JP7701055B2 - Information output device, information output method, and program - Google Patents

Description

The present invention relates to an information output device that processes job information and outputs the results of the processing.

Previously, there was a recruitment support server that could prove that a job seeker had the skills, knowledge, and qualifications based on documents related to the job seeker in the recruitment matching process for various tasks that require a high level of expertise (see Patent Document 1).

JP 2021-056883 A

However, conventional technology has not been able to provide appropriate information using job information sorted by publication medium. In particular, conventional technology has not been able to provide appropriate information using chronological job information sorted by publication medium.

Furthermore, 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 scores related to recruitment include the difficulty of recruitment, which will be described later, and the recommendation level for opening a store, which will be described later.

The information output device of the first invention is an information output device including: an acquisition unit that acquires job information from a job information storage unit in which two or more pieces of job information in a time series having one or more attribute values related to job openings are stored in association with one or more medium identifiers; a configuration unit that uses the two or more pieces of job information acquired by the acquisition unit to configure change information, which is information that can distinguish the publication medium identified by the medium identifier and is information that can grasp changes in the job information over time; and a change output unit that outputs the change information configured by the configuration unit.

This configuration makes it possible to provide information on changes in job information over time by publication medium.

The information output device of the second invention is an information output device according to the first invention, in which the job information acquired by the acquisition unit corresponds to one of two or more medium identifiers, and the change output unit outputs change information that allows the temporal change of the job information in two or more publication media to be simultaneously grasped.

This configuration makes it possible to provide information on changes in job information over time for two or more publication media.

The information output device of the third invention is an information output device according to the first or second invention, in which the configuration unit uses two or more pieces of job information in a time series to configure change information that is a graph with a time axis, which is a graph that allows the user to grasp the change over time in the job information.

This configuration makes it possible to provide a graph that shows changes over time in job information by publication medium.

The information output device of the fourth invention is an information output device according to the third invention, in which one or more attribute values have salary information, and the component is a graph that can grasp the temporal change in the salary information, and which configures the change information as a graph having salary information and a time axis.

This configuration makes it possible to provide a graph that shows changes in salaries over time in job postings by publication medium.

The information output device of the fifth invention is an information output device according to any one of the first to fourth inventions, further comprising a first recommendation acquisition unit that acquires first recommendation information for the recruiting party using one or more job information items corresponding to each of two or more medium identifiers, and a first recommendation output unit that outputs the first recommendation information.

This configuration allows appropriate information to be provided to employers using job information for each publication medium.

The information output device of the sixth invention is an information output device according to the fifth invention, in which the first recommendation acquisition unit includes a first score acquisition means for acquiring a first score for each publication medium using one or more attribute values of one or more job listings for each of two or more medium identifiers, and a first recommendation acquisition means for acquiring first recommendation information having a first medium identifier that identifies the publication medium in which the listing should be posted, using the first score acquired by the first score acquisition means.

This configuration allows the job information by publication medium to be used to suggest to the employer which medium they should use to publish their job.

The information output device of the seventh invention is an information output device according to the fifth invention, in which the job information has an organization identifier that identifies the organization that is hiring, the first recommendation acquisition unit is two or more pieces of job information that correspond to different medium identifiers, and the first recommendation acquisition unit is an information output device equipped with a first recommendation acquisition means that acquires recommendation information including warning information when a specific attribute value paired with one organization identifier satisfies a warning condition.

With this configuration, if an organization offering jobs posts different job information in two or more publication media, a warning can be issued to the organization offering jobs.

The information output device of the eighth invention is an information output device according to any one of the first to seventh inventions, further comprising a second recommendation acquisition unit that acquires second recommendation information for a job seeker using one or more job information items corresponding to each of two or more media identifiers, and a second recommendation output unit that outputs the second recommendation information.

This configuration allows job seekers to be provided with appropriate information using job information for each publication medium.

The information output device of the ninth invention is an information output device according to the eighth invention, in which the second recommendation acquisition unit includes a second score acquisition means for acquiring a second score for each publication medium using one or more attribute values of one or more job listings for each of two or more medium identifiers, and a second recommendation acquisition means for acquiring second recommendation information having a second medium identifier that identifies the publication medium to which the job listing should be applied, using the second score acquired by the second score acquisition means.

With this configuration, job information by publication medium can be used to suggest to job seekers which medium they should apply for.

The information output device of the tenth invention is an information output device according to the eighth invention, in which the second recommendation acquisition unit is configured to acquire a second medium identifier corresponding to an attribute value advantageous to a job seeker when the two or more job information items correspond to different medium identifiers and the specific attribute value paired with one organization identifier is different, and to acquire second recommendation information including the second medium identifier.

With this configuration, job information by publication medium can be used to suggest to job seekers which medium they should apply for.

The information processing device of the present invention is an information processing device that includes 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 score related to recruitment 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.

With this configuration, you can obtain a hiring score using job information from other companies.

The information processing device of the present invention is an information processing device that 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 recruitment information.

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

The information processing device of the present invention is an information processing device that further includes an appeal information acquisition unit that acquires appeal information that identifies differences between the company'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 present invention is an information processing device in which, compared to the above invention, the other company job information acquisition unit acquires, for each of one or more areas, other company job information relating to one or more other company job openings corresponding to each area, 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 makes it possible to clearly display the recruitment scores for each area using job information from other companies.

In addition, in the information processing device of the present invention, in comparison with the above invention, other company job information corresponds to one or more attribute values including an area identifier that specifies an area, and the information processing device 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 other company job information is to be obtained, and the other company job information acquisition unit acquires one or more pieces of other company job information corresponding 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.

The information processing device of the present invention is an information processing device in which, compared to the above invention, the other company job information acquisition unit acquires two or more other company job information in a time series of at least one other company, and the score acquisition unit acquires a score using the two or more other company job information in a time series.

With this configuration, it is possible to obtain a recruitment score using time-series job information from other companies.

The information processing device of the present invention is an information processing device in which, compared to the above invention, other company's job information includes salary information or working hour information, and the score acquisition unit acquires one or more element information from the salary information contained in other company's job information, the working hour information contained in other company's job information, the number of other companies in the target area, and salary increase information acquired from the salary information contained in other company's job information in a time series, and acquires a score using the element information.

With this configuration, it is possible to obtain an appropriate recruitment score using appropriate element information obtained using job information from other companies.

The information output device of the present invention can provide appropriate information using job information for each publication medium.

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

Conceptual diagram of information system A in embodiment 1. Block diagram of information system A A flowchart for explaining an example of the operation of the broadcast processing device 1. 11 is a flowchart illustrating an example of the first area determination process. 11 is a flowchart illustrating an example of the second area determination process. A flowchart for explaining an example of a process for acquiring the score A 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. 11 is a 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 A diagram showing an example of the output information A diagram explaining the algorithm for determining the area A diagram explaining the algorithm for determining the area A diagram showing an example of the output information A diagram showing an example of the output information A diagram showing the appeal information management table A figure showing an example of the output of the appeal information, etc. Conceptual diagram of information system B in embodiment 2 Block diagram of information system B A flowchart for explaining an example of the operation of the information output device 4. A flowchart for explaining an example of the change information configuration process. FIG. 2 shows the change information management table. An example of the graph Block diagram of information system C in embodiment 3. A flowchart for explaining an example of the operation of the information output device 5. A flowchart illustrating an example of the publication medium determination process. A flowchart illustrating an example of the application medium determination process FIG. 13 shows an example of the publication media information output. Overview of the computer system according to the above embodiment. Block diagram of the computer system

Embodiments of an information processing device, an information output device, etc. 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 repeated explanations may be omitted.

(Embodiment 1)
In this embodiment, an information processing device is described which obtains and outputs a recruitment score (e.g., recruitment difficulty) using one or more other companies' recruitment information. The element information used when obtaining the score is, for example, salary, number of other companies in the area, length of working hours, rate of salary increase, etc. Other companies' recruitment information is information about recruitment at other companies. Other companies' recruitment information is, for example, recruitment information entered with reference to recruitment information posted on a website or in a free paper. Two or more other companies' recruitment information may include the company's own recruitment information posted on a website, in 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 that exist in one or more areas to obtain and output a score regarding recruitment in each of one or more areas.

In this embodiment, an information processing device is described that also uses the company's own recruitment information to obtain and output a score. The company's own recruitment information is information about recruitment within the company. The company's own recruitment information does not need to have the same data structure as the other company's recruitment information. The company's own recruitment information may be a portion of the other company's recruitment information (for example, only salary, or only salary and working hours).

In this embodiment, we will also describe an information processing device that uses other companies' job information and our own job information to obtain and output our company's selling points.

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

In addition, in this embodiment, we will explain 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 obtains and outputs a score (e.g., a store recommendation rating) using two or more time-series job information from other companies.

In each embodiment of this specification, information A corresponds to information B, meaning that information B can be obtained from information A, or information A can be obtained from information B, and the method of the correspondence 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 an 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 other companies' job information 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 usually a device that manages publicly available job information. The job information management device 2 may be considered to be 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 a cloud server or an ASP server. 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 is, for example, a person in charge or a manager of a company that is about to hire. The user is, for example, a person who wants to obtain a score or an appeal point, which will be described later. The terminal device 3 is, for example, a so-called personal computer, a tablet terminal, a 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 with each other 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 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.

Various types of information are stored in the storage unit 11 constituting the information processing device 1. The various types of information include, for example, one or more area information described below, one or more job information described below, one or more attribute values described below, two or more teacher data, a learning device, a correspondence table, map information, one or more station information, a dictionary of important words, a level table described below, appeal conditions described below, and appeal information described below. The one or more job information includes other companies' job information described below. The one or more job information may also include the company's own job information described below.

The teacher data has one or more element information and a score. The teacher data is, for example, information that is the basis for constituting a learning device for calculating a score. The teacher data is, for example, information that is the basis for constituting a correspondence table described later. The element information is information that is the basis for obtaining a score. The element information is information that can be obtained using other companies' job information, or the company's own job information, or other companies' job information and the company's own job information. The other companies' job information may be chronological other companies' job information. The chronological other companies' job information is job information of the same organization, and two or more other companies' job information with different posting dates. The chronological other companies' job information is appropriately referred to as a set of other companies' job information. The element information is, for example, salary information contained in other companies' job information, working hours information contained in other companies' job information, 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 other companies' job information.

The learning device is information for obtaining a score through machine learning prediction processing. The learning device is information obtained as a result of machine learning learning processing using two or more pieces of teacher data. Note that the algorithms for the machine learning learning processing and the machine learning prediction processing are not important. For example, deep learning, random forest, decision tree, SVR, etc. can be used for machine learning.

The correspondence table has two or more pieces of correspondence information. The correspondence information is information that indicates the correspondence between a vector having one or more pieces of element information as elements and a score. The correspondence information has, for example, a vector having one or more pieces of element information as elements 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.

The important word dictionary has a set of important words for obtaining element information. The important word dictionary has, for example, two or more records of important words and ideal values. Pairs of (important word, ideal value) are, for example, (new opening, True), (year opened, 0), (working hours, 10:00-14:00), (go directly to work, Treu), (driving a car, False), and (night shift, False). Note that the ideal value "True" means that the corresponding important word is included in the job information. The ideal value "False" means that the corresponding important word is not included in the job information.

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

The job information storage unit 112 includes one or more job information items. The job information in the job information storage unit 112 is, for example, job information acquired from the job information management device 2 and 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 about job offers. Job information includes, for example, salary information, working hours information, nearest station information, address information, area identifier, 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. For example, working hour information is information indicating the length of working hours (e.g., "7.5 hours", "8 hours"), information indicating the working time period (e.g., "9:00-18:00", "10:00-14:00"), or information indicating that it is a "night shift".

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

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 character string. Examples of character string information include information indicating that the business is a "newly opened business," information indicating the number of years since the business opened, information about the age group of employees, information indicating whether "shortened working hours" are possible, information indicating whether direct travel is possible, and information indicating whether driving a car is required.

The reception unit 12 receives various instructions and information. The various instructions and information are, for example, an output instruction, an attribute value described below, and one or more pieces of access information. The output instruction is an instruction to output a score, or appeal information, or a score and appeal information. The output instruction includes, for example, the company's job information.

The access information is information for acquiring 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 on an API for acquiring job information from the job information management device 2, or an execution module for acquiring job information from the job information management device 2.

Here, acceptance usually refers to the receipt from the terminal device 3 of information, instructions, etc. transmitted via a wired or wireless communication line, but the concept may also include the acceptance of information input from an input device such as a keyboard, mouse, or touch panel, or the acceptance of information read from a recording medium such as an optical disk, magnetic disk, or semiconductor memory.

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, called the company) to which the user who outputs the score belongs. The attribute value is, for example, the company's industry, the company's train line, the company's nearest station, the company's address, etc. Each of the one or more attribute values received by the attribute value receiving unit 121 can be considered to be the company's job information.

The processing unit 13 performs various types of processing. The various types of processing are, for example, processing performed by the other company 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 usually has a other company identifier that is an identifier of the other organization. The organization is usually a company, but it can also be an association, a sole proprietorship, etc., and the type is not important.

It is preferable that the job information of other companies corresponds to one or more attribute values including an area identifier. The attribute values are, 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 job information of other companies was published. The media identifier is, for example, an identifier of a job site or an identifier of a 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 a job site, free paper, etc.

The other company's job information acquisition unit 131 acquires, for example, for each of one or more areas, other company's job information relating to job openings at one or more other companies corresponding to each area. The other company's job information acquired for each area is usually associated with an area identifier. Note that other company's job information relating to job openings at one or more other companies corresponding to an area is, for example, other company's job information from one or more other companies that exist in the area. One or more other company's job information corresponding to an area is, for example, other company's job information from other companies that exist in one or more areas that satisfy the commuting conditions for the area.

The other company job information acquisition unit 131 acquires, for example, one or more pieces of other company 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 job information acquisition unit 131 acquires two or more other company job information pieces of time series for at least one other company.

The other company's job information acquisition unit 131 acquires, for example, 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 acquires, for example, by crawling, 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 acquires, for example, access information corresponding to the other company's job information acquisition unit 131 from the storage unit 11, and acquires one or more pieces of other company's job information from the job information management device 2 using the access information. 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 a publicly known technology, so a detailed explanation is omitted.

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

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

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 are, for example, the company's own job information.

The area determination unit 133 determines, for example, the area in which the company's company is included and the areas from which the company can be commuted to the area. A commutable area is an area that satisfies the commutable conditions. An area from which a certain point or area (for example, the company) can be commuted is, for example, an area that can be traveled to from a certain point or area in a time within a threshold, an area that is within a distance of a certain point or area within a threshold, an area along the same train line from the nearest station to a certain point or area, or an area along the same train line from the nearest station to a certain point or area, and includes a station where the ride time from the nearest station is within a threshold. Any algorithm can be used to determine an area from which a certain point or area can be commuted.

The area determination unit 133, for example, determines one or more areas using the nearest station to the company that is accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, refers to one or more pieces of area information in the storage unit 11 and determines an area that includes the nearest station to the company that is accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, refers to one or more pieces of area information in the storage unit 11 and determines two or more areas that include an area that includes the nearest station to the company that is 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, refers to one or more pieces of area information in the storage unit 11 and determines one or more areas that are within a threshold distance from the position of the nearest station to the company that is accepted by the attribute value acceptance unit 121.

The area determination unit 133, for example, determines one or more areas using the company's line accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, refers to 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 line as the company's line accepted by the attribute value acceptance unit 121. The area determination unit 133, for example, refers to 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 line as the company's line accepted by the attribute value acceptance unit 121 and that are within a threshold ride time from the company's nearest station.

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

The area determination unit 133 may, for example, determine one or more areas that are commutable to the area in which the company is included, 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 score related to recruitment 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 companies. The set of job information from other companies has job information from two or more 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 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 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 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 in other company's job information, the working hours in other company's job information, the number of other companies in the target area, and salary increase information acquired from the salary in other company's 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 lower the information in the other company's job information indicates the salary. The score acquisition unit 134 acquires a higher hiring difficulty level the shorter the information in the other company's job information indicates the working hours. The score acquisition unit 134 acquires a higher hiring difficulty level the greater the number of other companies in the target area. The score acquisition unit 134 acquires a higher hiring difficulty level the greater 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.

The element information acquired by the score acquisition unit 134 includes, for example, salary (e.g., hourly wage, monthly salary), working hour information (e.g., working hours, working time zone), the 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 other companies' chronological job information, the number of companies in the target area with salary increases, information indicating that the company is a "new opening," information indicating the number of years since opening, information about the age group 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 a car is required.

In addition, the score acquisition unit 134 performs, for example, morphological analysis of character string information included in the job information, and uses the acquired morphemes (e.g., "newly opened," "direct commute," "driving a car," and "night shift") to refer to a dictionary of important words to acquire element information such as information indicating that the job is "newly opened," information indicating whether or not "shortened hours" are available, information indicating whether or not direct commute is possible, information indicating whether or not driving a car is required, etc.

The score acquisition unit 134 may, for example, acquire working time information (working time period) included in the job information, and use the working time period to refer to a key word dictionary to determine whether it matches an ideal value (e.g., "10:00-14:00"), and acquire 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 companies, which is the number of other company identifiers obtained as a result. 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."

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

The salary rank is the ranking of the salary in the 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 the company's job information. Here, the ranking is higher the higher the salary, and the highest ranking is the salary rank "1".

Salary increase information is information about an increase or decrease in salary within an organization. Salary increase information is, for example, the amount of salary increase, the rate of salary increase, the amount of salary increase in a unit period, and the rate of salary increase in a 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 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, for example, by one of the following three methods.
(1) Method using a formula (1-1) When using only job information from other companies

The score acquisition unit 134 acquires one or more pieces of other company recruitment information of organizations included in each of one or more areas from among the other company recruitment information acquired by the other company recruitment 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 recruitment 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 and the average salary in the target area as element information, for example, "score = f (number of other companies in the target area, average salary in the target area)". Note that the other company recruitment information acquired by the other company recruitment information acquisition unit 131 is, for example, recruitment 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 recruitment information of organizations included in one or more areas from among the other company recruitment information acquired by the other company recruitment 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 recruitment information. In addition, the score acquisition unit 134 acquires the company's own recruitment information acquired by the company's own recruitment information acquisition unit 132. Next, the score acquisition unit 134 acquires one or more pieces of element information using the company's own recruitment 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 in the target area, and the salary rank as element information, and is, for example, "score = w3 x number of other companies in the target area + w4 x upgrade information in the target area + w5 x salary rank (w3, w4, w5 are weights and are positive numbers)."
(1-3) When using a time series of job information from other companies

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

The score acquisition unit 134 acquires one or more sets of other company job information of organizations included in one or more areas from among the other company job information acquired by the other company 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 job information and the company's own 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 of each area is, for example, "score = f (number of other companies in the target area, average salary increase information in the target area, salary rank)". In addition, the arithmetic expression f is an increasing function with the number of other companies in the target area, average salary increase information in the target area, and salary rank as element information, and is, for example, "score = w9 x number of other companies in the target area + w10 x average salary increase information in the target area + w11 x salary rank (w9, w10, 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

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

The element information contained in the teacher data may be element information acquired using only other companies' job information, or may be element information acquired using other companies' job information and the company's own job information, or may be element information acquired using a time-series set of other companies' job information, or may be element information acquired using a time-series set of other companies' job information and the company's own 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 information used to calculate the score for each area. The job information here includes one or more other company job information. The job information may include the company's own job information. Next, the score acquisition unit 134 acquires one or more element information for each area using one or more job information for each area. The two or more element information here is the same type of information as the element information held by the teacher data used when creating 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 one or more element information and the learning device to a machine learning prediction module, executes the module, and acquires a score. 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 acquiring unit 134 accumulates 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 the 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 acquires two or more pieces of element information for each area using one or more pieces of job information from 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 acquired using only other companies' job information, or may be element information acquired using other companies' job information and the company's own job information, or may be element information acquired using a time-series set of other companies' job information, or may be element information acquired using a time-series set of other companies' job information and the company's own job information.

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

The appeal information acquisition unit 135 acquires appeal information that is a difference between the company's own recruitment information and one or more other companies' recruitment information, and that identifies 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 company's 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 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 value of the other company with the company's element information for each element information, determines the element information that satisfies the appeal condition, and acquires the appeal information using the element information. Note that the appeal condition is, for example, a condition regarding the difference between the representative value of the other company and the company's element information. The appeal condition is, for example, "the company's salary (hourly wage) - the average salary of the other company (hourly wage) >= 100 yen", "the salary is the maximum value", "the average working hours of the other company - the working hours of the company >= 2 hours", "the average walking time from the nearest station of the other company - the walking time from the nearest station of the company >= 5 minutes". The appeal information also includes, for example, an element identifier that identifies the element information. The appeal information includes, for example, element information. The appeal information is, for example, "Appeal your company's salary" using the element identifier "your company's salary." The appeal information is, for example, "It's attractive that your company's working hours are four hours" using the element information.

The output unit 14 outputs various information, such as the score, appeal information, and output information.

Output information is information to be output, and typically includes one or more of score and appeal information. Output information includes, for example, map information. Output information is, for example, information in which the score of each area is clearly displayed on top of the map information. The manner in which the score is clearly displayed does not matter as long as the score can be grasped. Clear display of the score is, for example, clear display of the score (for example, a numerical value) or clear display of the rank corresponding to the score. Clear display of the rank is, for example, displaying the background color of the area in a color that corresponds to the rank on the map.

In addition, here, output usually means transmission to the 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 the processing results to other processing devices or other programs, etc.

The score output unit 141 outputs the score acquired by the score acquisition unit 134. It is preferable that the score output unit 141 outputs the score 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 configured from the map information. Next, the score output unit 141, for example, determines the rank (e.g., 1 to 4) of the difficulty of hiring for each area using the score for each area. Next, the score output unit 141 configures a map (which may 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 accumulates job information from, for example, a terminal device 3. The job information management device 2 is, for example, a server of a Hello Work office or a server equipped with a job site.

The terminal storage unit 31 constituting the terminal device 3 stores various types of information. The various types of information include, for example, the company's job information and one or more attribute values.

The terminal reception unit 32 receives various information or instructions. The various information or instructions are, for example, the company's job information and output instructions. The means for inputting the various information or instructions can be anything, 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 are processing to convert instructions and information accepted by the device accepting unit 32 into instructions and information with a data structure to be transmitted. For example, various types of processing are processing to convert 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. The various instructions and information are, for example, the company's job information.

The terminal receiving unit 35 receives various types of information, such as score, appeal information, and output information.

The terminal output unit 36 outputs various information, such as the score, appeal information, and output information.

The storage unit 11, the area information storage unit 111, the job information storage unit 112, and the terminal storage unit 31 are preferably non-volatile recording media, but can also be realized using 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 inputted via an input device may be stored in the storage unit 11, etc.

The reception unit 12, the attribute value reception unit 121, the terminal reception unit 35, the other company job information acquisition unit 131, and the company's own 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 can be realized, for example, by a processor, memory, etc. The processing procedures of the processing unit 13, etc. are usually 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 is not important.

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 a touch panel or keyboard, control software for a menu screen, etc.

The terminal output unit 36 may or may not include an output device 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 FIG. 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 a 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 an area determination process will be described using the flowcharts in Figures 4 and 5. Note that the one or more areas are areas for which a score is to be acquired.

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

(Step S305) The score acquisition unit 134 determines whether or not 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, and 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 is described using the flowchart in FIG. 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 the appeal information. An example of the appeal information acquisition process is described using the flowchart in FIG. 8.

(Step S309) The output unit 14 composes the output information. An example of such output information composition processing is described using the flowchart in FIG. 9.

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

(Step S311) The other company job information acquisition unit 131 judges whether it is the time to acquire job information. If it is the time to acquire job information, proceed to step S312, and if it is not the time to acquire job information, proceed to step S317. The processing unit 13 judges that it is the time to acquire job information, for example, when a predetermined time has arrived. The processing unit 13 judges that it is the 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 judges that it is the time to acquire job information periodically (for example, once a week). There are no restrictions on the conditions under which the processing unit 13 judges that it is the time to acquire job information.

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

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

Here, the other company 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 job information acquisition unit 131 acquires the access information of the i-th job information management device 2 from the storage unit 11. Next, the other company job information acquisition unit 131 uses the access information to acquire the above job information from the 1i-th job information management device 2. Note that the one or more pieces of job information acquired here are other company job information, but may also include the company's own job information.

(Step S315) The other company 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 job information acquisition unit 131 increments the counter i by 1. Return to step S313.

(Step S317) The reception unit 12 judges whether or not one or more pieces of job information have been received from the job information management device 2. If job information has been received, the process proceeds to step S318, and if no job information has been received, the process returns to step S301. Note that the job information received here is, for example, job information from other companies published in a free paper.

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

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

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

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

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

(Step S407) The area determination unit 133 acquires the area identifier contained in the i-th area information, and temporarily stores the area identifier 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 the counter i by 1. Return to step S403.

In the flowchart of FIG. 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 FIG. 5. In the flowchart in FIG. 5, the description of the same steps as in the flowchart in FIG. 5 will be omitted.

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

(Step S502) The area determination unit 133 acquires the line name of the nearest station to the company. The area determination unit 133 acquires, for example, the line name contained in the company's job information. The area determination unit 133 acquires the line name using, for example, the nearest station to the company. The technology for acquiring the line name using the nearest station is publicly known technology, so a detailed explanation is 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. For example, the area determination unit 133 refers to 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 present 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 acquired 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 process.

(Step S506) The area determination unit 133 obtains the travel time between the station with the jth station name 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 the threshold or is less than the threshold. If it is within the threshold, the process proceeds to step S508, and 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 accumulates the area identifier obtained in step S507 in a buffer (not shown).

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

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

(Step S601) The other company job information acquisition unit 131 acquires one or more pieces of other company job information. An example of such other company job information acquisition processing is described using the flowchart in FIG. 7.

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

(Step S603) The score acquisition unit 134 uses one or more other company's job information acquired in step S601 to determine whether or not to acquire the i-th element information. 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 and average salary information in the other company's job information, the working hours information and average working hours information in the other company's job information, the number of other company's job information, the number of other companies in the target area, information indicating that it is a "new opening," information indicating the number of years since opening, information about the age group of employees, information indicating whether it is "reduced 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 j-th element information using the company's job information acquired in step S607 and one or more other company's 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 j-th element information using the company's job information acquired in step S607 and one or more other company's job information acquired in step S601, and store it in a buffer not shown. In addition, the j-th element information is, for example, the company's salary, the company's working hours, information indicating that it is a "new opening", information indicating the number of years since opening, information on the age group of employees, information indicating whether it is "reduced hours", information indicating whether direct commutes are possible, information indicating whether driving is required, upgrade information for the target area, and salary rank.

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

(Step S612) The score acquisition unit 134 determines whether or not to use a 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 the 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 or not to acquire the kth element information. If the kth element information is to be acquired, the process proceeds to step S615; if the kth element information is not to be acquired, the process proceeds 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 accumulates it in a buffer not shown. Note that here, the score acquisition unit 134 may 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 accumulate it in a buffer not shown. The kth element information may be, for example, salary increase information and 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, and (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 of acquiring job information from other companies in step S601 will be described using the flowchart in FIG. 7.

(Step S701) The other company 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, the process proceeds to step S704; if the i-th other area does not exist, the process proceeds to step S708.

(Step S704) The other company 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 is possible from the i-th other area are met. If the commuting conditions are met, the process proceeds to step S706, and if the commuting conditions are not met, the process proceeds to step S707.

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

(Step S707) The other company job information acquisition unit 131 increments the 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 for the area of interest from the storage unit 11. Return to the upper level process.

In the flowchart of FIG. 7, the algorithm for determining whether the commuting condition is met may be another algorithm, such as an algorithm for determining whether the station is on the same line as the station in the area of interest and includes an area that includes a station that is commutable, as described above.

Next, an example of the appeal information acquisition process in step S308 will be described using the flowchart in FIG.

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

(Step S802) The appeal information acquisition unit 135 determines whether or not 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, and if the i-th area does not exist, the process returns to the upper level process.

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

(Step S804) The appeal information acquisition unit 135 determines whether or not 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 or not 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 jth appeal candidate for the company.

(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 or not 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. The appeal conditions are, for example, "company's salary - average salary >= threshold" and "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 is, for example, "The salary is '$company salary', which is high." Note that "$company salary" is a variable, and the company's salary (for example, hourly wage) is substituted into it.

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

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

In the flowchart of FIG. 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 described using the flowchart in FIG. 9.

(Step S901) The output unit 14 reads the 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 or not the i-th area for which the 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 process.

(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. Note that the level table is a table having two or more records each having a score range, a level, and color information. Note that the level may be considered as the score.

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

(Step S907) The output unit 14 acquires area information that pairs with the area identifier of the i-th area. Next, the output unit 14 changes the area identified by the area information and located on 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 in the background color.

(Step S908) The output unit 14 determines whether or not there is appeal information that pairs with the area identifier of the i-th area. If there is appeal information, the process proceeds to step S909; if there is no appeal information, the process proceeds 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 the counter i by 1. Return to step S903.

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

Now, the area information management table shown in FIG. 10 is stored in the area information storage unit 111 of the information processing device 1. 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 having an "ID," "area identifier," "range specification information," and "station information." The "station information" has a "station name," "railway name," and "station location information." The "ID" is information that identifies the record. In this case, the "range specification information" is information that is specified by three or more pieces of location information (latitude, longitude). The "station information" is the state of the station within the corresponding area. The "station location information" is information that indicates the representative location of the station (latitude, longitude).

The job information storage unit 112 also stores a job information management table shown in FIG. 11. The job information management table is a table for managing one or more pieces of job information. The job information management table has one or more records having "ID", "medium identifier", "organization identifier", "industry", "job", "address", "salary", "working hours", "remarks", and "publication date". The "medium identifier" is information for identifying the medium in which the job information was published. The medium is, for example, a paper medium such as a site managed by the job information management device 2 or a free paper. Here, the "organization identifier" is usually the company name. The "industry" is the industry of the organization that is recruiting. The "industry" may also be called the industry. The "job" is information that specifies the content of the job being recruited. Here, the "salary" is an hourly wage in units of "yen". The "remarks" has character string information. The "publication date" is the date on which the job information was published, but it may also be the date on which the job information was acquired.

The job information in the job information management table is information acquired by the other company 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 usually other company job information, but may also include the company's own job information.

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

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

A user of company A, wanting to post a job, inputs 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."

Next, the terminal device 3 receives the job information, composes 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", the job information of other companies used when calculating the score is only the job information of other companies that includes the industry "Nursing".

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> 1000 yen/hour <address> A _3rd city B _5th town . . . <industry> nursing care <job> nursing care job" 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..." in the acquired company's job information and that 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 an area identifier that identifies each area, that includes the industry of "caregiving," and that is currently hiring (for example, the posting date is "2021/10/1" or later).

Next, the score acquisition unit 134 acquires the number of job listings corresponding to each area identifier (number of job listings), associates it with the area identifier, and temporarily stores the number of job listings in a buffer not shown. The score acquisition unit 134 also acquires the salaries contained in the job listings 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 "1000 yen/hour" contained in the company's job listing, among the acquired salaries, and associates it with the area identifier, and temporarily stores the 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 formula "score for each area = w1 x number of job openings + w2 x number of upgrades (w1 and w2 are weights)," executes the formula, calculates the score for each area, and temporarily stores the scores in a buffer (not shown) in association with the area identifier.

The score acquisition unit 134 then divides the scores into four groups (rank 1, rank 2, rank 3, and rank 4), for example, with 25% of the scores increasing, associates the scores with the area identifiers, and temporarily stores the ranks in a buffer (not shown). Note that the ranks here (any of "1" to "4") may be considered as the scores. Also, the way in which the ranks are divided here is merely an example and is not restrictive.

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads out 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. In addition, for each area, the output unit 14 uses the address contained in the job information to place a symbol (here, "・") that identifies the location at the address, and also 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.

Next, the output unit 14 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 FIG. 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 the ranking of salaries of the recruiting organization (usually a company), with organizations with higher rankings having higher rankings. The higher a company's salary ranking, the lower its score (lower the difficulty of recruiting). 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> 1000 yen/hour <address> A ₃ city B ₅ 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> 1000 yen/hour <address> A ₃ city B ₅ town ... <industry> nursing care <job> nursing care worker" corresponding to the received output instruction.

Next, the area determination unit 133 uses the area information management table in 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 an area including other stations along the line nearest to the station of company A that are commutable stations in addition to the area near company A, by the process described using the flowchart in Fig. 5, for example. 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 FIG. 5.

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

Next, the score acquisition unit 134 refers to the job information management table in FIG. 11 and acquires the salary and organization identifier included in the job information that is a salary paired with an address included in any of the 13 areas determined for area (6), is job information that includes the industry "caregiving", and is currently recruiting (for example, the posting date is "2021/10/1" or later). Next, the score acquisition unit 134 acquires the salary "1000 (yen/hour)" and organization identifier "company A" that are included in the company's job information. Next, the score acquisition unit 134 sorts the acquired information using the salary as a key, acquires the ranking "8" of company A, and associates the 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 ranking of company A's salaries among 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 the salary ranking of company A. 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 treat the rank as a score for the area. Also, the higher the rank, the easier it is to hire.

Next, the score acquisition unit 134 divides the areas into four groups according to the rank of the areas. That is, the score acquisition unit 134 determines group 1 including the bottom 25% of areas (1), (2), and (5) where company A ranks lowest, group 2 including the 25% of areas (3), (6), and (7) where company A ranks next lowest, group 3 including the 25% of areas (8) and (9) where company A ranks next lowest, and group 4 including the top 25% of areas (4) where company A ranks highest, and associates each area identifier with a group identifier. In the area of group 1, company A's salary rank is low and recruitment is the most difficult, and in the area of group 4, company A's salary rank is high and recruitment is the easiest. In this case, the group identifier is, for example, one of group 1, group 2, group 3, and group 4.

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads out 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 of each area in the color specified by the obtained color information, and composes the output information. Note that group 1 including areas (1), (2), and (5) is 1501 in FIG. 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.

Next, the output unit 14 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 FIG. 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 (e.g., one year) and the number of companies showing a salary increase trend.

Then, it is assumed that the reception unit 12 of the information processing device 1 receives an output instruction containing only the business type "care" 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 that includes the industry of "nursing care" from among the job information of organizations located in each area, from the job information management table (Figure 11). Note that the acquired job information also includes past job information.

Next, the score acquisition unit 134 acquires two or more job listings for each area and organization identifier. Next, the score acquisition unit 134 calculates the salary increase rate for each area and organization identifier in a unit period (e.g., "(salary associated with the most recent posting date - salary associated with the oldest posting date) / ((year included in the most recent posting date - year included in the oldest posting date) * salary associated with the oldest posting date"). The score acquisition unit 134 also calculates the average salary increase rate for each area (e.g., "(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 which the salary increase rate is positive (salary is on an upward trend) for each area.

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 numerical value of the salary increase rate, 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 with an upward trend in salaries 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 with an upward trend in salaries, or may determine whether the number is "low," "medium," or "high" based on the ranking of the number of organizations with an upward trend in salaries.

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" (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" (e.g., value "3"), and areas other than the above as a "high difficulty" (e.g., value "4").

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

Next, the output unit 14 composes the output information as follows. That is, the output unit 14 reads the 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 score of the area, and composes the output information. Note that the score here can be said to be the recommendation level for opening a store.

Next, the output unit 14 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 FIG. 16. FIG. 16 is a diagram that allows the user to grasp recommended areas for opening a new store.

(Specific Example 4)
Currently, the storage unit 11 of the information processing device 1 stores an 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 having "ID", "appeal conditions", and "appeal information". "ID" is information that identifies a record. "ID=1" indicates that "salary" becomes appeal information when the salary is the highest in the area. "ID=2" indicates that "working hours" becomes appeal information when the working hours are between 9:00 and 16:00 and there is no other job information in the area with working hours between 9:00 and 16:00. "ID=3" indicates that "new establishment" becomes appeal information when the establishment has been open for less than two years and there is no other job information in the area that has 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 "<Organizational 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 work <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 the score for each area using any of the algorithms in specific examples 1 to 3 above. The score (difficulty of adoption) here is, 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 refers to the appeal information management table (FIG. 17) for each area and determines whether one or more other company's job information and the company's job information corresponding to each area match each appeal condition. Here, for example, it is assumed that the appeal condition for "ID=2" is matched for area (3). This is because the working hours in the company's job information satisfy the appeal condition "between 9:00 and 16:00" that is included in the appeal condition "10:00-14:00", and there is no other company's job information that has information on working hours that satisfy the "between 9:00 and 16:00" in the job information corresponding to area (3). Next, the appeal information acquisition unit 135 acquires the appeal information "salary" that is paired with the appeal condition. The appeal information acquisition unit 135 then associates the appeal information "salary" with the area identifier "area (3)" and accumulates 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 out map information from the storage unit 11. The output unit 14 acquires color information corresponding to the score associated with the area identifier for each area on the map information. Next, the output unit 14 paints the range indicated by the range identification information for each area in the color specified by the acquired 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.

Next, the output unit 14 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 FIG. 18. In FIG. 18, when a user designates 1801 on the screen of the terminal device 3 using an input means such as a mouse, appeal information for the area corresponding to the designation is output as shown in 1802 in FIG. 18.

As described above, according to this embodiment, a recruitment score can be obtained using recruitment 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 job information.

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

In addition, 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, according to this embodiment, it is possible to suggest appropriate areas for obtaining recruitment scores.

The processing in this embodiment may be realized by software. This software may be distributed by software download or the like. This 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 realizes the information processing device 1 in this embodiment is a program as described below. In other words, this program causes a computer to function as a other company job information acquisition unit that acquires other company job information related to job openings at one or more other companies, a score acquisition unit that acquires a score related to recruitment using the one or more other company job information acquired by the other company job information acquisition unit, and a score output unit that outputs the score.

(Embodiment 2)
In this embodiment, an information system having an information output device that acquires and outputs change information using job information will be described. The change information is, for example, a graph. The change information is information that can distinguish one or more publication media and is information that can grasp the change over time of the job information.

Figure 19 is a conceptual diagram of information system B in this embodiment. Information system B includes an information output device 4, one or more job information management devices 2, and one or more terminal devices 3.

The terminal device 3 here may be a terminal used by a user who is recruiting, or a terminal used by general users such as job seekers.

The information output device 4 is typically a so-called server, such as a cloud server or an ASP server. The type of information output device 4 is not important.

The information output device 4 and one or more job information management devices 2, and the information output device 4 and one or more terminal devices 3 can communicate with each other via a network such as the Internet or a LAN.

Figure 20 is a block diagram of information system B in this embodiment. The information output device 4 constituting information system B includes a storage unit 41, a reception unit 42, a processing unit 43, and an output unit 44. The storage unit 41 includes a job information storage unit 412. The processing unit 43 includes an acquisition unit 431 and a configuration unit 432. The output unit 44 includes a change output unit 441.

The storage unit 41 constituting the information output device 4 stores various types of information. The various types of information include, for example, one or more job listings and change information, which will be described later.

The job information storage unit 412 stores one or more job information. It is preferable that the job information in the job information storage unit 412 is associated with a medium identifier. The medium identifier is information that identifies the medium in which the job information is published. The medium identifier is, for example, information that identifies the medium in which the job information is published. The medium is, for example, a website that publishes job information, or a free paper or magazine that publishes job information. The medium identifier is, for example, the name of the medium in which the job information is published, or the ID of the medium in which the job information is published. The job information has one or more attribute values. The attribute values are, for example, salary information, working hours information, nearest station information, address information, area identifier, and character string information.

It is preferable that the two or more pieces of job information in the job information storage unit 412 are chronological information. Each of the two or more pieces of job information in the chronological order is job information at two or more points in time. It is preferable that each of the two or more pieces of job information in the chronological order is job information posted by an organization when recruiting. It is preferable that the job information corresponds to time information. The time information is information that specifies a time, or information that specifies a day, or information that specifies a period (e.g., month, year). The time information is, for example, information that specifies the date the job information was posted, or information that specifies the date the job information was received by the job information management device 2. The time information may be an attribute value possessed by the job information.

The job information in the job information storage unit 412 is, for example, job information acquired from one or more job information management devices 2, or job information received from the terminal device 3. The job information in the job information storage unit 412 includes the above-mentioned job information of other companies. The job information in the job information storage unit 412 may also include the above-mentioned company's own job information.

The reception unit 42 receives various instructions and information. The various instructions and information are, for example, output instructions and job information. Note that an output instruction is, for example, an instruction to output change information.

Here, acceptance usually refers to the receipt from the terminal device 3 of information, instructions, etc. transmitted via a wired or wireless communication line, but the concept may also include the acceptance of information input from an input device such as a keyboard, mouse, or touch panel, or the acceptance of information read from a recording medium such as an optical disk, magnetic disk, or semiconductor memory.

The processing unit 43 performs various types of processing. The various types of processing are, for example, processing performed by the acquisition unit 431 and the configuration unit 432.

The acquisition unit 431 acquires one or more pieces of job information. The acquisition unit 431 acquires, for example, one or more pieces of job information from one or more job information management devices 2. Such job information is usually job information posted on the job information management device 2. The acquisition unit 431 acquires job information, for example, from the job information storage unit 412. It is preferable that the job information stored in the job information storage unit 412 is job information that the acquisition unit 431 acquires from the job information management device 2 and that is stored at least temporarily. It is preferable that the acquisition unit 431 has the function of the other company job information acquisition unit 131.

It is preferable that the acquisition unit 431 acquires one or more pieces of job information in association with one or more medium identifiers. It is preferable that the acquisition unit 431 acquires job information associated with time information or job information having time information. It is preferable that the acquisition unit 431 acquires two or more pieces of job information that are associated with one organization identifier and that are associated with different time information. Such two or more pieces of job information are chronological job information.

The composition unit 432 composes change information using two or more pieces of job information acquired by the acquisition unit 431. For example, the composition unit 432 composes change information that can distinguish the publication medium identified by the medium identifier for each of two or more medium identifiers.

The change information is information that allows for understanding the change over time of the job information. It is preferable that the change information is information that allows for distinguishing the publication medium identified by the medium identifier. The change information is, for example, information regarding the change of one or more attribute values of the job information. The change information is, for example, information regarding the change of one or more attribute values of the job information of one organization. The change information is, for example, information regarding the change of one or more attribute values of the job information of two or more organizations. The change information is, for example, information regarding the change of the representative value (e.g., average value, median value, maximum value) of the salary of the job information of two or more organizations. The change information is, for example, a graph that allows for understanding the change over time of the job information. The change information is, for example, a graph that allows for understanding the change over time of the salary information, and is a graph having salary information and a time axis. The change information is, for example, information for each medium identifier, and is a set of pairs of the organization identifier and salary information of the job information. The change information is, for example, information for each medium identifier, and is information regarding the change of the representative value (e.g., average value, median value, maximum value) of the attribute value (e.g., salary, working hours) of one or more job information corresponding to each medium identifier. The structure of the change information does not matter.

The composition unit 432, for example, uses two or more pieces of job information in a time series to compose change information that is a graph with a time axis that allows for understanding changes in the job information over time.

The composition unit 432 composes change information, which is, for example, a graph that can grasp the temporal change in salary information, and is a graph having salary information and a time axis.

The output unit 44 outputs various types of information. The various types of information are, for example, change information. The change output unit 441 outputs the change information constructed by the construction unit 432.

In addition, here, output usually means transmission to the 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 the processing results to other processing devices or other programs, etc.

The storage unit 41 and the job information storage unit 412 are preferably non-volatile recording media, but can also be realized using volatile recording media.

The process by which information is stored in the storage unit 41, etc. is not important. For example, information may be stored in the storage unit 41, etc. via a recording medium, information transmitted via a communication line, etc. may be stored in the storage unit 41, etc., or information inputted via an input device may be stored in the storage unit 41, etc.

The reception unit 42 is preferably realized by a wireless or wired communication means, but may also be realized by a broadcast receiving means, a device driver for an input means such as a touch panel or keyboard, or control software for a menu screen.

The processing unit 43, the acquisition unit 431, and the configuration unit 432 can usually be realized by a processor, memory, etc. The processing procedure of the processing unit 43, etc. is usually realized by software, and the software is recorded in 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 is not important.

The output unit 44 and the change output unit 441 are realized, for example, by wireless or wired communication means. However, the output unit 44 and the change output unit 441 may also be realized by driver software for an output device, or driver software for an output device and an output device, etc.

Next, an example of the operation of the information output device 4 constituting the information system B will be described using the flowchart in FIG. 21. In the flowchart in FIG. 21, the description of the same steps as in the flowchart in FIG. 3 will be omitted.

(Step S2101) The reception unit 42 determines whether or not an output instruction has been received. If an output instruction has been received, the process proceeds to step S2102. If an output instruction has not been received, the process proceeds to step S317. Note that here, the reception unit 42 receives the output instruction from, for example, the terminal device 3.

(Step S2102) The acquisition unit 431 assigns 1 to counter i.

(Step S2103) The acquisition unit 431 determines whether the i-th medium identifier exists. If the i-th medium identifier exists, the process proceeds to step S2104; if it does not exist, the process proceeds to step S2107.

The acquisition unit 431, for example, determines whether or not the i-th medium identifier exists among one or more medium identifiers corresponding to job information that matches the condition of the output instruction. The acquisition unit 431 also determines whether or not the i-th medium identifier exists among one or more medium identifiers corresponding to job information in the job information storage unit 412. The condition of the output instruction is, for example, a condition for identifying the type of job, or a condition for identifying the area of the workplace. However, the condition is not restrictive.

(Step S2104) The acquisition unit 431 acquires one or more pieces of job information corresponding to the i-th medium identifier. Note that here, it is preferable that the acquisition unit 431 acquires one or more pieces of job information corresponding to the i-th medium identifier and that match the conditions of the output instruction.

(Step S2105) The acquisition unit 431 associates the one or more job information pieces acquired in step S2104 with the i-th medium identifier and temporarily stores them in a buffer (not shown). Note that here, it is preferable that the acquisition unit 431 associates only one or more attribute values (e.g., salary information, time information) used when acquiring change information from among the one or more job information pieces acquired in step S2104 with the i-th medium identifier and temporarily stores them in a buffer (not shown).

(Step S2106) The acquisition unit 431 increments the counter i by 1. Return to step S2103.

(Step S2107) The composition unit 432 composes change information using two or more pieces of job information temporarily stored in a buffer (not shown). An example of such change information composition processing will be described with reference to the flowchart in FIG. 22. Note that the two or more pieces of job information here may be only one or more attribute values used when acquiring the change information.

(Step S2108) The change output unit 441 outputs the change information configured in step S2107. Return to step S2101. Note that here, the change output unit 441 transmits the change information to the terminal device 3, for example.

In the flowchart in Figure 21, processing ends when the power is turned off or an interrupt occurs to end processing.

Next, an example of the change information configuration process in step S2107 will be explained using the flowchart in Figure 22.

(Step S2201) The configuration unit 432 assigns 1 to the counter i.

(Step S2202) The configuration unit 432 determines whether the i-th medium identifier exists. If the i-th medium identifier exists, the process proceeds to step S2203; if it does not exist, the process proceeds to step S2209.

The i-th medium identifier is the identifier of the i-th medium for which change information is to be configured. Typically, there are as many medium identifiers as the maximum value of i obtained in step S2103.

(Step S2203) The configuration unit 432 assigns 1 to counter j.

(Step S2204) The configuration unit 432 determines whether the jth time information exists. If the jth time information exists, the process proceeds to step S2205, and if the jth time information does not exist, the process proceeds to step S2208. The jth time information is, for example, the jth time information among the time information contained in the job information temporarily stored in a buffer (not shown) in step S2105. Also, the jth time information is, for example, the jth time information among predetermined time information.

(Step S2205) The configuration unit 432 acquires a representative value of one or more specific attribute values of the job information corresponding to the i-th medium identifier and the j-th time information. The specific attribute value is determined in advance. The specific attribute value is, for example, salary information. The specific attribute value is, for example, salary information and working hour information. The representative value of the specific attribute value is, for example, a representative value of the salary information (for example, the average, median, or maximum value).

(Step S2206) The composition unit 432 composes a record and temporarily stores it in a buffer (not shown). Note that the record is, for example, (i-th medium identifier, j-th time information, one or more specific attribute values).

(Step S2207) The configuration unit 432 increments the counter j by 1. Return to step S2204.

(Step S2208) The configuration unit 432 increments the counter i by 1. Return to step S2202.

(Step S2209) The configuration unit 432 configures change information using one or more records configured in step S2206. Then, the process returns to the upper level. Note that the change information is, for example, a table having (i-th medium identifier, j-th time information, representative value of specific attribute value) as records, or a graph configured from the table.

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

Now, let us say that a job information management table having the structure shown in FIG. 11 is stored in the job information storage unit 412 of the information output device 4. Here, let us say that the job information in the job information management table is information obtained from the sites managed by each of the four job information management devices 2.

In this situation, the user inputs "output instruction: job type = care worker (full-time employee)" into the terminal device 3. This output instruction is an instruction to output, for each medium, a graph or the like that clearly shows the transition of average salary over time for job information that has care worker (full-time employee) as an attribute value.

Next, the terminal device 3 accepts the "output instruction: occupation = care worker (full-time employee)" and transmits it to the information output device 4.

Next, the reception unit 42 of the information output device 4 receives the output instruction. Next, the acquisition unit 431 acquires the job information in chronological order, which has "job type = nursing care worker (full-time employee)" as an attribute value, from the job information management table.

Next, the configuration unit 432 acquires a representative value (e.g., a maximum value) of the salary information of one or more job information for each medium identifier and each time information. Note that the time information is information indicating the month of the posting date (or the posting start date). That is, the time information is, for example, "May 2018" and "January 2019". The configuration unit 432 then configures the change information management table shown in FIG. 23. Note that the change information management table is a table that manages one or more pieces of change information. The change information management table is also an example of change information. The change information management table has four records having "ID", "medium identifier", and "time information". The "time information" is information indicating each month from "May 2018" to "December 2021". The change information management table is also a table that shows the transition of the maximum salary information for each of the four media, and is a table in which the monthly salary information of the salary information of the job information that matches "occupation = nursing care worker (full-time employee)" is stored.

Next, the configuration unit 432 uses the change information management table of FIG. 23 to configure a graph (here, a line graph) with time information on the horizontal axis and average value of salary information on the vertical axis. Note that the graph is an example of change information. The change information management table of FIG. 23 may also be an example of change information.

Next, the change output unit 441 transmits the graph constructed by the construction unit 432 to the terminal device 3. The change output unit 441 may also transmit the change information management table of FIG. 23 to the terminal device 3.

Next, the terminal device 3 receives and outputs the graph. An example of such a graph is shown in FIG. 24. The terminal device 3 may receive and output the change information management table of FIG. 23. The terminal device 3 may also receive the change information management table of FIG. 23 and output the graph of FIG. 24 using the change information management table. When the user instructs 2401 on the graph of FIG. 24, the terminal device 3 may accept the instruction, and obtain and output change information at the time corresponding to the time information of the instruction from the change information management table of FIG. 23. An example of such output is 2402 in FIG. 24.

As described above, according to this embodiment, it is possible to provide change information regarding changes in job information over time by publication medium. Such change information is useful to personnel in organizations that are recruiting when deciding which medium to publish job information in. In addition, the change information is useful to job seekers when deciding which medium to apply to.

In addition, this embodiment can provide a graph that allows users to understand the changes over time in job information by publication medium.

In addition, this embodiment can provide a graph that allows users to understand the changes in salaries over time for job postings by publication medium.

The software for realizing the information output device 4 in this embodiment is a program as described below. In other words, this program causes a computer that can access a job information storage unit in which two or more job information pieces in a time series having one or more attribute values related to job openings are stored in association with two or more medium identifiers to function as an acquisition unit that acquires job information from the job information storage unit, a configuration unit that uses the two or more job information pieces acquired by the acquisition unit to configure change information, which is information that can distinguish the publication medium identified by the medium identifier and is information that can grasp changes in the job information over time, and a change output unit that outputs the change information configured by the configuration unit.

(Embodiment 3)
In this embodiment, an information system having an information output device that uses job information from one or more publication media to recommend information to the recruiting party is described. The recommended information is, for example, a medium identifier of a medium in which the job information should be published in the future. The recommended information is, for example, information about job information that is not suitable for the company.

In this embodiment, an information system is described that includes an information output device that uses job information from one or more publication media to recommend information to job seekers. The recommended information is, for example, a media identifier for the media to which the job seeker should apply.

The conceptual diagram of the information system C in this embodiment is the same as that in FIG. 19, except for the reference numerals. The information system C includes an information output device 5, one or more job information management devices 2, and one or more terminal devices 3.

Figure 25 is a block diagram of information system C in this embodiment. Information output device 5 constituting information system C includes a storage unit 51, a reception unit 52, a processing unit 53, and an output unit 54. Storage unit 51 includes a job information storage unit 512. Processing unit 53 includes an acquisition unit 531, a first recommendation acquisition unit 532, and a second recommendation acquisition unit 533. First recommendation acquisition unit 532 includes first score acquisition means 5321 and first recommendation acquisition means 5322. Second recommendation acquisition unit 533 includes second score acquisition means 5331 and second recommendation acquisition means 5332. Output unit 54 includes a first recommendation output unit 541 and a second recommendation output unit 542.

The storage unit 51 constituting the information output device 5 stores various types of information. The various types of information are, for example, one or more job information items and various conditions. The various conditions are, for example, the publication medium conditions described below, the application medium conditions described below, the warning conditions described below, and one or more notification destination information.

The notification destination information is information that identifies the notification destination for the person in charge of the organization. The notification destination information is, for example, an email address, a telephone number, or a user ID. The notification destination information is usually associated with an organization identifier.

The job information storage unit 512 stores one or more job information. It is preferable that the job information in the job information storage unit 512 is associated with a medium identifier. The job information storage unit 512 stores, for example, one or more job information having one or more attribute values related to the job, in association with each of two or more publication medium identifiers. The attribute values are, for example, salary information, working hours information, nearest station information, address information, area identifier, and character string information.

The reception unit 52 receives various instructions and information. The various instructions and information are, for example, output instructions and job information. Note that the output instructions are, for example, a first output instruction described below and a second output instruction described below.

Here, acceptance usually refers to the receipt from the terminal device 3 of information, instructions, etc. transmitted via a wired or wireless communication line, but the concept may also include the acceptance of information input from an input device such as a keyboard, mouse, or touch panel, or the acceptance of information read from a recording medium such as an optical disk, magnetic disk, or semiconductor memory.

The processing unit 53 performs various types of processing. The various types of processing are, for example, processing performed by the acquisition unit 531, the first recommendation acquisition unit 532, and the second recommendation acquisition unit 533.

The acquisition unit 531 acquires one or more job information items. The acquisition unit 531 performs the same operations as the acquisition unit 431, for example. However, the acquisition unit 531 does not need to acquire job information in chronological order.

The first recommendation acquisition unit 532 acquires first recommendation information for the recruiting party for each of two or more medium identifiers, using one or more job information items corresponding to each medium identifier. The first recommendation information for the recruiting party is information that is useful to the recruiting party. Note that here, it is preferable that the first recommendation acquisition unit 532 acquires first recommendation information using the latest job information item among the job information items corresponding to each medium identifier.

More specifically, the first recommendation acquisition unit 532 acquires the first recommendation information, for example, by a first score acquisition means 5321 and a first recommendation acquisition means 5322, which will be described later. Also, the first recommendation acquisition unit 532 acquires the first recommendation information, for example, by a first recommendation acquisition means 5322, which will be described later.

The first score acquisition means 5321 acquires a first score for each publication medium using one or more attribute values of one or more job listings for each of two or more medium identifiers.

More specifically, the first score acquisition means 5321 acquires, for each of the two or more medium identifiers, one or more specific attribute values possessed by each of the one or more job listings corresponding to the medium identifier. Next, the first score acquisition means 5321 acquires a first score using one or more specific attribute values possessed by each of the one or more job listings. The specific attribute values are usually determined in advance. The specific attribute values are, for example, salary information or working hours.

The first score acquisition unit 5321 acquires the first score by, for example, (1) a method using an arithmetic expression, (2) a method using machine learning, or (3) a method using a correspondence table. Each method for acquiring the first score will be described below.
(1) Method using an arithmetic formula

The first score acquisition means 5321 acquires, for each medium identifier, a representative value (e.g., maximum value, average value, median value) of one or more specific attribute values possessed by each of one or more job postings. Next, the first score acquisition means 5321 substitutes the representative value of each of the one or more specific attribute values as a parameter into an arithmetic expression, executes the arithmetic expression, and calculates a first score.

The first score acquisition means 5321, for example, acquires a representative value of the salary information contained in one or more pieces of job information for each medium identifier. Next, the first score acquisition means 5321 acquires a first score indicating the difficulty of hiring using an increasing function with the representative value of the salary information as a parameter.

The first score acquisition means 5321, for example, acquires a representative value of the working hours information contained in one or more pieces of job information for each medium identifier. Next, the first score acquisition means 5321 acquires a first score indicating the difficulty of hiring using a decreasing function with the representative value of the working hours information as a parameter.

The first score acquisition means 5321 acquires, for example, for each medium identifier, a representative value of salary information and a representative value of working hour information contained in one or more pieces of job information. Next, the first score acquisition means 5321 acquires a first score indicating the difficulty of hiring using an increasing function with the representative value of the salary information as a parameter and a decreasing function with the representative value of the working hour information as a parameter.
(2) Machine learning method

The learning unit (not shown) acquires two or more pieces of teacher data stored in the storage unit 51. The teacher data is, for example, information in which one or more specific attribute values of the job information or one or more representative values of the one or more specific attribute values are used as explanatory variables, and a score is used as a target variable. Next, the learning unit performs a machine learning learning process using two or more pieces of teacher data, acquires a learning device, and stores the learning device in the storage unit 51. For example, the learning unit provides two or more pieces of teacher data to a module that performs a machine learning learning process, executes the module, acquires a learning device, and stores the learning device in the storage unit 51. For example, deep learning, random forest, decision tree, SVR, etc. can be used as the machine learning. The module is, for example, a learning module in the TensorFlow library, a learning module in the random forest library of the R language, or a learning module of TinySVM. The learning unit may be the first score acquisition means 5321. In other words, the first score acquisition means 5321 may perform a machine learning learning process and acquire a learning device.

Next, the first score acquisition means 5321 performs a prediction process of the first score as follows. That is, the first score acquisition means 5321 acquires one or more specific attribute values or one or more representative values of each of the one or more job information for each medium identifier. Next, the first score acquisition means 5321 configures a vector whose elements are one or more specific attribute values or one or more representative values of each of the one or more specific attribute values. Next, the first score acquisition means 5321 provides a learning device and the vector to a machine learning prediction module for each medium identifier, 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 first score acquisition means 5321 accumulates the acquired scores in the storage unit 51 or a buffer not shown in the figure in association with each medium identifier.
(3) Method using the correspondence table

The first score acquisition means 5321 acquires, for each medium identifier, a representative value of one or more specific attribute values possessed by each of one or more job information items. Next, the first score acquisition means 5321 determines, from the correspondence table, correspondence information having a representative value of one or more specific attribute values that is closest to the representative value of each of the one or more specific attribute values. The first score acquisition means 5321 then acquires a first score possessed by the correspondence information from the correspondence table, associates it with each medium identifier, and accumulates the acquired first score in the storage unit 51 or a buffer not shown.

The first recommendation acquisition means 5322 acquires first recommendation information having a first medium identifier that identifies the publication medium in which the advertisement should be published, for example, by using the first score acquired by the first score acquisition means 5321.

When the first score is the hiring difficulty, the first recommendation acquisition means 5322 acquires a first medium identifier that is paired with the lowest first score, and acquires first recommendation information that includes the first medium identifier. Note that the first recommendation information here is information that recommends posting the job information in the medium identified by the first medium identifier.

The first recommendation acquisition means 5322 acquires a specific attribute value that is a specific attribute value of two or more job information items corresponding to two or more different medium identifiers, and that is paired with one organization identifier. Next, the first recommendation acquisition means 5322 determines whether the acquired two or more specific attribute values satisfy a warning condition. If the warning condition is satisfied, the first recommendation acquisition means 5322 acquires warning information. The specific attribute value is, for example, salary information. The warning condition is, for example, "two or more specific attribute values do not all match" and "the maximum value of the difference between two or more specific attribute values is equal to or greater than a threshold value." The warning information is, for example, "The salary is different in the job information items in multiple media. It is thought that the number of applications will increase if you post a job information item with a lower salary." The warning information may be of any content as long as it serves as a warning to the employer.

The first recommendation acquisition means 5322 acquires recommendation information including warning information when, for example, the specific attribute values possessed by two or more job postings corresponding to different medium identifiers and paired with a single organization identifier are different from one another. Here, the first recommendation acquisition means 5322 does not use the first score.

The second recommendation acquisition unit 533 acquires second recommendation information for the job seeker for each of the two or more medium identifiers, using one or more pieces of job information corresponding to each medium identifier. The second recommendation information is, for example, information for recommending a medium to which the job seeker should apply.

The second score acquisition means 5331 acquires a second score for each publication medium using one or more specific attribute values of one or more job information for each of two or more medium identifiers. The specific attribute values are determined in advance. The specific attribute values are, for example, salary information.

The second score acquisition unit 5331 acquires the second score by, for example, (1) a method using an arithmetic expression, (2) a method using machine learning, or (3) a method using a correspondence table. Each method will be described below.
(1) Method using an arithmetic formula

The second score acquisition means 5331 acquires, for each medium identifier, a representative value (e.g., average, median, maximum) of one or more specific attribute values possessed by each of one or more job postings. Next, the second score acquisition means 5331 substitutes the representative value of each of the one or more specific attribute values as a parameter into an arithmetic expression, executes the arithmetic expression, and calculates a second score.

The second score acquisition means 5331, for example, acquires a representative value of the salary information contained in one or more pieces of job information for each medium identifier. Next, the second score acquisition means 5331 acquires a second score indicating the degree of recommendation for application using an increasing function with the representative value of the salary information as a parameter.

The second score acquisition means 5331, for example, acquires a representative value of the working hours information contained in one or more pieces of job information for each medium identifier. Next, the second score acquisition means 5331 acquires a second score indicating the degree of recommendation for application using a decreasing function with the representative value of the working hours information as a parameter.

The second score acquisition means 5331 acquires, for example, for each medium identifier, a representative value of salary information and a representative value of working hours information contained in one or more pieces of job information. Next, the second score acquisition means 5331 acquires a second score indicating the degree of recommendation for application by an increasing function having the representative value of the salary information as a parameter and a decreasing function having the representative value of the working hours information as a parameter.
(2) Machine learning method

The learning unit (not shown) acquires two or more pieces of teacher data stored in the storage unit 51. The teacher data is, for example, information in which one or more specific attribute values of the job information or one or more representative values of the specific attribute values are used as explanatory variables, and the second score is used as a target variable. Next, the learning unit performs a machine learning learning process using the two or more pieces of teacher data, acquires a learning device, and stores the learning device in the storage unit 51. For example, the learning unit provides the two or more pieces of teacher data to a module that performs a machine learning learning process, executes the module, acquires a learning device, and stores the learning device in the storage unit 51. For example, deep learning, random forest, decision tree, SVR, etc. can be used as the machine learning. The learning unit may be the second score acquisition means 5331. In other words, the second score acquisition means 5331 may perform the machine learning learning process and acquire the learning device.

Next, the second score acquisition means 5331 performs a second score prediction process as follows. That is, the second score acquisition means 5331 acquires, for each medium identifier, one or more specific attribute values possessed by each of one or more job information items, or a representative value of one or more specific attribute values. Next, the second score acquisition means 5331 configures a vector whose elements are one or more specific attribute values or a representative value of one or more specific attribute values. Next, the second score acquisition means 5331 provides a learning device and the vector to a machine learning prediction module for each medium identifier, executes the module, and acquires a score. Then, the second score acquisition means 5331 accumulates the acquired second score in the storage unit 51 or a buffer not shown in association with each medium identifier.
(3) Method using the correspondence table

The second score acquisition means 5331 acquires, for each medium identifier, a representative value of one or more specific attribute values possessed by each of one or more job information items. Next, the second score acquisition means 5331 determines, from the correspondence table, correspondence information having a representative value of one or more specific attribute values that is closest to the representative value of each of the one or more specific attribute values. The second score acquisition means 5331 then acquires, from the correspondence table, a second score possessed by the correspondence information, associates it with each medium identifier, and accumulates the acquired second score in the storage unit 51 or a buffer not shown.

The second recommendation acquisition means 5332 uses the second score acquired by the second score acquisition means 5331 to acquire second recommendation information having a second medium identifier that identifies the publication medium to which the application should be submitted.

The second recommendation acquisition means 5332, for example, acquires a second medium identifier corresponding to an attribute value advantageous to a job seeker when there are two or more job information items associated with different medium identifiers and the specific attribute values paired with one organization identifier are different, and acquires second recommendation information including the second medium identifier. Note that the specific attribute value is, for example, salary information and working hours information. An attribute value advantageous to a job seeker is, for example, an attribute value indicating a high salary. An attribute value advantageous to a job seeker is, for example, an attribute value indicating short working hours indicated by working hours information.

The output unit 54 outputs various information. The various information is, for example, recommendation information. The recommendation information is, for example, first recommendation information and second recommendation information.

The first recommendation output unit 541 outputs the first recommendation information acquired by the first recommendation acquisition unit 532. The first recommendation output unit 541, for example, transmits the first recommendation information to the recruiting party's terminal device 3.

The second recommendation output unit 542 outputs the second recommendation information acquired by the second recommendation acquisition unit 533. The second recommendation output unit 542, for example, transmits the second recommendation information to the job seeker's terminal device 3.

The storage unit 51 and the job information storage unit 512 are preferably non-volatile recording media, but can also be realized as volatile recording media.

The process by which information is stored in the storage unit 51, etc. is not important. For example, information may be stored in the storage unit 51, etc. via a recording medium, information transmitted via a communication line, etc. may be stored in the storage unit 51, etc., or information inputted via an input device may be stored in the storage unit 51, etc.

The reception unit 52 is preferably realized by a wireless or wired communication means, but may also be realized by a broadcast receiving means, a device driver for an input means such as a touch panel or keyboard, or control software for a menu screen.

The processing unit 53, the acquisition unit 531, the first recommendation acquisition unit 532, the second recommendation acquisition unit 533, the first score acquisition means 5321, the first recommendation acquisition means 5322, the second score acquisition means 5331, and the second recommendation acquisition means 5332 can usually be realized by a processor, a memory, etc. The processing procedure of the processing unit 53, etc. is usually realized by software, and the software is recorded in a recording medium such as a ROM. However, it may also be realized by hardware (dedicated circuit). The processor may be a CPU, MPU, GPU, etc., and the type does not matter.

The output unit 54, the first recommendation output unit 541, and the second recommendation output unit 542 are realized, for example, by wireless or wired communication means.

Next, an example of the operation of the information output device 5 constituting the information system C will be described using the flowchart in FIG. 26. In the flowchart in FIG. 26, the description of the same steps as in the flowchart in FIG. 3 will be omitted.

(Step S2601) The reception unit 52 determines whether or not a first output instruction has been received from the recruiting party's terminal device 3. If a first output instruction has been received, the process proceeds to step S2602; if not, the process proceeds to step S2605.

(Step S2602) The first recommendation acquisition unit 532 performs a publication medium determination process. An example of the publication medium determination process is described using the flowchart in FIG. 27. The publication medium determination process is a process for determining the medium in which the job information should be published.

(Step S2603) The first recommendation acquisition unit 532 constructs publication medium information using the medium identifier of the medium determined in step S2602. Note that the publication medium information usually has the medium identifier obtained in the publication medium determination process.

(Step S2604) The first recommendation output unit 541 transmits the publication medium information constructed in step S2603 to the terminal device 3 that transmitted the first output instruction. Return to step S2601.

(Step S2605) The reception unit 52 determines whether or not a second output instruction has been received from the job seeker's terminal device 3. If a second output instruction has been received, the process proceeds to step S2606; if not, the process proceeds to step S2609.

(Step S2606) The second recommendation acquisition unit 533 performs an application medium determination process. An example of the application medium determination process is described using the flowchart in FIG. 28. The application medium determination process is a process for determining the medium to which a job seeker should apply.

(Step S2607) The second recommendation acquisition unit 533 constructs application medium information using the medium identifier of the medium determined in step S2606. Note that the application medium information usually has the medium identifier obtained in the application medium determination process.

(Step S2608) The second recommendation output unit 542 transmits the application medium information constructed in step S2607 to the terminal device 3 that transmitted the second output instruction. Return to step S2601.

(Step S2609) The processing unit 53 judges whether it is time to inspect the job information. If it is, the process proceeds to step S2610, and if it is not, the process proceeds to step S311. The timing for inspecting the job information is, for example, when a predetermined time arrives (for example, midnight every day) or when an instruction to inspect the job information is received.

(Step S2610) The first recommendation acquisition unit 532 assigns 1 to counter i.

(Step S2611) The first recommendation acquisition unit 532 determines whether or not an organization identifier for the i-th organization to be inspected for job information exists. If an organization identifier for the i-th organization exists, the process proceeds to step S2612; if not, the process returns to step S2601.

(Step S2612) The first recommendation acquisition unit 532 acquires specific attribute values in association with one or more medium identifiers from one or more job information items paired with the organization identifier of the i-th organization. Note that the specific attribute values are predetermined attribute values. The specific attribute values are, for example, salary information and working hours information.

(Step S2613) The first recommendation acquisition unit 532 determines whether or not the one or more specific attribute values acquired in step S2612 satisfy a warning condition. If the warning condition is satisfied, the process proceeds to step S2614, and if the warning condition is not satisfied, the process proceeds to step S2617. Note that the warning condition is, for example, that the specific attribute values associated with each of the two or more medium identifiers are different values.

(Step S2614) The first recommendation acquisition unit 532 constructs warning information. The warning information has, for example, a pair of a specific attribute value and a medium identifier. The warning information has, for example, a pair of salary information published in each of two or more media and a medium identifier.

(Step S2615) The first recommendation output unit 541 acquires notification destination information corresponding to the organization identifier of the i-th organization. Note that the first recommendation output unit 541 acquires, for example, notification destination information paired with the organization identifier of the i-th organization from the storage unit 51. In addition, the first recommendation output unit 541 acquires notification destination information that is, for example, the terminal identifier (e.g., IP address) of the terminal device 3 that has sent the instruction to inspect the job information.

(Step S2616) The first recommendation output unit 541 sends the warning information constructed in step S2614 to the notification destination identified by the notification destination information acquired in step S2615.

(Step S2617) The first recommendation acquisition unit 532 increments the counter i by 1. Return to step S2611.

Next, an example of the publication medium determination process in step S2602 will be explained using the flowchart in Figure 27.

(Step S2701) The first recommendation acquisition unit 532 acquires one or more job information items corresponding to the first output instruction.

The first recommendation acquisition unit 532, for example, reads out one or more job information that matches the conditions of the first output instruction (for example, "posted within the last month" or "job type of attribute value = specific job type (for example, nursing care)") from the job information storage unit 512. The first recommendation acquisition unit 532 also searches one or more job information management devices 2 for one or more job information that matches the conditions of the first output instruction, and acquires them. Note that it is preferable that the first recommendation acquisition unit 532 acquires only the most recent job information.

(Step S2702) The first recommendation acquisition unit 532 assigns 1 to counter i.

(Step S2703) The first recommendation acquisition unit 532 determines whether the i-th medium identifier exists. If the i-th medium identifier exists, the process proceeds to step S2704; if it does not exist, the process proceeds to step S2706.

(Step S2704) The first recommendation acquisition unit 532 acquires one or more specific attribute values corresponding to the i-th medium identifier. Note that the specific attribute value here is an attribute value used when determining the medium to be recommended in order to recommend to the recruiting party the medium in which the job information should be posted. The one or more specific attribute values are, for example, one or more pieces of information among a representative value of salary information (e.g., average, median, maximum value) of one or more organizations, a representative value of working hours information (e.g., average, median, maximum value), and a representative value of the number of holidays per year (e.g., average, median, maximum value).

Note that here, the first score acquisition means 5321 may acquire a first score for the i-th medium identifier using one or more acquired specific attribute values. Such a first score may also be considered to be a specific attribute value for the i-th medium identifier.

(Step S2705) The first recommendation acquisition unit 532 increments the counter i by 1. Return to step S2703.

(Step S2706) The first recommendation acquisition unit 532 acquires one or more medium identifiers for which the one or more specific attribute values acquired in step S2704 match the publication medium conditions. The process returns to the upper level process.

The conditions for the publication medium are, for example, that the representative value of the salary information is the lowest, that the first score of the difficulty of hiring is the smallest, and that the first score is equal to or less than the threshold value.

An example of the application medium determination process in step S2606 is explained using the flowchart in Figure 28.

(Step S2801) The second recommendation acquisition unit 533 acquires one or more job information items corresponding to the second output instruction.

The second recommendation acquisition unit 533, for example, reads out one or more job information that matches the conditions of the second output instruction (for example, "posted within the last month" or "job type of attribute value = specific job type (for example, nursing care)") from the job information storage unit 512. The second recommendation acquisition unit 533 also searches one or more job information management devices 2 for one or more job information that matches the conditions of the second output instruction, and acquires them. Note that it is preferable that the second recommendation acquisition unit 533 acquires only the most recent job information.

(Step S2802) The second recommendation acquisition unit 533 assigns 1 to counter i.

(Step S2803) The second recommendation acquisition unit 533 determines whether the i-th medium identifier exists. If the i-th medium identifier exists, the process proceeds to step S2804; if it does not exist, the process proceeds to step S2806.

(Step S2804) The second recommendation acquisition unit 533 acquires one or more specific attribute values corresponding to the i-th medium identifier. Note that the specific attribute value here is an attribute value used when determining the medium to be recommended in order to recommend a medium that is advantageous to the job seeker. The one or more specific attribute values are, for example, one or more pieces of information among a representative value of salary information (e.g., average, median, maximum value) of one or more organizations, a representative value of working hours information (e.g., average, median, maximum value), and a representative value of the number of annual holidays (e.g., average, median, maximum value).

Note that here, the second score acquisition means 5331 may acquire a second score for the i-th medium identifier using one or more acquired specific attribute values. Such a second score may also be considered to be a specific attribute value for the i-th medium identifier.

(Step S2805) The second recommendation acquisition unit 533 increments the counter i by 1. Return to step S2803.

(Step S2806) The second recommendation acquisition unit 533 acquires one or more medium identifiers whose one or more specific attribute values acquired in step S2804 match the application medium conditions. Return to the upper process.

The application medium conditions are, for example, that the representative value of the salary information is the highest, that the second score of the application recommendation level is the lowest, and that the second score is equal to or less than the threshold value.

Below, four specific examples of the operation of information system C in this embodiment are described. It is assumed that a job information management table having the structure shown in FIG. 11 is stored in the job information storage unit 512 of the information output device 5. The job information in the job information management table is information that the acquisition unit 531 automatically acquires from the sites managed by each of the four job information management devices 2. It is assumed that the medium identifiers of the sites (job sites) managed by each of the four job information management devices 2 are "M01", "M02", "M03", and "M04", respectively.

(Specific Example 1)
Assume that it is now May 1, 2021. Assume also that the job information storage unit 512 of the information output device 5 stores job information that was posted at the end of April 2021, which the acquisition unit 531 has acquired from each of the four job information management devices 2.

Next, it is assumed that the reception unit 52 of the information output device 5 receives a first output instruction "job type = nursing care worker (full-time employee)" from the employer's terminal device 3. Next, the first recommendation acquisition unit 532 performs a publication medium determination process as follows. That is, the first recommendation acquisition unit 532 acquires, for example, the maximum salary information among the attribute value "salary information" in the job information that matches the condition "job type = nursing care worker (full-time employee)" and corresponds to the time information "April 2021", in association with the medium identifier. Here, it is assumed that the first recommendation acquisition unit 532 acquires, for example, the maximum salary information "200,000" published in the medium "M1", the maximum salary information "205,000" published in the medium "M2", the maximum salary information "210,000" published in the medium "M3", and the maximum salary information "215,000" published in the medium "M4".

Next, the first recommendation acquisition unit 532 acquires a medium identifier "M1" in which one or more specific attribute values (here, the maximum salary information) match the publication medium condition "maximum salary information is the lowest."

Next, the first recommendation acquisition unit 532 uses the medium identifier "M1" of the determined medium to construct the posting medium information "We recommend that you post the job listing on the medium "M1". Note that the first recommendation acquisition unit 532 constructs the posting medium information by, for example, substituting the acquired medium identifier for the variable "& medium identifier" of the posting medium information template "We recommend that you post the job listing on the medium "& medium identifier"" stored in the storage unit 51. Note that the algorithm by which the first recommendation acquisition unit 532 constructs the posting medium information is not important.

Next, the first recommendation output unit 541 transmits the publication medium information to the terminal device 3 that transmitted the first output instruction.

Next, the terminal device 3 that sent the first output instruction receives and outputs the publication medium information. In other words, the terminal device 3 outputs the publication medium information "We recommend that you post the job information on the medium "M1".

The output publication medium information is, for example,
"The highest salary of a competitor company listed in the media "M01" is "200,000"
The highest salary of a competitor company listed in the media "M02" is "205,000."
The highest salary of a competitor company listed in the media "M03" is "210,000."
The highest salary of a competitor listed in the media "M04" is "215,000"
Therefore, I recommend the medium "M01"
In this way, it is preferable to include specific attribute values of two or more media. This allows the user to understand the basis for recommending a media that posts job information.

As described above, according to this specific example, it is possible to analyze job information from other companies that may be published in each medium, and recommend the medium in which the job information should be posted.

(Specific Example 2)
It is assumed that the reception unit 52 of the information output device 5 receives a first output instruction "job type = nursing care worker (full-time employee), company's salary information = 205,000" from the recruiting party's terminal device 3. Note that "company's salary information = 205,000" is the salary information to be included in the recruitment information planned by the company.

Next, it is assumed that the reception unit 52 of the information output device 5 receives a first output instruction "Occupation = Care worker (Full-time employee)" from the recruiting party's terminal device 3. Next, the first recommendation acquisition unit 532 performs a publication medium determination process as follows.

In other words, the first recommendation acquisition unit 532 acquires, for each medium identifier, the attribute value "salary information" in the job information that matches the condition "job type = nursing care worker (full-time employee)" and corresponds to the time information "April 2021."

Next, the first recommendation acquisition unit 532 acquires, for each medium identifier, the number of organizations for which job information was obtained, and the ranking of the company's salary information. Next, the first score acquisition means 5321 uses the ranking to assign a first score to each medium identifier, one of three levels of hiring difficulty: "high," "normal," or "low." For example, the first recommendation acquisition unit 532 acquires a hiring difficulty of "high" if the ranking is within the bottom 30%, a hiring difficulty of "low" if the ranking is within the top 20%, and a hiring difficulty of "normal" otherwise.

Then, the first recommendation acquisition unit 532 creates publication medium information having the difficulty of adoption and ranking for each medium identifier.

Next, the first recommendation output unit 541 transmits the publication medium information to the terminal device 3 that transmitted the first output instruction.

Next, the terminal device 3 that sent the first output instruction receives and outputs the publication medium information. An example of the output of such publication medium information is shown in FIG. 29.

As described above, according to this specific example, by comparing the job information (e.g., salary information) of other companies that may be published in each medium with the job information (e.g., salary information) of the company, it is possible to recommend the medium in which the job information should be posted.

(Specific Example 3)
It is assumed that the reception unit 52 of the information output device 5 receives an instruction to inspect job information "organization identifier=X" from the terminal device 3. Next, the first recommendation acquisition unit 532 acquires salary information of each medium paired with "organization identifier=X" from the job information storage unit 512 or the job information management device 2 of each medium, in association with the medium identifier. It is assumed here that the first recommendation acquisition unit 532 acquires, for example, "200,000" in association with medium "M01" and "220,000" as the highest salary of a competing company posted in medium "M02".

Next, the first recommendation acquisition unit 532 determines that the two acquired specific attribute values (here, salary information) satisfy a warning condition (here, two or more specific attribute values are different).

Next, the first recommendation acquisition unit 532 constructs warning information. The warning information here is, "The salary in medium "M01" is "200,000" yen, and the salary in medium "M02" is "220,000" yen. To increase the number of applications, it would be better to set the listed salary in medium "M01" to "220,000" yen." Next, the first recommendation output unit 541 transmits the warning information to the terminal device 3.

The terminal device 3 then receives and outputs the warning information.

As described above, according to this specific example, if a company posting job information containing different attribute values unintentionally in multiple media, an alert notification can be sent.

(Specific Example 4)
Now, it is assumed that the reception unit 52 of the information output device 5 has received the second output instruction “Occupation=care worker (permanent employee)” from the terminal device 3 of the job seeker.

Next, the second recommendation acquisition unit 533 performs application medium determination processing as follows. That is, the second recommendation acquisition unit 533 acquires a specific attribute value (here, salary information) for each medium from the job information of each medium that matches the condition "job type = nursing care worker (full-time employee) organization identifier = X". Here, it is assumed that the salary information "(medium "M01", salary information "200,000") (medium "M02", salary information "220,000")" of each medium that matches the condition "job type = nursing care worker (full-time employee) organization identifier = X" has been acquired.

Next, the second recommendation acquisition unit 533 acquires the medium identifier "M02" from the two acquired specific attribute values that matches the application medium condition (here, "salary information is the highest").

Next, the second recommendation acquisition unit 533 constructs application medium information including the medium identifier "M02" (e.g., "We recommend that you apply to "M02"").

Next, the second recommendation output unit 542 transmits the applied medium information to the terminal device 3 that transmitted the second output instruction.

Next, the terminal device 3 receives and outputs the application medium information.

It is preferable that the application medium information constructed by the second recommendation acquisition unit 533 includes all acquired medium identifiers and specific information. In such a case, the application medium information is, for example, "There is a posting on medium "M01" for a salary of 200,000 yen, and on medium "M02" for a salary of 220,000 yen. Therefore, we recommend medium "M02."."

As described above, this specific example suggests to job seekers the best medium to use for applying.

As described above, according to this embodiment, appropriate information can be provided to the employer using job information for each publication medium. Note that appropriate information is, for example, information that suggests the medium in which the job should be published.

In addition, according to this embodiment, an organization offering a job can check job information in two or more publication media, and if the warning conditions are met, a warning can be issued to the organization offering a job.

Furthermore, according to this embodiment, appropriate information can be provided to job seekers using job information by publication medium. Note that appropriate information is, for example, information that suggests the medium to which a job seeker should apply.

The software for realizing the information output device 5 in this embodiment is the following program. In other words, this program causes a computer to function as an acquisition unit that acquires one or more pieces of job information from a job information storage unit in which two or more pieces of job information having one or more attribute values related to job offers are stored in association with two or more medium identifiers, a first recommendation acquisition unit that acquires first recommendation information for the recruiting party using one or more pieces of job information corresponding to each of the two or more medium identifiers, and a first recommendation output unit that outputs the first recommendation information.

This program also causes the computer to function as an acquisition unit that acquires one or more pieces of job information from a job information storage unit in which two or more pieces of job information having one or more attribute values related to job offers are stored in association with each of two or more medium identifiers, a second recommendation acquisition unit that acquires second recommendation information for job seekers using one or more pieces of job information corresponding to each of the two or more medium identifiers, and a second recommendation output unit that outputs the second recommendation information.

Figure 30 also shows the appearance of a computer that executes the programs described in this specification to realize the information output device 4 and the like of the various embodiments described above. The above-mentioned embodiments can be realized by computer hardware and a computer program executed thereon. Figure 30 is an overview of this computer system 300, and Figure 31 is a block diagram of system 300.

In FIG. 30, computer system 300 includes computer 301, which includes a CD-ROM drive, keyboard 302, mouse 303, and monitor 304.

In FIG. 31, in addition to a CD-ROM drive 3012, computer 301 includes an MPU 3013, a bus 3014 connected to the CD-ROM drive 3012 etc., a ROM 3015 for storing programs such as a boot-up program, a RAM 3016 connected to the MPU 3013 for temporarily storing instructions for application programs and providing temporary storage space, and a hard disk 3017 for storing application programs, system programs, and data. Although not shown here, computer 301 may further 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 output device 4 and the like of the above-mentioned embodiment may be stored on the CD-ROM 3101, inserted into the CD-ROM drive 3012, and then transferred to the hard disk 3017. Alternatively, the program may be sent to the computer 301 via a network (not shown) and stored on the hard disk 3017. The program is loaded into the RAM 3016 when executed. The program may be loaded directly from the CD-ROM 3101 or the network.

The program does not necessarily have to include an operating system (OS) that causes the computer 301 to execute the functions of the information output device 4 of the above-mentioned embodiment, or a third-party program. The program only needs to include an instruction portion that calls appropriate functions (modules) in a controlled manner to obtain the desired results. How the computer system 300 operates is well known, and a detailed description will be omitted.

In addition, 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 is performed only by hardware).

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.

Furthermore, in each of the above embodiments, it goes without saying that two or more communication means present in one device may be realized physically by one medium.

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

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

As described above, the information output device of the present invention has the effect of being able to provide appropriate information using chronological job information by publication medium, and is useful as an information output device, etc.

A, B Information system 4, 5 Information output device 41, 51 Storage unit 42, 52 Reception unit 43, 53 Processing unit 44, 54 Output unit 412, 512 Job information storage unit 431, 531 Acquisition unit 432 Configuration unit 441 Change output unit 532 First recommendation acquisition unit 533 Second recommendation acquisition unit 541 First recommendation output unit 542 Second recommendation output unit 5321 First score acquisition means 5322 First recommendation acquisition means 5331 Second score acquisition means 5332 Second recommendation acquisition means

Claims (12)

An acquisition unit that acquires two or more pieces of job information from a job information storage unit that stores two or more pieces of job information in a time series, the two or more pieces of job information having one or more attribute values related to job vacancies , each of the two or more pieces of job information being associated with a medium identifier that identifies a medium in which the job information is published;
A configuration unit that configures change information, which is information that can distinguish a publication medium identified by the medium identifier using the two or more job information acquired by the acquisition unit , is information that can grasp a change in the job information over time , and is information regarding a change in one or more attribute values of the job information ;
and a change output unit that outputs the change information configured by the configuration unit. The job information acquired by the acquisition unit corresponds to one of two or more medium identifiers,
The change output unit is
2. The information output device according to claim 1, wherein the change information is outputted, which enables a time-dependent change in job information in two or more publication media to be grasped simultaneously. The component comprises:
3. The information output device according to claim 1, further comprising: a time axis graph that allows the user to grasp the change over time in the job information, the change information being a graph using two or more pieces of job information in time series. The one or more attribute values include salary information;
The component comprises:
4. The information output device according to claim 3, wherein the change information is a graph that enables the change in salary information over time to be grasped, the change information being a graph having salary information and a time axis. A first recommendation acquisition unit that acquires first recommendation information for a recruiting party using one or more job information items corresponding to each of the two or more medium identifiers;
The information output device according to claim 2 , further comprising a first recommendation output unit that outputs the first recommendation information. The first recommendation acquisition unit,
A first score acquisition means for acquiring a first score for each of the posting media using one or more attribute values of one or more job information for each of the two or more medium identifiers;
The information output device according to claim 5 , further comprising a first recommendation acquisition means for acquiring first recommendation information having a first medium identifier for identifying the medium in which the information should be published, using the first score acquired by the first score acquisition means. The job information includes an organization identifier that identifies the organization offering the job,
The first recommendation acquisition unit,
The information output device of claim 5 further comprises a first recommendation acquisition means for acquiring recommendation information including warning information when the recommendation information corresponds to two or more job information items corresponding to different media identifiers and a specific attribute value paired with an organization identifier satisfies a warning condition. A second recommendation acquisition unit that acquires second recommendation information for a job seeker using one or more job information items corresponding to each of the two or more medium identifiers;
The information output device according to claim 2 , further comprising a second recommendation output unit that outputs the second recommendation information. The second recommendation acquisition unit,
A second score acquisition means for acquiring a second score for each of the publication media using one or more attribute values of one or more job information for each of the two or more medium identifiers;
The information output device of claim 8, further comprising a second recommendation acquisition means for acquiring second recommendation information having a second medium identifier for identifying the publication medium to which the application should be submitted, using the second score acquired by the second score acquisition means. The second recommendation acquisition unit,
The information output device of claim 8 further comprises a second recommendation acquisition means for acquiring a second media identifier corresponding to an attribute value that is advantageous to a job seeker when the two or more job information items correspond to different media identifiers and the specific attribute values paired with a single organization identifier are different, and acquiring second recommendation information including the second media identifier. An information processing method including all processes performed by the information output device according to claim 1 . Computer ,
A program for causing an information output device according to any one of claims 1 to 10 to function as such an information output device .

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