at least one other company,
The score acquisition unit
The information processing device according to claim 1 , wherein the score is obtained using the time-series job information of two or more other companies. An information processing method for causing a computer to execute all of the processes performed by the information processing device according to claim 1 . Computer,
A program for causing the information processing device according to any one of claims 1 to 6 to function as the information processing device .