Information processing device, method, program, and system

Abstract

To promote successful matching between job seekers and job offering companies.SOLUTION: An aspect of a program disclosed herein causes a computer to function as: means of acquiring job seeker information regarding a job seeker; means of acquiring offer information regarding an offer notified to the job seeker for employment or contracting of the job seeker by a job offering company; means of estimating the possibility that offers will be accepted by the job seeker on the basis of the job seeker information and the offer information; and means of outputting information based on a result of the estimation of the possibility that the job seeker will accept the offer.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, a method, a program, and a system. [Background technology]

[0002] Various technical ideas have been proposed regarding matching job seekers with companies offering jobs. Patent Document 1 discloses a technical idea that aims to match job seekers with a compatible work environment and improve the retention rate of employees after they are hired. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2023-054726 A Summary of the Invention [Problem to be solved by the invention]

[0004] The technical idea of ​​Patent Document 1 is to use a learning model that learns the correlation between personality test results and years of employment to extract job seekers who are likely to work for a specified number of years or more in the employer's organization.

[0005] When job seekers are searching for a new job, they ultimately consider the content of the offer notified to them by the company that is hiring and make a decision on whether or not to accept the offer. If the content of the offer is not attractive to the job seeker, or if the offer is notified at a bad time, the job seeker may not accept the offer. In this case, the costs that the company invested in the recruitment activity and the effort that the job seeker spent on the job search are wasted. Therefore, simply extracting job seekers who are suitable for the company that is hiring and introducing the two parties together may not be effective enough in promoting the establishment of a match between the job seeker and the company that is hiring.

[0006] The purpose of this disclosure is to facilitate matching between job seekers and companies offering jobs. [Means for solving the problem]

[0007] A program of one embodiment of the present disclosure causes a computer to function as: a means for acquiring job seeker information, which is information about a job seeker; a means for acquiring offer information regarding an offer that a recruiting company will notify a job seeker when hiring or entering into a contract with the job seeker; a means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information; and a means for outputting information based on the estimation result of the likelihood that the job seeker will accept the offer. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of an information processing system according to an embodiment of the present invention; [Diagram 2] FIG. 2 is a block diagram showing a configuration of a client device according to the present embodiment. [Diagram 3] FIG. 2 is a block diagram showing a configuration of a server according to the present embodiment. [Figure 4] FIG. 1 is an explanatory diagram of one aspect of the present embodiment. [Diagram 5] FIG. 2 is a diagram showing an overall flow of information processing according to the present embodiment. [Figure 6] 3 is a diagram illustrating an example of a data structure of job seeker information according to the embodiment. FIG. [Figure 7] 11A to 11C are diagrams illustrating examples of screens displayed in the information processing of the present embodiment. [Figure 8] 11A to 11C are diagrams illustrating examples of screens displayed in the information processing of the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In the drawings for explaining the embodiment, the same components are generally designated by the same reference numerals, and the repeated description will be omitted.

[0010] (1) Information Processing System Configuration The configuration of the information processing system will be described below. Fig. 1 is a block diagram showing the configuration of the information processing system according to the present embodiment.

[0011] As shown in FIG. 1, the information processing system 1 includes a client device 10 and a server 30. The client device 10 and the server 30 are connected via a network (eg, the Internet or an intranet) NW.

[0012] The server 30 is an example of an information processing device that provides the client device 10 with a response in response to a request sent from the client device 10. The server 30 is, for example, a server computer. The server 30 can manage a talent matching service (which can also be called a "talent matching platform") in which job seekers and recruiting companies participate. The talent matching service corresponds to a place that connects job seekers and recruiting companies. In this specification, a job seeker includes a person who is changing jobs or (re)looking for a job, a person who is interested in these activities, or a person who intends to seek work. For example, a job seeker can include a person who registers his / her information on the talent matching service or prepares to register (e.g., uploads a resume file or a curriculum vitae file, or inputs his / her information). Similarly, a recruiting company includes a corporation or individual who intends to hire. For example, a recruiting company can include a person who uses the talent matching service to carry out recruitment activities (e.g., sends scouting documents, registers or prepares to register job information, notifies an offer, etc.).

[0013] The client device 10 is an example of an information processing device that transmits a request to the server 30. The client device 10 is, for example, a smartphone, a tablet terminal, or a personal computer. The user of the client device 10 is a person who belongs to the company that is hiring (for example, a recruiting person at the company that is hiring). Here, the recruiting person at the company that is hiring is not limited to a person in the human resources department, and may be, for example, a person in a department that is looking to hire someone through the job offer.

[0014] Here, an example of the behavior of the server 30 with regard to the management of the human resources matching service will be described. Specifically, the server 30 makes the profile information provided by the job seeker viewable (for example, published anonymously and searchable) by, for example, the recruiting staff of the hiring company. The recruiting staff can create and send scouting documents to job seekers who are deemed suitable for their company. Alternatively, the server 30 publishes the job information provided by the hiring company in, for example, a state that can be viewed by job seekers. The job seeker can create a resume and apply for a job at a hiring company that he or she deems suitable for him or her. In this way, hiring companies and job seekers can be linked together.

[0015] (1-1) Client device configuration The configuration of the client device will now be described with reference to Fig. 2, which is a block diagram showing the configuration of the client device of this embodiment.

[0016] 2, the client device 10 includes a storage device 11, a processor 12, an input / output interface 13, and a communication interface 14. The client device 10 is connected to a display 21.

[0017] The storage device 11 is configured to store programs and data. The storage device 11 is, for example, a combination of a Read Only Memory (ROM), a Random Access Memory (RAM), and a storage (for example, a flash memory or a hard disk).

[0018] The programs include, for example, the following programs: ·OS (Operating System) programs · Programs for applications that process information (e.g. web browsers or dedicated applications)

[0019] The data includes, for example, the following data: Databases referenced in information processing Data obtained by performing information processing (i.e., the results of performing information processing)

[0020] The processor 12 is a computer that realizes the functions of the client device 10 by running a program stored in the storage device 11. The processor 12 is, for example, at least one of the following: ·CPU(Central Processing Unit) ·GPU(Graphic Processing Unit) ·ASIC(Application Specific Integrated Circuit) ·FPGA(Field Programmable Gate Array)

[0021] The input / output interface 13 is configured to obtain information (eg, a user's instruction) from an input device connected to the client device 10, and to output information (eg, an image) to an output device connected to the client device 10.

[0022] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display 21, a speaker, or a combination thereof.

[0023] The communication interface 14 is configured to control communications between the client device 10 and an external device (eg, a server 30).

[0024] The display 21 is configured to display an image (still image or moving image). The display 21 is, for example, a liquid crystal display or an organic EL display.

[0025] (1-2) Server configuration The configuration of the server will now be described with reference to Fig. 3, which is a block diagram showing the configuration of the server according to this embodiment.

[0026] As shown in FIG. 3, the server 30 includes a storage device 31, a processor 32, an input / output interface 33, and a communication interface .

[0027] The storage device 31 is configured to store programs and data, and is, for example, a combination of a ROM, a RAM, and a storage (for example, a flash memory or a hard disk).

[0028] The programs include, for example, the following programs: -OS programs Application programs that perform information processing

[0029] The data includes, for example, the following data: Databases referenced in information processing Results of information processing

[0030] The processor 32 is a computer that realizes the functions of the server 30 by starting a program stored in the storage device 31. The processor 32 is, for example, at least one of the following. ·CPU GPU ·ASIC FPGA

[0031] The input / output interface 33 is configured to obtain information (eg, a user's instruction) from an input device connected to the server 30, and to output information (eg, an image) to an output device connected to the server 30.

[0032] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display.

[0033] The communication interface 34 is configured to control communications between the server 30 and external devices (eg, the client device 10).

[0034] (2) One aspect of the embodiment An embodiment of the present invention will now be described with reference to Fig. 4, which is an explanatory diagram of an embodiment of the present invention.

[0035] As shown in Figure 4, a user US1, who corresponds to a recruiter at a company hiring, uses information processing system 1 to have the recruiting company check the validity of an offer that the recruiting company plans to notify to a job seeker (hereinafter referred to as the "target job seeker") that the recruiting company plans to hire (or enter into a contract such as a service agreement).

[0036] Specifically, user US1 operates client device 10 to input or specify information about the target job seeker (hereinafter referred to as "job seeker information"). Furthermore, user US1 operates client device 10 to input or specify information about the offer that the hiring company plans to notify the target job seeker (hereinafter referred to as "offer information"). Client device 10 transmits the job seeker information or information that can identify the job seeker information (e.g., a Uniform Resource Locator (URL), identification information, etc.) to server 30. Similarly, client device 10 transmits the offer information or information that can identify the offer information (e.g., a URL, identification information, etc.) to server 30.

[0037] The server 30 acquires job seeker information and offer information based on the information received from the client device 10. The server 30 acquires an estimation result of the possibility that the target job seeker will accept an offer from a hiring company by inputting model input information based on the job seeker information and the offer information into the acceptance possibility estimation model LM5.

[0038] The server 30 outputs an alert to the client device 10 when the acquired estimation result satisfies a predetermined condition (for example, when the likelihood indicated by the estimation result is equal to or less than a threshold). The client device 10 presents the alert received from the server 30 to the user US1. On the other hand, when the acquired estimation result does not satisfy the predetermined condition, the server 30 does not output an alert to the client device 10. Instead, the server 30 may output a message to the client device 10 that the current offer is deemed reasonable.

[0039] In this way, the server 30 can, if necessary, prompt the user US1 to reconsider the content and timing of the offer that the hiring company plans to notify the job seeker, thereby increasing the possibility that the job seeker will accept the offer from the hiring company and supporting the establishment of a match between the two parties (conclusion of an employment contract or a service contract). As a result, the effort that the job seeker expends in job search activities and the costs that the hiring company expends in recruiting activities can be reduced.

[0040] (3) Information processing The information processing of this embodiment will be described. Fig. 5 is a diagram showing an overall flow of the information processing of this embodiment. Fig. 6 is a diagram showing an example of the data structure of job seeker information of this embodiment. Fig. 7 is a diagram showing an example of a screen displayed in the information processing of this embodiment. Fig. 8 is a diagram showing an example of a screen displayed in the information processing of this embodiment.

[0041] The process of FIG. 5 may begin, for example, by the client device 10 accessing a talent matching service and receiving an instruction from a user (e.g., a recruiter at the hiring company) to begin checking the validity of an offer that the hiring company plans to notify a target job seeker.

[0042] As shown in FIG. 5, the server 30 acquires job seeker information (S130). Specifically, the server 30 receives job seeker information on the target job seeker or information that can identify the job seeker information from the client device 10. The server 30 acquires the job seeker information based on the received information.

[0043] As a first example, a user inputs, for example, by copying and pasting, job seeker information of a target job seeker into an object for accepting job seeker information arranged on a UI (User Interface) screen of the human resources matching service displayed on the display 21 of the client device 10. The client device 10 transmits the content input into this object to the server 30 as job seeker information.

[0044] As a second example, a user specifies information of a target job seeker on a UI screen of the talent matching service displayed on the display 21 of the client device 10. For example, in the talent matching service, job seeker information of the job seeker is registered by the job seeker so that the job seeker can be viewed, and the user (a person in charge at the recruiting company) can specify the job seeker information of a job seeker who is planned to be hired by the recruiting company (i.e., to submit an offer). Alternatively, if the talent matching service provided by the information processing system 1 also has a hiring management function, the user may specify information of a job seeker who is planned to be hired from information of job seekers who have applied for a job at the recruiting company, which is managed by the function. The client device 10 transmits information identifying the specified job seeker information (for example, a user ID identifying a job seeker corresponding to the specified job seeker information, or a URL at which the specified job seeker information can be viewed) to the server 30 as information that can identify the job seeker information.

[0045] As a third example, the server 30 may acquire job seeker information based on information accumulated in an external system by a job seeker using the external system. Specifically, the server 30 may acquire job seeker information from the external system using account information (e.g., account name, login information, or a combination thereof) of the job seeker in a service provided by the external system (hereinafter referred to as an "external service"). The server 30 may acquire job seeker information using an application programming interface (API) of the external service, or may acquire job seeker information by crawling a web page of the external service. The server 30 may acquire information on content posted by the job seeker (e.g., technical blog), log information representing the activity of the job seeker in an issue management service (e.g., GitHub), or information on a profile registered by the job seeker in an external service. The external service may include, but is not limited to, Qiita (registered trademark), Zenn (registered trademark), LinkedIn (registered trademark), note (registered trademark), Slide Share, or Speaker Deck.

[0046] As shown in Fig. 6, the job seeker information may include personal attribute information, career information, skill information, job-seeking intention information, and job-seeking activity status information. Note that the job seeker information may not include some or all of the elements shown in Fig. 6, and may include elements not shown in Fig. 6.

[0047] The personal attribute information is information about the personal attributes of the job seeker. As an example, the personal attribute information may include at least one of the job seeker's name, gender, age, place of residence, preference (e.g., whether in-house development or contract development is preferred), current annual income, strengths, or weaknesses.

[0048] The career information is information about the career of the job seeker. As an example, the career information may include at least one of the job type, job title, place of employment, work history (which may include, for example, the period of employment or an overview of projects experienced), or educational history of the job seeker.

[0049] The skill information is information about the skills of a job seeker. As an example, the skill information may include at least one of the job seeker's technical skills, business skills, skills, language skills (e.g., English skills), used technology (e.g., programming language used), aptitude test results, and qualifications. The skill information may also include at least one of information extracted from content posted by the job seeker (e.g., technical blog articles), information extracted from the job seeker's log information in the issue management service (e.g., information stored in the job seeker's repository), or an index (e.g., a statistic such as a standard deviation) that quantifies the job seeker's skills based on the content or log information.

[0050] The job-seeking intention information is information about the job seeker's intention to seek a job. As an example, the job-seeking intention information may include at least one of the strength of the desire to change jobs, the strength of the desire to quickly change jobs, what the job seeker wants to do in the future (specifically, desired job type, desired work, desired work location, desire for remote work, or desired career, etc., for the next job), what the job seeker does not want to do in the future, or desired income.

[0051] The job search status information is information about the status of a job seeker's job search. As an example, the job search status information may include at least one of the selection status of other companies to which the job seeker has applied, or company information of the other companies (e.g., company name, market capitalization, sales volume, business type, etc.).

[0052] Furthermore, the information that can identify the job seeker information may be a resume created by the target job seeker, or a memo recording what the target job seeker said during the selection process at the hiring company. In this case, the server 30 may extract text corresponding to, for example, personal attribute information, career information, skill information, job-seeking intention information, and job-seeking activity status information from the acquired information (document). A large-scale language model may be used for such extraction processing.

[0053] The job seeker information may include information that the user (the recruiter at the company offering the job) is not permitted to view. For example, job-seeking intention information and job-seeking activity status information may fall under information that is not permitted to be viewed by anyone other than the job seeker.

[0054] After step S130, the server 30 executes acquisition of offer information (S131). Specifically, the server 30 receives offer information or information capable of identifying the offer information from the client device 10. The server 30 acquires the offer information based on the received information.

[0055] As a first example, a user inputs information about an offer that the hiring company to which the user belongs plans to notify a target job seeker (for example, the treatment to be offered to the target job seeker, the timing of the offer notification, or a combination thereof) into an object for accepting offer information arranged on the UI screen of the human resources matching service displayed on the display 21 of the client device 10. The client device 10 transmits the content input into this object to the server 30 as offer information.

[0056] As a second example, the user specifies offer information for a target job seeker from a list of offer information corresponding to job seekers that the recruiting company to which the user belongs plans to hire, on the UI screen of the human resources matching service displayed on the display 21 of the client device 10. Such a list can be read by the client device 10 as a file in CSV format, for example. The client device 10 transmits the specified offer information to the server 30.

[0057] The server 30 may execute step S130 after step S131, or may execute both simultaneously.

[0058] The offer information may include at least one of the following: Information regarding the benefits (e.g. salary) expected for the job applicant after employment Information about when the offer will be communicated

[0059] The information regarding the timing of the offer notification may include information regarding the length of the period (lead time) from the base date to the date on which the offer is notified. Here, the base date is the date on which a specific event occurs related to the job seeker's job search activities. Examples of base dates are shown below, but base dates not exemplified here may also be used. The date on which the job seeker applied for a job at the company to which the user belongs The date on which the job seeker underwent selection (e.g. written test, first interview, or final interview) at the company to which the user belongs The date on which the job seeker was notified of an offer or selection result from another company (first or last) The date on which the job seeker applied for a job at another company (first or last) The date on which the job seeker was first or last selected by another company The date on which the job seeker started job hunting

[0060] After step S131, the server 30 performs an estimate of the offer acceptability (S132). Specifically, the server 30 estimates the possibility that the target job seeker will accept the offer, based on the job seeker information acquired in step S130 and the offer information acquired in step S131.

[0061] As an example, the server 30 estimates the likelihood that the target person will accept the offer based on information output by the acceptance likelihood estimation model LM5 in response to model input information. The model input information includes feature amounts based on the job seeker information and the offer information. The feature amounts can be represented by vectors consisting of multiple numerical values.

[0062] The acceptability estimation model LM5 can be constructed by supervised learning. The learning data used in supervised learning is collected from job seeker information of job seekers to whom the same or different recruiting companies have decided to notify an offer in the past, offer information of the offer notified by the recruiting company, and the track record of whether the job seeker accepted the offer. The learning data includes learning features and corresponding correct answer data. The acceptability estimation model LM5 is trained to infer correct answer data corresponding to the learning features using a decision tree, a neural network, a Light Gradient Boosting Machine (LGBM), logistic regression, or the like. The correct answer data is information on whether the job seeker has accepted the offer. The learning features can be extracted from the corresponding job seeker information and offer information.

[0063] The acceptability estimation model LM5 may be at least partially configured by a decision tree structure, a neural network structure, or a combination thereof. In general, a decision tree structure has an advantage of low learning and operation load. On the other hand, a neural network structure has an advantage of being easy to improve the accuracy of inference, although it has a high learning and operation load.

[0064] If the estimation result obtained in step S132 indicates that the target job seeker is less than or equal to a threshold value, the server 30 outputs an alert (S133). Specifically, the server 30 outputs an alert to the hiring company to urge them to reconsider the offer as information based on the estimation result obtained in step S132. The alert may include information to urge the hiring company to change at least one of the contents of the offer or the timing of the notification. As an example, the alert may include information to urge the hiring company to at least one of increase the salary (which may include remuneration) offered to the target job seeker, or to advance or delay the date of the offer notification.

[0065] On the other hand, the alert may not include information indicating the recommended amount of change (i.e., how much the salary should be increased) in the salary offered to the target job seeker. Also, the alert may not include a numerical value indicating the likelihood that the target job seeker will accept the offer, as indicated by the estimation result obtained in step S132.

[0066] As an example, the server 30 presents the alert to the user via the client device 10. That is, the server 30 transmits the alert to the client device 10. The client device 10 displays the received alert on the display 21. For example, the client device 10 may display the screen of FIG. 7 on the display 21.

[0067] The screen of FIG. 7 includes an object J20. Object J20 displays the contents of the alert. In the example of Figure 7, the alert contains the following information: A message to the employer informing them that the job seeker is unlikely to accept the current offer Messages encouraging employers to increase the salary offered to targeted job seekers and / or to advance the date of the offer

[0068] The alert may be presented on an app screen or a website screen, or may be presented by email or other messages (e.g., Social Networking Service (SNS) messages, Short Message Service (SMS) messages, etc.). The presentation of the alert may include, for example, a notice by posting a message on an electronic bulletin board, a chat tool, or an SNS in a format viewable by the user (and further by a legitimate authority such as the user's superior). Furthermore, the output of the alert information may include provision as a file in, for example, CSV format.

[0069] If the estimation result obtained in step S132 indicates that the target job seeker is likely to accept the offer, and this probability exceeds a threshold, the server 30 skips outputting the alert (S133) and ends the information processing of FIG.

[0070] As an option, the server 30 may transmit a message to the client device 10, as information based on the estimation result obtained in step S132, informing the hiring company that the current offer is estimated to be appropriate. However, the server 30 may not include in the output information a numerical value indicating the likelihood that the target job seeker will accept the offer, as indicated by the estimation result obtained in step S132. The client device 10 displays the received information on the display 21. For example, the client device 10 may display the screen of FIG. 8 on the display 21.

[0071] The screen of FIG. 8 includes an object J30. Object J30 contains a message conveying that the current offer is presumed to be reasonable.

[0072] (5) Summary As described above, the server 30 of this embodiment acquires job seeker information, which is information about a job seeker, and acquires offer information about an offer that a hiring company will notify the job seeker of when hiring the job seeker or entering into a contract with the job seeker. The server 30 estimates the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information, and outputs information based on the estimated result of the likelihood that the job seeker will accept the offer. This encourages the hiring company to reconsider the offer as necessary, so that the job seeker is notified of an offer that is more likely to be acceptable, making it easier for a match to be made. As a result, the effort that the job seeker expends in job search activities and the costs that the hiring company incurs in recruitment activities can be reduced.

[0073] The server 30 may estimate the possibility that the job seeker will accept the offer based on information output by the acceptance possibility estimation model LM5, which is a trained model, in response to model input information based on the job seeker information and the offer information. This enables the server 30 to reasonably estimate the possibility that the job seeker will accept the offer.

[0074] At least a part of the trained model may be configured as at least one of a decision tree structure and a neural network structure, which allows the server 30 to reasonably estimate the likelihood that a job seeker will accept an offer.

[0075] The server 30 may output an alert to the hiring company when the likelihood indicated by the estimated result is equal to or less than a threshold value. This allows the hiring company to recognize that the current offer is unlikely to be accepted by the job seeker, and strongly urges the hiring company to reconsider the offer.

[0076] The alert may include information that prompts the recruiting company to modify the content and / or timing of the offer, thereby directing the offer to be refined so that it is more likely to be accepted by the job seeker.

[0077] The alert may include information prompting the recruiting company to increase the salary offered to the job seeker and / or to advance or delay the date on which the offer is communicated, thereby allowing the company to refine the offer so that it is more likely to be accepted by the job seeker.

[0078] The alert may not include information indicating the amount of a recommended change in the salary offered to the job seeker. This allows a recruiting company to consider increasing the salary offered to avoid the job seeker not accepting the offer, and since no guideline amount information is provided, the job seeker is more likely to be offered a salary higher than expected, making it easier to match the job seeker.

[0079] The server 30 does not have to present a numerical value representing the possibility to the hiring company. In this way, if a hiring company wants to avoid a situation in which a job seeker does not accept an offer, the hiring company is induced to actively improve the offer because no information is presented that quantitatively represents the possibility that the current offer will be accepted. As a result, the job seeker is more likely to be notified of a more favorable offer, making it easier to achieve a match.

[0080] The offer information may include the length of time from the reference date to the date of the offer notification, which allows a reasonable estimation of the likelihood that the job seeker will accept the offer based on the length of the lead time from the reference date to the offer notification.

[0081] The reference date may be the date on which a predetermined event related to the job seeker's job search occurs, which allows a reasonable estimation of the likelihood that the job seeker will accept the offer based on the length of the lead time from the date on which the predetermined event related to the job seeker's job search occurs to the notification of the offer.

[0082] The job seeker information may include information on at least one of the job seeker's personal attributes, career history, skills, preferences, job-seeking intentions, or job-seeking activity status, which allows a reasonable estimation of the likelihood that the job seeker will accept the offer based on the information on at least one of the job seeker's personal attributes, career history, skills, preferences, job-seeking intentions, or job-seeking activity status.

[0083] The job seeker information may include information on the job seeker's job search activity status, and the information on the job search activity status may include at least one of the selection status at other companies to which the job seeker has applied and the company information of those other companies. This makes it possible to reasonably estimate the possibility that the job seeker will accept an offer based on the information on the job seeker's job search activity status.

[0084] (6) Other modifications The storage device 11 may be connected to the client device 10 via a network NW. The display 21 may be integrated with the client device 10. The storage device 31 may be connected to the server 30 via the network NW.

[0085] Each step of the above information processing can be executed by either the client device 10 or the server 30. In addition, in the above description, an example in which each step in the information processing is executed in a specific order has been shown, but the execution order of each step is not limited to the example described above as long as there is no dependency between the steps.

[0086] The server 30 may accumulate the offer information acquired from the client device 10 as a database. In addition, when a recruiting company changes its offer, the client device 10 may transmit the changed offer information to the server 30, and the server 30 may update the offer information before the change stored in the above-mentioned database with the changed offer information. Furthermore, the server 30 may acquire information indicating whether or not the target job seeker has accepted the offer from the client device 10 or another information source (e.g., a terminal used by the target job seeker), and store the information in the above-mentioned database in association with the corresponding offer information. The server 30 may use the offer information recorded in such a database and the result of whether or not the offer has been accepted as learning data to train (which may include transfer learning or fine tuning) the acceptability estimation model LM5.

[0087] The number of times a user's offer to the same job seeker can be checked for validity may be limited, which discourages users from making small improvements to their offer and repeatedly checking its validity, resulting in minimal improvement of the offer.

[0088] (7) Additional Notes The matters described in the embodiment and the modified examples are supplemented below.

[0089] (Appendix 1) A computer (30), A means for acquiring job seeker information, which is information about job seekers (S130); A means for acquiring offer information regarding an offer to be notified to a job seeker by a recruiting company when the recruiting company employs the job seeker or enters into a contract with the job seeker (S131); A means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information (S132); A means for outputting information based on the result of estimating the possibility that the job seeker will accept the offer (S133); A program that functions as a

[0090] (Appendix 2) The estimation means estimates the likelihood that the job seeker will accept the offer based on information output by an estimation model, which is a trained model, in response to model input information based on job seeker information and offer information; 2. The program described in Appendix 1.

[0091] (Appendix 3) At least a part of the trained model is configured with at least one of a decision tree structure and a neural network structure. 2. The program described in Appendix 2.

[0092] (Appendix 4) The means for outputting information based on the estimation result outputs an alert for the company hiring when the possibility indicated by the estimation result is equal to or less than a threshold. 2. The program described in Appendix 1.

[0093] (Appendix 5) The alert may contain information that may prompt the employer to change the content and / or timing of the offer. 5. The program described in Appendix 4.

[0094] (Appendix 6) The alert contains information that prompts the employer to increase the salary offered to the job seeker and / or to advance or delay the date of the offer; 6. The program described in Appendix 5.

[0095] (Appendix 7) The alert does not include any information indicating the amount of the recommended change to the salary offered to the job seeker; 6. The program described in Appendix 5.

[0096] (Appendix 8) The means of outputting information based on the estimation results does not present a numerical value representing the possibility to the job-seeking company. 2. The program described in Appendix 1.

[0097] (Appendix 9) The offer information includes the length of the period from the base date to the date of announcement of the offer; 2. The program described in Appendix 1.

[0098] (Appendix 10) The reference date is the date on which a specific event occurred related to the job seeker's job search activities. 9. The program described in Appendix 9.

[0099] (Appendix 11) The job seeker information includes information on at least one of the job seeker's personal attributes, career history, skills, preferences, job-seeking intentions, or job-seeking activity status; 2. The program described in Appendix 1.

[0100] (Appendix 12) The job seeker information includes information regarding the job seeker's job search activity status, The information regarding the job search status includes at least one of the selection status of other companies to which the job seeker has applied and the company information of those other companies. 2. The program described in Appendix 1.

[0101] (Appendix 13) A computer (30) A step of acquiring job seeker information (S130), which is information related to a job seeker; A step (S131) ​​of a recruiting company acquiring offer information regarding an offer to be notified to a job seeker when hiring the job seeker or entering into a contract with the job seeker; A step of estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information (S132); A step of outputting information based on the estimated result of the likelihood that the job seeker will accept the offer (S133); How to do it.

[0102] (Appendix 14) A means for acquiring job seeker information, which is information about job seekers (S130); A means for acquiring offer information regarding an offer that a recruiting company will notify a job seeker when hiring the job seeker or entering into a contract with the job seeker (S131); A means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information (S132); A means for outputting information based on the result of estimating the possibility that the job seeker will accept the offer (S133); An information processing device (30) comprising:

[0103] (Appendix 15) A system (1) including a plurality of information processing devices (10, 30), The system is A means for acquiring job seeker information, which is information about job seekers (S130); A means for acquiring offer information regarding an offer that a recruiting company will notify a job seeker when hiring the job seeker or entering into a contract with the job seeker (S131); A means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information (S132); A means for outputting information based on the result of estimating the possibility that the job seeker will accept the offer (S133); A system comprising:

[0104] Although the embodiment of the present invention has been described in detail above, the scope of the present invention is not limited to the above embodiment. Furthermore, the above embodiment can be improved or modified in various ways without departing from the spirit of the present invention. Furthermore, the above embodiment and the modified examples can be combined. [Explanation of symbols]

[0105] 1: Information processing system 10: Client device 11:Storage device 12: Processor 13: Input / Output Interface 14: Communication interface 21: Display 30: Server 31: Storage device 32 : Processor 33: Input / Output Interface 34: Communication interface

Claims

1. Computer, A means for acquiring job seeker information, which is information about job seekers; A means for acquiring offer information regarding an offer that a recruiting company will notify the job seeker when hiring the job seeker or entering into a contract with the job seeker; means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information; means for outputting information based on the result of estimating the likelihood that the job seeker will accept the offer; A program that functions as a

2. the estimating means estimates the likelihood that the job seeker will accept the offer based on information output by an estimation model, which is a trained model, in response to model input information based on the job seeker information and the offer information; The program according to claim 1.

3. At least a part of the estimation model is configured with at least one of a decision tree structure or a neural network structure. The program according to claim 2.

4. The means for outputting information based on the estimation result outputs an alert for the company hiring when the possibility indicated by the estimation result is equal to or less than a threshold. The program according to claim 1.

5. The alert includes information that prompts the recruiting company to change at least one of the content or notification timing of the offer; The program according to claim 4.

6. the alert includes information prompting the recruiting company to at least one of increase the salary offered to the job seeker and / or advance or delay the date of the notice of the offer; The program according to claim 5.

7. the alert does not include information indicating a recommended amount of change in salary offered to the job seeker; The program according to claim 5.

8. The means for outputting information based on the estimation result does not present a numerical value representing the possibility to the hiring company. The program according to claim 1.

9. The offer information includes a length of time from a reference date to a date on which the offer is notified. The program according to claim 1.

10. The reference date is a date on which a predetermined event related to the job seeker's job search activity occurs. The program according to claim 9.

11. The job seeker information includes information regarding at least one of the job seeker's personal attributes, career history, skills, preferences, job-seeking intentions, or job-seeking activity status. The program according to claim 1.

12. The job seeker information includes information regarding the job seeker's job search activity status, The information regarding the job search activity status includes at least one of the selection status of other companies to which the job seeker has applied or the company information of those other companies; The program according to claim 1.

13. The computer acquiring job seeker information, which is information about a job seeker; A step of acquiring offer information regarding an offer to be notified to the job seeker by a recruiting company when employing the job seeker or entering into a contract with the job seeker; estimating a likelihood that the job seeker will accept the offer based on the job seeker information and the offer information; outputting information based on the estimated result of the likelihood that the job seeker will accept the offer; How to do it.

14. A means for acquiring job seeker information, which is information about job seekers; A means for acquiring offer information regarding an offer that a recruiting company will notify the job seeker when hiring the job seeker or entering into a contract with the job seeker; means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information; means for outputting information based on the result of estimating the likelihood that the job seeker will accept the offer; An information processing device comprising:

15. A system including a plurality of information processing devices, The system comprises: A means for acquiring job seeker information, which is information about job seekers; A means for acquiring offer information regarding an offer that a recruiting company will notify the job seeker when hiring the job seeker or entering into a contract with the job seeker; means for estimating the likelihood that the job seeker will accept the offer based on the job seeker information and the offer information; means for outputting information based on the result of estimating the likelihood that the job seeker will accept the offer; A system comprising:

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