Employment management system, employment management program, and employment management method

Abstract

To provide an employment management system that appropriately recommends job information in areas far from a job seeker's address. [Solution] A job recommendation model has been machine-trained to output the probability that a job seeker will be interested in a job listing as output data using learning data including job seeker information indicating a job seeker, job information, features identifying the work location where the job seeker tends to work, and features indicating whether the job seeker has shown interest in the job information. By inputting input data including a job seeker identifier indicating an actual job seeker and job information including a work location, the model outputs the probability that the job seeker will be interested in the job information.

Description

[Technical field]

[0001] The present invention relates to an employment management system, an employment management program, and an employment management method. [Background technology]

[0002] There is a known job matching system service in which a company (client) posts short-term job openings for a few hours, and workers can select work at various companies on the days and times they desire, allowing them to work short hours such as part-time rather than on a continuous basis with a specific company (Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-184310 A Summary of the Invention [Problem to be solved by the invention]

[0004] In the past, when a worker received job offers, only jobs in areas close to the address registered by the worker were offered. However, jobs in areas other than the worker's school, work, or other living areas were not offered, and there was a problem that the job offers were not properly matched with the worker's desired place of employment. [Means for solving the problem]

[0005] One aspect of the present invention is an employment management system that recommends job information to a job seeker, and is characterized in that the system outputs the probability that the job seeker will be interested in the job information by inputting input data including a job seeker identifier indicating an actual job seeker and job information including a workplace into a job recommendation model that has been machine-trained to output the probability that the job seeker will be interested in the job information as output data using learning data that includes job seeker information indicating the job seeker, job information, features that identify the work location where the job seeker tends to work, and features that indicate whether the job seeker has shown interest in the job information.

[0006] Here, it is preferable that the feature included in the learning data indicating whether the job seeker has shown interest is information indicating whether the job seeker has registered the job information as a favorite.

[0007] In addition, it is preferable that the feature included in the learning data indicating whether or not the job seeker has shown interest is information indicating whether or not the job seeker has actually worked for the job information.

[0008] In addition, it is preferable that the feature amount included in the learning data indicating whether or not the job seeker has shown interest is information indicating whether or not the job seeker has viewed the job information.

[0009] It is also preferable that the job information be preferentially displayed on the job seeker terminal used by the job seeker in accordance with the probability that the job seeker will be interested in the job information.

[0010] It is also preferable that the learning data further includes at least one of a feature indicating whether the job offer is for an industry or job that the job seeker tends to work in, a feature indicating whether the job offer is for a day or time that the job seeker tends to work, a feature indicating whether the job offer is for a remuneration range that the job seeker tends to work, a feature indicating whether the job offer is for working hours that the job seeker tends to work, a feature indicating whether the job offer is for additional information that the job seeker tends to work, a feature indicating a tendency for people of the same gender as the gender registered by the job seeker to work, and a feature indicating a tendency for people of the same age as the age group registered by the job seeker to work.

[0011] Another aspect of the present invention is an employment management program that recommends job information to a job seeker, comprising: causing a computer to function as a job recommendation model that has been machine-learned to output, as output data, the probability that the job seeker will be interested in the job information, using learning data including job seeker information indicating the job seeker, job information, a feature identifying a work location where the job seeker tends to work, and a feature indicating whether the job seeker has shown interest in the job information; and causing a computer to output the probability that the job seeker will be interested in the job information by inputting input data including a job seeker identifier indicating an actual job seeker and job information including a work location into the job recommendation model.

[0012] Another aspect of the present invention is an employment management method for recommending job information to a job seeker, comprising the steps of: inputting input data including a job seeker identifier indicating an actual job seeker and job information including a workplace to a job recommendation model that has been machine-trained to output the probability that the job seeker will be interested in the job information as output data using learning data including job seeker information indicating the job seeker, job information, a feature identifying a work location where the job seeker tends to work, and a feature indicating whether the job seeker has shown interest in the job information, and causing a computer to output the probability that the job seeker will be interested in the job information. Effect of the Invention

[0013] According to the present invention, job information in areas far from the job seeker's address can also be appropriately recommended. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a diagram showing a configuration of an employment management system in an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating a configuration of a management server according to an embodiment of the present invention. [Diagram 3] FIG. 2 is a diagram showing a configuration of an employee terminal in the embodiment of the present invention. [Figure 4] FIG. 2 is a diagram showing a configuration of a job seeker terminal according to the embodiment of the present invention. [Diagram 5] 2 is a functional block diagram showing a configuration of a management server according to an embodiment of the present invention; FIG. [Figure 6] FIG. 2 is a diagram showing an example of a job seeker information database in the embodiment of the present invention. [Figure 7] FIG. 2 is a diagram illustrating an example of a job information database according to the embodiment of the present invention. [Figure 8] FIG. 1 is a diagram illustrating an example of a grid system according to an embodiment of the present invention. [Figure 9] FIG. 4 is a diagram illustrating an example of a performance database according to the embodiment of the present invention. [Figure 10] FIG. 2 is a schematic diagram showing the configuration of a job recommendation model in an embodiment of the present invention. [Figure 11] FIG. 4 is a diagram showing an example of learning data in the embodiment of the present invention. [Figure 12] FIG. 4 is a diagram showing an example of output data according to the embodiment of the present invention. [Figure 13] FIG. 4 is a diagram showing an example of input data according to the embodiment of the present invention. [Figure 14] FIG. 4 is a diagram showing an example of output data according to the embodiment of the present invention. [Figure 15] FIG. 13 is a diagram showing an example of a job information recommendation result in a conventional employment management system. [Figure 16] FIG. 11 is a diagram showing an example of a job information recommendation result in the employment management system according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] As shown in Figure 1, employment management system 100 in an embodiment of the present invention includes a management server 102, an employer terminal 104, and a job seeker terminal 106. There may be one employer terminal 104 and one job seeker terminal 106, or there may be multiple employer terminals 104 and job seeker terminals 106. Management server 102, employer terminal 104, and job seeker terminal 106 are connected to each other via an information and communications network 108 such as the Internet so that they can exchange information with each other.

[0016] The information and communications network 108 is not limited to the Internet, but may be anything that can communicatively connect the management server 102, the employer terminals 104, and the job seeker terminals 106 to each other. For example, it may be a dedicated line, a public line (telephone line, mobile communication line, etc.), a wired LAN (Local Area Network), a wireless LAN, etc., or it may be a combination of these with the Internet.

[0017] Management server 102 is a server that performs processes such as concluding employment contracts between employers and job seekers (laborers), managing the attendance of job seekers (laborers), and paying salaries from employers to job seekers (laborers) via employer terminal 104 and job seeker terminal 106. Management server 102 is also a server that performs processes to propose job offers from employers to job seekers.

[0018] As shown in FIG. 2, the management server 102 includes a processing unit 10, a storage unit 12, an input unit 14, an output unit 16, and a communication unit 18. The processing unit 10 includes a processor or other means for performing arithmetic processing, such as a CPU or a GPU. The processing unit 10 executes a management server program stored in the storage unit 12, thereby achieving a function of matching companies using the employer terminal 104 with workers using the job seeker terminal 106 in the employment management system 100 of this embodiment, and performing processes such as employment contracts, attendance management, and salary payment. The storage unit 12 includes storage means such as a semiconductor memory, a hard disk, and a memory card. The storage unit 12 is connected to the processing unit 10 so as to be accessible, and stores the management server program and information required for the processing. The input unit 14 includes a means for inputting information. The input unit 14 includes, for example, a keyboard, a touch panel, buttons, etc. for receiving input from the administrator. The output unit 16 includes a means for outputting the processing results in the management server 102, such as a user interface screen (UI) for receiving input information from the administrator. The output unit 16 includes, for example, a display that presents an image to the manager. The communication unit 18 includes an interface that communicates information with the employer terminal 104 and the job seeker terminal 106 via an information and communication network 108. The communication by the communication unit 18 may be wired or wireless.

[0019] The employer terminal 104 is a terminal used by an employer who wants to hire a worker. As shown in FIG. 3, the employer terminal 104 includes a processing unit 20, a storage unit 22, an input unit 24, an output unit 26, and a communication unit 28. The processing unit 20 includes a processor that performs arithmetic processing, such as a CPU or a GPU. The processing unit 20 executes the employer terminal program stored in the storage unit 22 to realize the function of the employer terminal in the employment management system 100 in this embodiment. The storage unit 22 includes a storage unit such as a semiconductor memory, a hard disk, or a memory card. The storage unit 22 is connected to the processing unit 20 so as to be accessible, and stores the employer terminal program and information required for the processing. The input unit 24 includes a means for inputting information. The input unit 24 includes, for example, a keyboard, a touch panel, buttons, a camera, etc. that receive input from an employer on the company side. The output unit 26 includes a means for outputting information required for processing on the employer terminal 104, such as a screen for receiving input information from an employer and a display that displays image information such as a user interface screen (UI). The communication unit 28 includes an interface for communicating information with the management server 102 via the information communication network 108. The communication by the communication unit 28 may be wired or wireless.

[0020] The job seeker terminal 106 is a terminal used by a job seeker who wishes to work part-time or the like. As shown in FIG. 4, the job seeker terminal 106 includes a processing unit 30, a storage unit 32, an input unit 34, an output unit 36, and a communication unit 38. The processing unit 30 includes a processor or other means for performing arithmetic processing, such as a CPU or a GPU. The processing unit 30 executes a job seeker terminal program stored in the storage unit 32 to realize the function of the job seeker terminal in the employment management system 100 of this embodiment. The storage unit 32 includes a storage means such as a semiconductor memory, a hard disk, or a memory card. The storage unit 32 is connected to the processing unit 30 in an accessible manner, and stores the job seeker terminal program and information required for the processing. The input unit 34 includes a means for inputting information. The input unit 34 includes, for example, a keyboard, a touch panel, buttons, a camera, etc. for receiving input from a user who will become a worker. The output unit 36 ​​includes a means for outputting information required for processing in the job seeker terminal 106, such as a screen for receiving input information from a user and a display for displaying image information such as a user interface screen (UI). The communication unit 38 includes an interface for communicating information with the management server 102 via the information communication network 108. The communication by the communication unit 38 may be wired or wireless.

[0021] The employer terminal 104 and the job seeker terminal 106 can be various information processing devices capable of executing programs for providing the services of the employment management system 100. For example, the employer terminal 104 and the job seeker terminal 106 can be a fixed or portable dedicated machine, a personal computer (PC), a tablet computer, a smartphone, a mobile phone terminal, a PHS (Personal Handy-phone System) terminal, a personal digital assistant (PDA), a multi-function television receiver with information processing capabilities (a so-called smart TV), etc.

[0022] The employer terminal 104 and the job seeker terminal 106 can be implemented by installing an application (for the employer or for the job seeker). The job seeker operates the job seeker terminal 106 to start up the application and registers for use with the management server 102. Similarly, the employer operates the employer terminal 104 to start up the application and registers for use with the management server 102.

[0023] The program may be provided as a program product, that is, as a program stored in a tangible information medium, or as a program downloadable via an information communication network such as the Internet.

[0024] Furthermore, the processing in this embodiment is executed by processors included in management server 102, employer terminal 104, and job seeker terminal 106. In this case, the processing of management server 102, employer terminal 104, and job seeker terminal 106 may be appropriately combined, or may be appropriately divided and executed among a plurality of devices.

[0025] [Service Overview] The employment management system 100 according to this embodiment provides services such as the conclusion of employment contracts between job seekers seeking part-time or other employment and employers looking to hire people, attendance management, and salary payment.

[0026] Specifically, a job seeker transmits his / her job seeker information, which is his / her information, to management server 102 via job seeker terminal 106. An employer transmits employment information, including employment conditions, such as employment hours and wages, to management server 102 via employer terminal 104, and presents the employment information to the job seeker. A job seeker browses the employment information presented by the employer via job seeker terminal 106, and if he / she applies for the job, transmits an employment request to management server 102 indicating that he / she will apply for the job. An employer browses the job seeker's application for the employment information via employer terminal 104, and if he / she is willing to hire the job seeker, receives from management server 102 a code that links the employment conditions and the job seeker who wishes to work. When the job seeker comes to work, he / she reads the code shown by the employer via employer terminal 104 using job seeker terminal 106. As a result, management server 102 stores the fact that the job seeker has agreed to the employment conditions and a contract has been concluded, and stores the read time as the work time. The job seeker also reads the code again when he or she clocks out from work, and the management server 102 then stores the time when the code is read as the clock-out time.

[0027] The management server 102 also deposits wages, which are compensation for labor, into an account or the like previously associated with the job seeker, according to the job seeker's arrival and departure times and the hourly wage and other wage payment conditions included in the employment conditions. It also collects wages and fees, such as commission, paid to the job seeker from an account or the like previously associated with the employer. It may also be configured to perform accounting procedures related to the payment of these wages.

[0028] In this way, by managing contracts at the time of attendance, it is possible to simplify the cumbersome procedures between job seekers and employers. In addition, by managing attendance and departure times, it is possible to accurately grasp working hours and provide accurate services such as wage payments.

[0029] [Processing on Management Server 102] In the employment management system 100 according to this embodiment, a job recommendation process is performed to recommend job information to job seekers.

[0030] 5 is a block diagram showing the functional configuration of the management server 102. The management server 102 functions as a job seeker information receiving unit 40, a job information receiving unit 42, a job recommendation learning unit 44, and a job recommendation processing unit 46 by executing a management server program.

[0031] In addition, the storage unit 12 of the management server 102 functions as a job seeker information database 60, a job information database 62, and a performance database 64.

[0032] 6, the job seeker information database 60 stores information about job seekers, such as an identifier for identifying the job seeker (hereinafter referred to as a job seeker ID), the job seeker's name, address, email address, telephone number, date of birth, age, sex, an image (photo) related to the job seeker, Good evaluation rate, cancellation rate, and last-minute cancellation rate, in association with each other. The information stored in the job seeker information database 60 is not limited to this information, and may be any information necessary related to job seekers.

[0033] 7, the job information database 62 stores, in association with one another, information about the employer and employment conditions, such as an identifier for identifying the job information (hereinafter referred to as a job ID), an identifier for identifying the employer providing the job information (hereinafter referred to as an employer ID), the name of the employer (e.g., store name), location, contact phone number, type of business, and an image (photo) of the employer. The information stored in the job information database 62 is not limited to this information, and may include information necessary for displaying the job information, etc. described below, information necessary for the employer, and information regarding the employment conditions.

[0034] The information indicating the location such as the address of the job seeker and the workplace of the job information is specified by a grid system expressed by cells that divide the geographical space into a mesh shape. For example, as shown in FIG. 8, a grid system in which the geographical space is divided into hexagonal cells such as H3 provided by Uber can be applied. Also, a grid system in which the geographical space is divided into square cells such as S2 geometry provided by Google can be applied. Each cell in the grid system is assigned unique address information. For example, in H3, as shown in FIG. 8, address information that combines unique numbers along the i-axis, j-axis, and k-axis is assigned to each cell. The information regarding the location such as the address of the job seeker and the workplace used in the employment management system 100 is expressed by the address information of the cell corresponding to the location.

[0035] As shown in Fig. 9, the performance database 64 stores, in association with one another, a job seeker ID, a job offer ID, an employer ID, employment conditions presented by an employer to a job seeker, whether or not the job seeker agrees to the employment conditions, work arrival time, work departure time, salary to be paid, etc. The performance database 64 is registered based on the employment conditions presented by the employer when a job seeker and an employer apply for a job offer and the application is accepted. In addition, the work arrival time and work departure time are registered when a job seeker actually arrives at work and leaves work.

[0036] The job seeker information database 60 also stores employer IDs indicating employers who have been registered by job seekers in the past as "favorite" employers (shops). Registration as a "favorite" can be made, for example, by displaying a "favorite registration button" on a web page that displays job information by employer, and allowing the job seeker to register the employer by clicking or tapping on the "favorite registration button." However, the method of registering as a "favorite" is not limited to this, and any method may be used as long as it allows the job seeker to specify and register an employer.

[0037] The job seeker information receiving unit 40 receives information about job seekers who wish to seek work from the job seeker terminal 106. The job seeker information receiving unit 40 receives information about job seekers entered from the job seeker terminal 106 used by the job seeker. The information about job seekers received by the job seeker information receiving unit 40 is stored in the job seeker information database 60. The job seeker information received by the job seeker information receiving unit 40 may be transmitted to the employer terminal 104 via the information and communications network 108.

[0038] The job information receiving unit 42 receives job information including employment conditions such as employment hours, rest periods, work location, wages (hourly wage, daily wage, etc.), premium wages, various allowances, wage payment date, work content, and reasons for dismissal from the employer terminal 104. The job information receiving unit 42 receives job information from the employer terminal 104 via the information and communications network 108. The job information receiving unit 42 also receives disclosure conditions that limit the recipients of the job advertisement from the employer terminal 104 via the information and communications network 108. The job information receiving unit 42 may transmit the job information received in accordance with the disclosure conditions to the job seeker terminal 106 via the information and communications network 108.

[0039] The job recommendation learning unit 44 uses machine learning to construct a job recommendation model for extracting information related to job searches recommended to job seekers. That is, as shown in FIG. 10, the job recommendation learning unit 44 inputs learning data 72 to LightGBM 70 and applies machine learning to construct a job recommendation model that outputs a predicted value of whether or not a job seeker will be interested in job information from an employer as output data 74. LightGBM 70 is an analysis algorithm based on a decision tree algorithm in machine learning, and is a data analysis method in the field called "supervised learning" that expresses a target variable from given data. The job recommendation model in this embodiment can also be constructed using a neural network instead of LightGBM 70.

[0040] The learning data 72 is a data set that associates a job seeker ID indicating a job seeker, a job offer ID, and information indicating features related to the employment of the job seeker, as shown in Fig. 11. Note that the learning data 72 may include additional information such as an employer ID indicating an employer in addition to the features.

[0041] The feature amount is information that represents the employment characteristics of each job seeker. Feature amount 1 is information that indicates whether or not the place of employment is one where the job seeker tends to work. The location is indicated by address information in a grid system. It is preferable that the learning data 72 includes at least feature amount 1.

[0042] Feature 2 is information indicating whether the job offer is for an industry or job that job seekers tend to work in. The industry may be any industry related to employment provided in the employment management system 100. The industry may be, for example, food and beverage, accommodation, retail, delivery, etc. The job (position) is set for each industry, and may be, for example, hall work, dishwashing work, and cooking work in the food and beverage industry, banquet staff and front desk work in the accommodation industry, cleaning work, cashier work, and stocking work in the retail industry, and inspection work, sorting work, picking work, packing work, and loading and unloading work in the delivery industry. However, the industry and job (position) are not limited to these, and may be any industry and job (position) that allows for an employment contract between a job seeker and an employer in the employment management system 100.

[0043] Feature 3 is information indicating whether the job offer is for days and times that the job seeker tends to work. Feature 4 is information indicating whether the job offer is for a remuneration range that the job seeker tends to work for. Feature 5 is information indicating whether the job offer is for working hours that the job seeker tends to work for. Feature 6 is information indicating whether the job offer is for additional information that the job seeker tends to work for. The additional information can be, for example, information on working conditions such as welcoming inexperienced people and freedom to wear your hairstyle. Feature 7 is information indicating the tendency for people of the same gender as the registered gender of the job seeker to work. Feature 8 is information indicating the tendency for people of the same age as the registered age of the job seeker to work.

[0044] The feature amount 9 is information indicating whether or not the job seeker showed interest in the job information. The feature amount 9 is, for example, information indicating whether or not the job seeker has registered the job information as a favorite. The feature amount 9 may also be, for example, information indicating whether or not the job seeker has actually worked for the job information. The feature amount 9 may also be, for example, information indicating whether or not the job seeker has viewed the job information. Whether or not the job seeker showed interest in the job information may be represented, for example, as 1 if the job seeker registered the job information as a favorite, and 0 if the job seeker did not register the job information. Also, for example, it may be represented as 1 if the job seeker actually worked, and 0 if the job seeker did not work. Also, for example, it may be represented as 1 if the job seeker actually viewed the job information, and 0 if the job seeker did not view the job information.

[0045] The learning data 72 preferably includes feature amount 2 to feature amount 9. However, it is not essential that the learning data 72 includes feature amount 2 to feature amount 9. For example, the learning data 72 may include a combination of any of feature amounts 2 to 9.

[0046] In order to avoid the inclusion of address information of job seekers affecting the output data, it is preferable that the learning data 72 does not include features indicating the address of job seekers, but this is not limited to the above.

[0047] It is preferable that the learning data 72 utilize information on past employment of job seekers in the employment management system 100. The learning data may also utilize information in which each feature amount is assumed for a virtual job seeker.

[0048] The training data 72 is input to LightGBM70, and machine learning is performed so that LightGBM70 outputs a predicted value of whether or not a job seeker will be interested in a job offer from an employer as output data 74. Specifically, for example, when the training data 72 is input to LightGBM70, the job recommendation model is trained so that the probability that a job seeker has registered a recommended job offer as a favorite is correctly output as output data 74. In addition, for example, when the training data 72 is input to LightGBM70, the job recommendation model is trained so that the probability that a job seeker actually worked for the recommended job offer is correctly output as output data 74. As a result, a job recommendation model is constructed that outputs the probability that a job seeker will be interested in job information as output data 74 in association with a job seeker ID indicating a job seeker and a job ID indicating job information, as shown in FIG. 12.

[0049] When actually recommending job information from an employer to a job seeker, the job recommendation processing unit 46 of the management server 102 associates the information provided as the job information from the employer with the job seeker ID indicating the job seeker and the job ID indicating the job information as features, as shown in Figure 13, and inputs them into the trained job recommendation model.

[0050] The features input as input data preferably include information indicating the place of work. The place is indicated by address information in a grid system. It is also preferable to include information on the industry and work for which the job is being offered. The industry and work are the industry and work input by the employer as the job information. It is also preferable to include information indicating the days of the week and time periods for the work included in the job information. It is also preferable to include information indicating the remuneration for employment. It is also preferable to include information indicating the working hours of the job. It is also preferable to include additional information regarding the job. The additional information is, for example, information on working conditions such as welcoming inexperienced people and freedom of hairstyle. It is also preferable to include information indicating gender conditions and age conditions for the job.

[0051] By inputting such input data into the job recommendation model, as shown in Figure 14, for each combination of a job seeker ID indicating a job seeker and a job ID indicating job information, the probability that the job seeker will be interested in a job offer by the employer is output as output data.

[0052] Figure 15 shows an example of a conventional employment management system that recommends job information by focusing on the job seeker's address, without considering the place of work where the job seeker tends to work. Even though the places where the job seeker actually works are concentrated in areas far from the job seeker's address, the job information recommended to the job seeker in the employment management system is concentrated in the vicinity of the job seeker's address. In other words, job information in areas where the job seeker is likely to actually work was not properly recommended.

[0053] 16 shows an example of job information being recommended to a job seeker taking into consideration the place of employment where the job seeker tends to work, in employment management system 100 of this embodiment. In employment management system 100, job information recommended to a job seeker is not only in the vicinity of the job seeker's address, but also appropriately recommended to the job seeker job information in areas away from the address where the job seeker tends to work.

[0054] When recommending job offers to a job seeker, the data in the output data may be sorted in descending order of the probability of interest for each job seeker ID of the job seeker, and a predetermined number of job offers may be recommended from the top. It is preferable that the job recommendation processing unit 46 of the management server 102 transmits information to the job seeker terminal 106 so that when job offers are viewed on the job seeker terminal 106 used by each job seeker, the job offers are displayed in descending order of the probability of interest to the job seeker. This allows the job seeker to preferentially view job offers that are likely to interest him or her using the job seeker terminal 106. This makes it possible to more effectively match job seekers with employers.

[0055] It should be noted that management server 102 may send a push notification of job information to job seeker terminal 106. For example, management server 102 may send a push notification of job information that the job seeker is likely to be interested in at a predetermined value or higher to job seeker terminal 106 used by each job seeker. This allows job seekers to quickly find out about job information that they are likely to be interested in using job seeker terminal 106. This also makes it possible to more effectively match job seekers with employers. It should be noted that whether or not to send a push notification of job information may be set according to the wishes of the job seeker or the employer. [Explanation of symbols]

[0056] 10 processing unit, 12 memory unit, 14 input unit, 16 output unit, 18 communication unit, 20 processing unit, 22 memory unit, 24 input unit, 26 output unit, 28 communication unit, 30 processing unit, 32 memory unit, 34 input unit, 36 output unit, 38 communication unit, 40 job seeker information reception unit, 42 job information reception unit, 44 job recommendation learning unit, 46 job recommendation processing unit, 60 job seeker information database, 62 job information database, 64 performance database, 70 LightGBM, 72 learning data, 74 output data, 100 employment management system, 102 management server, 104 employer terminal, 106 job seeker terminal, 108 information and communication network.

Claims

1. An employment management system that recommends job information to job seekers, a job recommendation model that has been machine-trained to output the probability that the job seeker will be interested in the job information as output data using learning data including job seeker information indicating a job seeker, job information, a feature that specifies a work location where the job seeker tends to work, and a feature that indicates whether the job seeker has shown an interest in the job information, and input data including a job seeker identifier indicating an actual job seeker and job information including a work location is input to the job recommendation model, which outputs the probability that the job seeker will be interested in the job information; An employment management system characterized in that the job information is displayed on a job seeker terminal used by the job seeker according to the probability that the job seeker shows interest in the job information.

2. The employment management system according to claim 1, An employment management system characterized in that the feature included in the learning data indicating whether the job seeker has shown interest is information indicating whether the job seeker has registered the job information as a favorite.

3. The employment management system according to claim 1, An employment management system characterized in that the feature included in the learning data indicating whether the job seeker showed interest is information indicating whether the job seeker actually worked for the job information.

4. The employment management system according to claim 1, An employment management system characterized in that the feature included in the learning data indicating whether the job seeker has shown interest is information indicating whether the job seeker has viewed the job information.

5. The employment management system according to any one of claims 1 to 4, An employment management system characterized in that, depending on the probability that the job seeker shows interest in the job information, the job information is preferentially displayed on the job seeker terminal used by the job seeker.

6. The employment management system according to claim 1, The employment management system is characterized in that the learning data further includes at least one of a feature indicating whether the job offer is in an industry or job that the job seeker tends to work in, a feature indicating whether the job offer is for a day or time that the job seeker tends to work, a feature indicating whether the job offer is in a remuneration range that the job seeker tends to work, a feature indicating whether the job offer is for working hours that the job seeker tends to work, a feature indicating whether the job offer is additional information that the job seeker tends to work, a feature indicating a tendency for people of the same gender as the gender registered by the job seeker to work, and a feature indicating a tendency for people of the same age as the age registered by the job seeker to work.

7. An employment management program that recommends job information to a job seeker, Computer, Using learning data including job seeker information indicating a job seeker, job information, features specifying a place of employment where the job seeker tends to work, and features indicating whether the job seeker has shown interest in the job information, the system functions as a job recommendation model trained by machine learning to output the probability that the job seeker will show interest in the job information as output data; By inputting input data including a job seeker identifier indicating an actual job seeker and job information including a work location into the job recommendation model, the job recommendation model is caused to output a probability that the job seeker will be interested in the job information, An employment management program that causes the computer to function in a manner that causes the job seeker to display the job information on a job seeker terminal used by the job seeker in accordance with the probability that the job seeker will be interested in the job information.

8. An employment management method for recommending job information to a job seeker, comprising: On the computer, A job recommendation model that has been machine-trained to output the probability that a job seeker will be interested in the job information as output data using learning data including job seeker information indicating a job seeker, job information, a feature that specifies a work location where the job seeker tends to work, and a feature that indicates whether the job seeker has shown an interest in the job information is input with input data including a job seeker identifier indicating an actual job seeker and job information including a work location, thereby causing the job recommendation model to output the probability that the job seeker will be interested in the job information, An employment management method characterized by causing the computer to process the job information on a job seeker terminal used by the job seeker in accordance with the probability that the job seeker will be interested in the job information.

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