Matching system, computing device and method

Abstract

A matching system (1) for providing an advertisement matching each of a plurality of groups including an enterprise is provided with: a plurality of user devices (500); and a computing device (100) that communicates with each of a plurality of user devices (500) including a first user device operated by a user belonging to a first group and a second user device operated by a user belonging to a second group, the computing device (100) being capable of accessing the database (120). Group information capable of specifying each of a plurality of groups, a plurality of pieces of advertisement information, and prohibition information capable of specifying, from among the plurality of pieces of advertisement information, advertisement information that prohibits association with a user belonging to the first group are registered in a database (120). A computing device (100) associates one or more pieces of advertisement information among a plurality of pieces of advertisement information with users belonging to a first group, and issues the one or more pieces of advertisement information to a first user device on the basis of the association. The computing device (100) associates the advertisement information with the user belonging to the first group after excluding the advertisement information identified by the prohibition information.

Description

Technical Field

[0001] The present disclosure relates to a matching system, a computing device, and a method for providing an advertisement matched with each of a plurality of groups including businesses. Background Art

[0002] Generally, there is an advertising technology that displays advertisements estimated to suit a user's preferences on the screen of a web page browsed by the user. In this advertising technology, user preferences are estimated based on various data, and product and service information corresponding to the estimated results is provided to the user as an advertisement.

[0003] Patent Document 1 describes a method for determining the content of an advertisement using rules set based on personal information, and a method for determining the content of an advertisement using rules set based on the assumption that people with similar interests and preferences have similar behavioral characteristics.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2004-021810 Summary of the Invention

[0007] Problems to be solved by the invention

[0008] Consider building platforms for resource sharing and information provision by connecting various groups, such as businesses, using the internet. By participating as users on such platforms, businesses can enjoy benefits that are consistent with the platform's purpose and cannot be achieved through a single company.

[0009] Companies can also use the platform to advertise their own products to other companies whose products are considered effective. It is believed that the greater the number of users participating in the platform and the larger the platform's scale, the greater the advertising effectiveness. This allows companies to effectively advertise to multiple other companies among platform users who are considered to have high praise for their products.

[0010] However, there is a possibility that other companies that highly praise our products may include competitors. This possibility increases particularly as the platform scales. Proactively providing our advertising to competitors is undesirable and should not be done in the first place.

[0011] The present disclosure has been made to solve the above-mentioned problems, and an object of the present disclosure is to effectively provide advertisements from a group such as a company to other groups while limiting the provision of advertisements to competing groups.

[0012] Solutions for solving problems

[0013] The matching system involved in the first aspect of the present disclosure provides advertisements matched with each of a plurality of groups including an enterprise, and the matching system comprises: a plurality of user devices; and a computing device, which communicates with each of the plurality of user devices and can access a database, wherein the plurality of user devices includes a first user device operated by a user belonging to a first group, and the database contains group information capable of determining each of the plurality of groups, a plurality of advertising information, and prohibition information capable of determining the advertising information in the plurality of advertising information that prohibits the advertising information from being matched with the user belonging to the first group. The computing device establishes a correspondence between one or more of the plurality of advertising information and the user belonging to the first group, and based on the established correspondence, publishes the one or more advertising information to the first user device, and the computing device excludes the advertising information determined by the prohibition information and then establishes a correspondence between the advertising information and the user belonging to the first group.

[0014] The computing device involved in the second aspect of the present disclosure is included in a matching system for providing advertisements matched with each group of multiple groups including an enterprise, and the computing device has: a communication interface, which communicates with multiple user devices including a first user device operated by a user belonging to a first group; and a processor, which accesses a database, wherein group information capable of determining each of the multiple groups, multiple advertising information, and prohibition information capable of determining the advertising information in the multiple advertising information that is prohibited from being established with the user belonging to the first group are registered in the database, the processor establishes a correspondence between one or more of the multiple advertising information and the user belonging to the first group, publishes one or more of the advertising information to the first user device, and the processor establishes a correspondence between the advertising information and the user belonging to the first group after excluding the advertising information determined by the prohibition information.

[0015] The method involved in the third aspect of the present disclosure is a method for providing advertisements that match each of a plurality of groups including an enterprise, the method comprising the following steps: communicating with a plurality of user devices including a first user device operated by a user belonging to a first group; accessing a database that registers group information of each of the plurality of groups capable of determining a plurality of groups, a plurality of advertisement information, and prohibition information capable of determining an advertisement information in the plurality of advertisement information that is prohibited from establishing a correspondence with the user belonging to the first group; establishing a correspondence between one or more advertisement information in the plurality of advertisement information and the user belonging to the first group, publishing one or more advertisement information to the first user device; and establishing a correspondence between the advertisement information and the user belonging to the first group after excluding the advertisement information determined by the prohibition information.

[0016] Effects of the Invention

[0017] According to the present disclosure, advertisements can be efficiently provided from a group such as a company to other groups, and advertisement provision to competing groups can be restricted. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a block diagram showing an overview of a matching system.

[0019] Figure 2 This is a block diagram showing the configuration of a shared server, a recruiter device, and an applicant device.

[0020] Figure 3 This is a diagram showing an example of a corporate database.

[0021] Figure 4 This is a diagram showing an example of a member database.

[0022] Figure 5 This is a diagram showing an example of a community database.

[0023] Figure 6 This is a diagram showing an example of a recruitment case database.

[0024] Figure 7 This is a diagram showing an example of a side job database.

[0025] Figure 8 This is a diagram showing an example of an evaluation input database.

[0026] Figure 9 This is a diagram showing an example of an evaluation summary database.

[0027] Figure 10 This is a diagram for explaining the functions of a shared server, a recruiter device, and an applicant device.

[0028] Figure 11 This is a diagram for explaining the functions of a shared server, a recruiter device, and an applicant device.

[0029] Figure 12 This is a diagram for explaining the functions of a shared server, a recruiter device, and an applicant device.

[0030] Figure 13 This is a diagram for further explaining the functions of the applicant device.

[0031] Figure 14 This is a diagram for explaining the process of registering a recruitment case in the recruitment case database.

[0032] Figure 15 This is a diagram for explaining the process of retrieving recruitment cases from a database.

[0033] Figure 16This diagram explains the process of registering side job plans and performance in a database.

[0034] Figure 17 This is a diagram for explaining the process of registering evaluations of applicants in a database.

[0035] Figure 18 This is a diagram for explaining the process of registering evaluations of applicants in a database.

[0036] Figure 19 This is a diagram for explaining a process of displaying applicant evaluations and member search results on a display.

[0037] Figure 20 This is a diagram for explaining the process of displaying evaluations of recruiters and member search results on a display.

[0038] Figure 21 This is a diagram for explaining the browsable range of the evaluation summary database.

[0039] Figure 22 This is a diagram showing an example of setting a disclosure range according to a disclosure level.

[0040] Figure 23 This figure shows a screen displayed on the applicant's device when the manager (the applicant's supervisor) checks the status of the subordinate's side job.

[0041] Figure 24 This is a diagram showing details of the case contents included in the recruitment case database.

[0042] Figure 25 This is a diagram showing an overview of the advertisement distribution function included in the matching system.

[0043] Figure 26 FIG. 1 is a diagram showing an example of a profile database and a behavior history database.

[0044] Figure 27 This is a diagram showing an example of an advertisement database.

[0045] Figure 28 This is a diagram showing an example of a priority database.

[0046] Figure 29 1 is a flowchart illustrating a processing procedure related to an advertisement distribution function of a matching system.

[0047] Figure 30 This is a flowchart showing the processing procedure of the advertisement information registration unit.

[0048] Figure 31 : is a flowchart showing the processing procedure of the user information acquisition unit.

[0049] Figure 32 is a flowchart showing the processing procedure of the content algorithm.

[0050] Figure 33 is a flowchart showing the processing procedure of the collaborative algorithm.

[0051] Figure 34 Flowchart showing the processing procedure of the decision algorithm.

[0052] Figure 35 This is a flowchart showing the processing procedure of the advertisement information acquisition unit.

[0053] Figure 36 This is a flowchart showing the processing procedure of the display unit.

[0054] Figure 37 This is a flowchart showing the processing procedure of the advertisement result feedback unit.

[0055] Figure 38 This is a flowchart showing the processing procedure of the learning unit.

[0056] Figure 39 This is a diagram for explaining the functions of the shared server, recruiter device, and applicant device according to Modification 1.

[0057] Figure 40 This is a diagram showing an example of a member database according to Modification 1.

[0058] Figure 41 This is a flowchart showing the processing procedure of reverse invitation member search processing according to Modification 1.

[0059] Figure 42 This is a block diagram showing the configuration of a shared server, a recruiter device, and an applicant device according to Modification 2.

[0060] Figure 43 This is a diagram showing an example of a member group database according to Modification 2.

[0061] Figure 44 This is a diagram showing an example of a recruitment case database according to Modification 2.

[0062] Figure 45 This is a diagram for explaining the functions of a shared server, a recruiter device, and an applicant device according to Modification 2.

[0063] Figure 46 This is a diagram for explaining a process of registering a recruitment case according to Modification 2 in the recruitment case database. DETAILED DESCRIPTION

[0064] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the drawings, identical or corresponding parts are denoted by identical reference numerals, and their description will not be repeated.

[0065] [Background of Proposing Matching System 1]

[0066] Figure 1 1 is a block diagram showing an overview of the matching system 1 according to the present embodiment. First, the background of proposing the matching system 1 in the present embodiment will be described.

[0067] The matching system 1 is used, for example, for crowdsourcing between businesses. Crowdsourcing is generally a process of recruiting an unspecified number of people to contribute to obtaining a desired service, idea, or content.

[0068] Many companies are promoting side businesses to effectively utilize their human resources. By leveraging crowdsourcing across companies, the capabilities of their employees can be utilized.

[0069] However, when general crowdsourcing methods are directly applied between companies, the following problems may arise.

[0070] [Possibility of confidential information being leaked]

[0071] Conventional crowdsourcing methods don't consider the relationship between the order-issuing and order-receiving companies. Therefore, crowdsourcing carries both corporate and personal risks. For example, confidential information could be leaked to a competing company through an employee's side hustle. Conventional crowdsourcing methods also made it impossible for managers to verify that employees weren't taking on competing companies as side jobs.

[0072] [Possibility of overwork]

[0073] If companies allow employees to work side jobs, their working hours may become excessive. To mitigate the risk of overwork, companies may consider setting a cap on overtime hours for both main and side jobs. However, if employees are free to take on side jobs, it will be difficult for companies to manage their side job hours. Consequently, employees may end up working too much.

[0074] [Possibility that the results of side jobs are not properly evaluated]

[0075] Conventionally, there are crowdsourcing systems that require orderers to evaluate order takers. By sharing appropriate evaluations from orderers in a crowdsourcing system, those recruiting order takers can refer to these evaluations and select highly qualified candidates from among the many people seeking to take on the work.

[0076] However, a business's order-giver might be overly concerned about the order-takers of other businesses being evaluated and enter a higher-than-original rating into the system. Alternatively, a business's order-giver might consider the possibility of inter-business relations deteriorating and avoid giving a lower rating to the order-takers of other businesses. Furthermore, a business's order-giver might fail to perceive the benefits of evaluation and enter a rating significantly different from its original rating into the system. Taking these factors into account can reduce the reliability of the ratings provided by the system. In such cases, even if the order-taker ratings are shared, the business's order-giver cannot use them as a reference when selecting an order-taker.

[0077] [Possibility of not being able to obtain accurate information about the recruiter]

[0078] In a crowdsourcing system such as the one described above, applicants who want to apply for a business being recruited will choose an acceptable business while referring to the content of the business, remuneration, etc. However, there may be recruiters who add commissions outside the scope of the contracted business and frequently instruct to change the content of the business. As an applicant, they will want to avoid applying for the business being recruited by such recruiters. On the contrary, there are recruiters who will not cause any problems until the business is completed. As an applicant, they will want to apply for the business recruited by such recruiters as long as possible. Therefore, it is expected that not only the evaluation of the applicants (order takers) but also the evaluation of the recruiters (order issuers) will be widely shared in the crowdsourcing system.

[0079] When appropriate evaluations of job seekers are shared in a crowdsourcing system, those who subsequently wish to apply for a job can refer to the evaluations and select a job they can accept from a large number of job offers while considering the job seeker's past transaction history.

[0080] However, when building an evaluation system that can evaluate recruiters, the same problems as when building an evaluation system that can evaluate order takers may also arise. That is, an order taker (applicant) of a certain company may be too concerned about the order issuers (recruiters) of other companies who are the evaluation objects and input an evaluation higher than the original evaluation into the system. In addition, an order taker (applicant) of a certain company may avoid making a lower evaluation of the order issuers (recruiters) of other companies considering the possibility of deterioration of relations between companies. Moreover, the order taker (applicant) may not feel the benefits of the evaluation and thus input an evaluation that is far from the original evaluation into the system. When these possibilities are taken into account, the reliability of the evaluation provided by the system may decrease. In this case, even if the evaluation of the recruiter is shared, the applicant will not be able to use the evaluation as reference data when selecting a recruiter.

[0081] [Regarding the particularity of setting the matching subject as a company]

[0082] Typically, matching talent with tasks across multiple companies requires close relationships, such as trust, between the companies involved. Consequently, matching talent with tasks across companies without a capital relationship is extremely difficult. Furthermore, large companies, such as listed companies, are prone to competing with other companies for multifaceted management, leading to cannibalization. This makes matching talent with tasks across a large number of companies difficult.

[0083] [Possibility of targeted advertising being delivered to competitors]

[0084] When a platform that provides crowdsourcing services to businesses is built, it becomes increasingly large as the number of participating businesses increases. Within this large platform, a network encompassing a variety of businesses is formed. Consider adding a mechanism to the platform that allows participating businesses to leverage this network to distribute targeted advertising to other participating businesses. Targeted advertising is delivered to targeted users based on analysis of user preferences, resulting in highly effective advertising. Therefore, by adding advertising functionality to the platform, advertisers can distribute advertisements for their products and services to representatives of other companies believed to be highly interested in those products and services.

[0085] However, there's a possibility that other companies that highly praise our products and services may include competitors. This possibility increases particularly as the platform scales. Proactively providing our advertising to competitors is not advisable. This is because advertisements may contain technical information related to a company's latest products.

[0086] Systems for delivering targeted advertising have mechanisms that determine where ads are delivered based on user attributes and actions. This mechanism can also be used to exclude competing companies from receiving targeted ads. However, with widespread adoption of social networking services (SNS), the possibility of users falsifying their attributes cannot be ruled out, and the resulting estimates are not always accurate.

[0087] If the estimation result is wrong, there is a possibility that an advertisement related to a new product exhibition, etc., which is not intended for the competitor to see, may be sent to the competitor. Therefore, it is not desirable to determine whether a user belongs to a competitor based on the user's attributes and actions obtained from the network.

[0088] In this embodiment, a matching system 1 described in detail below is proposed for the purpose of solving at least one of the aforementioned various problems existing in conventional crowdsourcing.

[0089] [Overall structure]

[0090] Reference Figure 1 The following describes a schematic configuration of the matching system 1. The matching system 1 includes a shared server 100, recruiter devices 200A, 200B, 200C, ..., and applicant devices 300A, 300B, 300C, ....

[0091] The shared server 100 provides a matching service for matching orders and receipts between businesses to multiple businesses. Figure 1 , Company A, Company B, Company C, etc. are shown as examples of companies using the matching service. Company A, Company B, Company C, etc. are registered as company members of the matching system 1. Employees of Company A, Company B, Company C, etc. who use the matching system 1 are also individually registered as members of the matching system 1.

[0092] The jobs introduced in matching system 1 are, for example, short-term jobs, intended to be completed within a predetermined period. Therefore, those who accept jobs introduced in matching system 1 are expected to engage in various jobs, focusing on their own specific department within the company as their primary occupation and using the jobs introduced in matching system 1 as a secondary occupation. Furthermore, in matching system 1, for example, applicants from company A can also accept jobs for company A. Therefore, matching system 1 also allows applicants from a different department, Y, within company A to accept jobs for company A's department X.

[0093] Hereinafter, a business that is recruiting order takers in the matching system 1 may be referred to as a "recruitment business" or a "recruitment case," a person who provides a recruitment case may be referred to as a "recruiter," and a person who responds to an order for a recruitment case may be referred to as a "recruiter." The situation of responding to a recruitment business may be referred to as a "recruitment business" or a "recruitment case."

[0094] The applicant in a case of receiving an order to recruit is equivalent to the "order-taker", and the recruiter in a case of issuing an order to the order-taker is equivalent to the "order-issuer". However, in the following text, the "order-taker" is sometimes included in the mainland and referred to as the "applicant", and the "order-issuer" is sometimes included in the mainland and referred to as the "recruiter".

[0095] A database 120 required for the matching service is built into shared server 100. Database 120 includes various databases that store information necessary for providing the matching service. For example, database 120 contains information about members and recruitment activities. Shared server 100 is managed and operated by a company separate from the companies utilizing the matching service. However, any company utilizing the matching service may manage and operate shared server 100.

[0096] Recruiter device 200A is operated by a manager of company A. Recruiter device 200B is operated by a manager of company B. Recruiter device 200C is operated by a manager of company C. Hereinafter, recruiter devices 200A, 200B, 200C, ... may be collectively referred to as "recruiter device 200".

[0097] Applicant device 300A is operated by an applicant of company A. Applicant device 300B is operated by an applicant of company B. Applicant device 300C is operated by an applicant of company C. Hereinafter, applicant devices 300A, 300B, 300C, etc. may be collectively referred to as "applicant devices 300". Figure 1 In the figure, two applicants are depicted for each company, but the number of applicants is not limited to this. There may be more applicants in each company, or there may be only one applicant in a company. The shared server 100 may also accept applicants who are not affiliated with the company, such as freelancers.

[0098] In this embodiment, the managers of Company A, Company B, Company C, etc., act as recruiters. Therefore, below, the managers of each company will sometimes be referred to as "recruiters." Recruiters can also act as applicants for jobs recruited by other recruiters. In this case, recruiter device 200 functions as applicant device 300. In this embodiment, when a company manager acts as a recruiter, the device used by that manager to utilize the matching service is referred to as recruiter device 200.

[0099] The manager of company A can be one person or multiple people. When a manager is assigned to company A, each manager can be provided with a recruiter device 200, or multiple people can share one recruiter device 200. The same applies to company B, company C, etc.

[0100] The shared server 100 and the recruiter device 200 are configured to be able to communicate via the Internet 50 , which is an example of a communication network. The shared server 100 and the applicant device 300 are configured to be able to communicate via the Internet 50 .

[0101] When accepting access from the recruiter's device 200, the shared server 100 requires login by entering a member ID and password. Similarly, when accepting access from the applicant's device 300, the shared server 100 requires login by entering a member ID and password. The shared server 100 identifies each recruiter and applicant based on the member ID notified during login.

[0102] The recruiter device 200 accepts various operations from the recruiter. For example, the recruiter device 200 accepts input of recruitment cases (commissioned tasks), input of evaluations of order takers who have completed tasks, and search for members of matching services.

[0103] The recruiter device 200 communicates with the shared server 100 in response to various operations on the recruiter device 200. The shared server 100 registers a recruitment case (commissioned work) in the database 120 in response to an operation to input a recruitment case, registers the evaluation of the target applicant (order taker) in the database 120 in response to an operation to input an evaluation, and provides member information to the recruiter device 200 in response to an operation to search for members.

[0104] The applicant device 300 accepts various operations from applicants. For example, the applicant device 300 accepts operations such as searching for recruitment cases, applying for recruitment cases, inputting work performance, and inputting evaluations of the applicant (orderer).

[0105] The applicant device 300 communicates with the shared server 100 in response to various operations performed on the applicant device 300. The shared server 100 provides the applicant device 300 with appropriate recruitment cases in response to the operation of searching for recruitment cases, issues a notification of acceptance or rejection to the applicant device 300 in response to the operation of applying for a recruitment case, registers the work results in the database 120 in response to the operation of inputting work results, and registers the evaluation of the target recruiter (order issuer) in the database 120 in response to the operation of inputting an evaluation.

[0106] As described above, the matching system 1 includes an evaluation system for evaluating job applicants (order takers) and job recruiters (order issuers), and a recruitment system for recruiting job order takers.

[0107] A recruiter in a department of Company A can recruit an applicant from another department of Company A as a job taker by using the matching system 1. A recruiter in Company A can recruit an applicant from Company B as a job taker by using the matching system 1.

[0108] Members using the matching system 1 access the shared server 100 as recruiters or applicants. Furthermore, members using the matching system 1 can also access the shared server 100 as advertisers. Hereinafter, members of the matching system 1 may be referred to as "users." Furthermore, the recruiter device 200 and applicant device 300 operated by a member may be collectively referred to as "user device 500."

[0109] An advertiser who is a user of the matching system 1 uploads advertisements related to their own products and services to the shared server 100. The advertiser uploads the advertisements to the shared server 100 using, for example, a user device 500.

[0110] Shared server 100 selects users who are believed to be highly interested in the content of the advertisement and distributes the advertisement to these users. In this way, shared server 100 utilizes a large platform built through the participation of multiple companies to distribute so-called targeted advertising. Database 120 of shared server 100 contains data that identifies competitive relationships between companies. Shared server 100 uses this data to prevent advertisers' ads from being distributed to competitors.

[0111] exist Figure 1 2 illustrates a screen 250 displayed on a recruiter's device 200 and a screen 350 displayed on an applicant's device 300. The recruiter views a list of applicants 251 displayed on screen 250 and selects an applicant to hire as an order-taker. At this time, an advertisement 252 targeting the recruiter is displayed on screen 250. The applicant views a list of available jobs 351 displayed on screen 350 and selects a job to apply for. At this time, an advertisement 252 targeting the recruiter is displayed on screen 250.

[0112] Figure 2 1 is a block diagram showing the configuration of the shared server 100 , the recruiter device 200 , and the applicant device 300 .

[0113] [Structure of Shared Server 100]

[0114] The shared server 100 includes a processor 101 , a memory 102 , a storage device 103 , and a communication interface 104 .

[0115] The memory 102 includes RAM (Random Access Memory), ROM (Read Only Memory), flash memory, or any other appropriate memory system. The memory 102 stores programs required for the calculation processing of the processor 101 and temporary data calculated during the calculation processing.

[0116] The storage device 103 is composed of a hard disk drive, a solid-state drive, or the like. A database 120 is stored in the storage device 103. The database 120 includes multiple databases. These include a company database (company DB) 121, a member database (member DB) 122, a community database (community DB) 123, a recruitment case database (recruitment case DB) 124, a sideline database (sideline DB) 125, an evaluation input database (evaluation input) 126, an evaluation summary database (evaluation summary DB) 127, and multiple other databases.

[0117] Alternatively, a portion of these various databases may be stored in a storage device that is separate from the shared server 100. For example, a cloud service outside the shared server 100 may be connected to store the database. Figure 2 Some of the various databases shown are stored on the cloud. In this case, the shared server 100 can access the required database by communicating with the cloud via the Internet 50.

[0118] The processor 101 is connected to the Internet 50 via the communication interface 104 in accordance with the program stored in the memory 102. The processor 101 is connected to the Internet 50 to communicate with the recruiter device 200 and the applicant device 300. The processor 101 accesses the database 120 and executes processes such as extracting required data, registering new data in the database 120, and updating data registered in the database 120.

[0119] [Structure of Recruiter Device 200]

[0120] The recruiter device 200 includes a processor 201, a memory 202, a communication interface 203, an input / output interface 204, a display 205, and an operation unit 206. The operation unit 206 is composed of a mouse, a keyboard, and the like.

[0121] The memory 202 includes RAM (Random Access Memory), ROM (Read Only Memory), flash memory, or any other appropriate memory system. The memory 202 stores programs required for the calculation processing of the processor 201 and temporary data calculated during the calculation processing.

[0122] Processor 201 connects to Internet 50 via communication interface 203 in accordance with a program stored in memory 202. Processor 201 connects to Internet 50 to communicate with shared server 100. Processor 201 communicates with shared server 100 to execute processes such as sending recruitment proposals, displaying information about applicant members on display 205, issuing orders to order takers selected from applicants, and sending evaluations of order takers entered by recruiters to shared server 100.

[0123] Information input by operating the operation unit 206 is notified to the processor 201 via the input / output interface 204 .

[0124] [Structure of Applicant Device 300]

[0125] The applicant device 300 includes a processor 301, a memory 302, a communication interface 303, an input / output interface 304, a display 305, and an operation unit 306. The operation unit 306 is composed of a mouse, a keyboard, and the like.

[0126] The memory 302 includes RAM (Random Access Memory), ROM (Read Only Memory), flash memory, or any other appropriate memory system. The memory 302 stores programs required for the calculation processing of the processor 301 and temporary data calculated during the calculation processing.

[0127] Processor 301 connects to Internet 50 via communication interface 303 in accordance with a program stored in memory 302. Processor 301 connects to Internet 50 to communicate with shared server 100. Processor 301 communicates with shared server 100 to perform tasks such as processing application recruitment cases, displaying notifications of acceptance or rejection of applied cases on display 305, transmitting actual results of accepted jobs to shared server 100, and transmitting evaluations of recruiters input by applicants to shared server 100.

[0128] Information input by operating the operation unit 306 is notified to the processor 301 via the input / output interface 304 .

[0129] [Overview of Database 120]

[0130] The following describes an overview of the database 120. The company database 121 contains information about companies that have joined the matching system 1. The member database 122 contains information about members who use the matching system 1. Most members are employees of companies that have joined the matching system 1.

[0131] Members registered in the member database 122 can act as recruiters (order issuers) or applicants (order takers) by using the matching system 1. Members may include not only employees of companies registered in the company database 121 but also individuals (freelancers) who do not belong to companies.

[0132] The community database 123 stores information identifying the companies that belong to a community. Communities are formed through agreements between companies. Therefore, multiple communities can be formed depending on the method of agreement between companies. The number of companies that belong to a community can also be set in various ways. Companies in a community form a trust relationship within the scope determined by the method of agreement reached when the community was formed. Information identifying the companies that belong to the community is registered for each community in the community database 123.

[0133] Jobs for recruiting order takers (recruitment cases) are registered in the recruitment case database 124. Employees of each company can, while working on their main business within their department, accept orders from other departments within their company or from other companies registered in the recruitment case database 124 as members of the matching system 1. In this case, members accept orders from other departments within their company or from other companies as a side job.

[0134] Data indicating the status of the side job is registered for each member in the side job database 125. The data indicating the status of the side job includes information such as the side job performance and the side job plan.

[0135] The evaluation input database 126 contains information on evaluations of applicants (order takers) and recruiters (order issuers). Recruiters (order issuers) use the matching system 1 to evaluate the work performance of applicants (order takers) who have completed their work. Applicants (order takers) use the matching system 1 to evaluate recruiters (order issuers). Each evaluator's evaluation is registered in the evaluation input database 126.

[0136] Evaluation summaries are registered in the evaluation summary database 127. Evaluation summaries are registered for each member in the evaluation summary database 127. Evaluation summaries include recruiter evaluation summaries and applicant evaluation summaries. Recruiter evaluation summaries indicate the level of evaluation of a member when acting as a recruiter (order issuer). Applicant evaluation summaries indicate the level of evaluation of a member when acting as an applicant (order taker). Recruiter evaluation summaries are generated based on applicants' evaluations of recruiters. Applicant evaluation summaries are generated based on recruiters' evaluations of applicants.

[0137] Members can browse the evaluation summary. Recruiters can browse the applicant evaluation summary of each member and select the member they think is suitable as the order taker. Applicants can browse the applicant evaluation summary of each member and apply for the job of the recruiter they think is suitable.

[0138] [Enterprise Database 121]

[0139] Figure 3 1 is a diagram showing an example of a company database 121. In the company database 121, the company ID, company name, company address, and side job upper limit time for identifying the company are registered for each company. The side job upper limit time is the upper limit time that employees are allowed to perform work as a side job in addition to their main job. The side job upper limit time is stipulated for each company. For example, the side job upper limit time can be calculated by "specified overtime time - overtime time of the main job other than the side job". "Specified overtime time" varies from company to company. In addition, Figure 3 In the example, the upper limit of the time for side jobs is shown in months, but it can also be set in weeks. The unit of the upper limit of the time for side jobs can also be specified for each company.

[0140] In this embodiment, members are allowed to apply for and receive orders for jobs offered by various companies and departments within a time limit not exceeding the upper limit of the side job period specified by the company to which the member belongs.

[0141] [Member Database 122]

[0142] Figure 4 1 is a diagram showing an example of the member database 122. Various member information is registered in the member database 122. The various member information includes a member ID for identifying the member, the ID of the company to which the member belongs, the member's name, the member's authority, the department to which the member belongs, and the time available for side jobs.

[0143] Member permissions include administrator and applicant. Members with administrator permissions are granted the ability to use the matching system 1 as both recruiters and applicants. Members with applicant permissions are granted the ability to use the matching system 1 as applicants, but not as recruiters. Managers within a company are granted administrator permissions to manage the side hustles of their subordinates. Managers with administrator permissions are granted the ability to approve applications from their subordinate applicants. Thus, managers function as approvers.

[0144] The time available for side jobs is the remaining time that can be used to engage in side jobs. The time available for side jobs is calculated by "side job upper limit time - total side job time". In the case where the subject is engaged in multiple side jobs, the total side job time includes the time already spent on these multiple side jobs. In addition to the time already spent on the side job, the total side job time also includes the estimated time for the side job. The estimated time for the side job is calculated based on the assumed working hours registered in the recruitment case database 124. Figure 4 The available time for side jobs is shown in units of months. Only jobs that can be handled within the available time for side jobs are provided as available jobs to applicants who search for job openings using the matching system 1 .

[0145] [Community Database 123]

[0146] Figure 5 This figure shows an example of a community database 123. Community database 123 registers information about communities formed between companies. This community information includes a community ID, a community name, and a list of IDs of companies belonging to the community. Companies can form various communities by reaching agreements with other companies. Companies belonging to a community can change the companies included in the community by reaching agreements with other companies.

[0147] [Recruitment Case Database 124]

[0148] Figure 6 This figure shows an example of the recruitment case database 124. Recruitment case information is registered in the recruitment case database 124. This recruitment case information includes a case ID for identifying the recruitment case, the ID of the company to which the recruiter who registered the recruitment case belongs, a list of non-public company IDs, a disclosure level, a case title, estimated duration, an estimated period, and the case details.

[0149] The IDs of companies that prohibit public recruitment are registered in the non-public company ID list. The disclosure level can be set to one of three levels: "Company," "Within the community," or "All." If the disclosure level is set to "All," applicants outside the community will also be disclosed.

[0150] exist Figure 6 The right side of the recruitment case database 124 shows the IDs of companies that can view recruitment cases. For example, for the recruitment case corresponding to case ID = 001, the disclosure level is set to "Our Company." In this case, only members of the company that registered the recruitment case (Company ID = 00A) can view the recruitment case corresponding to case ID = 001.

[0151] Hereinafter, the recruitment cases corresponding to each case ID may be referred to as Case 001, Case 002, Case 003, etc., using the case ID. Similarly, the communities corresponding to each community ID may be referred to as Community 01, Community 02, Community 03, etc., using the community ID, and the members corresponding to each member ID may be referred to as Member P1, Member P2, Member P3, etc., using the member ID. Furthermore, below, the companies corresponding to each company ID may be referred to as Company A, Company B, Company C, etc., using part of their company ID.

[0152] For case 002, the disclosure level is set to "within the community". Figure 5 In the community database 123 shown, the companies that have a community relationship with the company A registered in case 002 are company B and company C. Figure 6 As shown, only members belonging to any one of Company A, Company B, and Company C can browse Project 002.

[0153] The registered companies and disclosure levels of the recruitment case 003 are the same as those of case 002. However, for case 003, "00B" is registered in the private company ID list. Figure 6 As shown, only members belonging to either Company A or Company C can view Project 003 , and members belonging to Company B are not granted the right to view Project 003 .

[0154] In the case of a job posting whose disclosure level is set to "all", all members can browse the target job posting. Figure 6 This situation applies to the case 005 shown. If one or more company IDs are registered in the private company ID list of the case 005, members of the companies belonging to these company IDs are not given the right to view the case 005.

[0155] The assumed working hours and the assumed period are used by applicants and the matching system 1 to estimate the time required to process a recruitment case.

[0156] [Side Job Database 125]

[0157] Figure 7 This figure shows an example of the side job database 125. In the side job database 125, information indicating the status of a member's side job is registered for each side job case. This information includes the member's ID, case ID, month (period of side job), planned side job duration, actual side job duration, estimated side job duration, and progress rate.

[0158] The planned time for a side job is the time a member is expected to spend completing a given case. Members who have accepted a side job enter their planned time for the side job on a monthly basis through their applicant device 300. This time is reflected in the side job database 125. For example, the estimated working hours for case 001 are set at 5 hours / person / month in the recruitment case database 124. This means that one person will have to work 5 hours per month. Typically, members enter their planned time for the side job based on the estimated working hours for the recruitment case.

[0159] Side job performance time refers to the time a member actually worked on an accepted project. In other words, side job performance time refers to the time a member has actually worked on a project. Before completing a project, members can enter the time they spent working on the project at any time using their applicant device 300. The accumulated time entered via the applicant device 300 is recorded monthly in the side job database 125 as side job performance time.

[0160] The estimated time for the side job is the time required for the business of the case as the subject. In other words, the estimated time for the side job is the time estimated to be the member's future working time. The shared server 100 automatically sets the estimated time for the side job in consideration of the planned time for the side job and the actual time for the side job. It is also possible that before the business of the case as the subject is completed, the member can input the estimated time for the side job through his or her applicant device 300 at any time. In addition, it is also possible that the member can temporarily correct the automatically set estimated time for the side job. It is expected that the estimated time for the side job is less than the planned time for the side job. However, depending on the situation of the case, there is a possibility that the estimated time for the side job is longer than the planned time for the side job. It is also possible that the member working on the case can update the estimated time for the side job at any time before the business of the case is completed.

[0161] The progress rate indicates the degree of progress of the side job. The progress rate is entered based on the judgment of the person doing the side job. For example, enter a progress rate between 0 (%) and 100 (%).

[0162] For example, when a member first accepts a case, the progress rate is 0%, the actual side job time is 0 hours, and the planned side job time matches the estimated side job time. As the member progresses the case, they enter the actual side job time and progress rate, and the estimated side job time changes accordingly.

[0163] exist Figure 7 The side job database 125 shown shows the side job data of member P2 from October 2021 to December 2021. Figure 7 The side job database 125 shown shows that member P2 worked on project 001 and project 002 from October 2021 to December 2021.

[0164] As data for October of Project 001, the side job database 125 registers side job planned time = 5, side job actual time = 10, and side job estimated time = 10. This indicates that member P2 worked on Project 001 in October, exceeding the planned side job time.

[0165] As data for Project 002 for November, the side job database 125 records the side job planned duration = 10, the side job actual duration = 4, and the side job estimated duration = 8. This indicates that member P2 worked on Project 002 in November within the set estimated side job duration. The progress rate of 50 indicates that member P2 completed half of the total work for Project 002 in November.

[0166] For the December data for Case 001, the side job database 125 records the side job planned time = 5 and the side job estimated time = 5, but no actual side job time has been recorded. Similarly, for the December data for Case 002, no actual side job time has been recorded. This indicates that the system is waiting for member P2 to input the actual side job time.

[0167] The shared server 100 uses the estimated time for side jobs and the actual time for side jobs in the side job database 125 to calculate the spare time that the member can have to perform additional side jobs. In the case where a member is engaged in multiple side jobs, the shared server 100 calculates the total estimated time for side jobs corresponding to these multiple side jobs, namely the "total estimated time for side jobs", and the total actual time for side jobs corresponding to these multiple side jobs, namely the "total performance time for side jobs". The shared server 100 calculates the spare time for side jobs by calculating "the upper limit time for side jobs - (the total estimated time for side jobs + the total performance time for side jobs)". Here, when "the total estimated time for side jobs + the total performance time for side jobs" is defined as "the total time for side jobs", the spare time for side jobs, namely "the time available for side jobs", is calculated by "the upper limit time for side jobs - the total time for side jobs". For example, in Figure 7 In the side job database 125 shown, the total estimated side job time for member P2 for December is 15 hours (5 hours + 10 hours). Furthermore, member P2's total actual side job time for December is zero. If the "side job maximum time limit" set by member P2's company is 30 hours, member P2's remaining side job time (available time for side job) is calculated to be 15 hours (30 hours - 15 hours).

[0168] Here, we'll explain a more specific example of calculating the estimated time for a side job. For example, "estimated time for a side job" can also be calculated using the formula: "(Working Hours Progress Rate / Progress Rate) × Side Job Planned Time - Side Job Actual Time." Here, the "Working Hours Progress Rate" is calculated as "Side Job Actual Time / Side Job Planned Time." As already explained, the "Progress Rate" is a ratio entered into the side job database 125 based on the judgment of the person performing the side job.

[0169] For example, if the planned side job duration is 10 hours and the actual side job duration is 2 hours, the work progress rate is calculated as 20%. Here, let's set the progress rate to 40%. In this case, the estimated side job duration is calculated as "(20% 40%) x 10 hours - 2 hours" = 3 hours. In other words, based on this calculation, the estimated side job duration for the target side job is 3 hours.

[0170] [Evaluation input database 126]

[0171] Figure 8 1 is a diagram showing an example of the evaluation input database 126. Evaluation information on the evaluated person is registered in the evaluation input database 126. The evaluation information includes the evaluation object, the member ID of the evaluated person, the member ID of the evaluator, and the evaluation result.

[0172] Evaluation input database 126 includes recruiter evaluation unit 126A and applicant evaluation unit 126B. Recruiter evaluation unit 126A registers evaluation information for recruiters (order issuers), while applicant evaluation unit 126B registers evaluation information for applicants (order takers).

[0173] In the recruiter evaluation unit 126A, the recruiter (order issuer) corresponds to the evaluation target (evaluated person), and the applicant who applied for the recruitment business of the evaluation target and received the business order corresponds to the evaluator. In the recruiter evaluation unit 126A, the evaluation of the evaluated person is registered for each evaluator. Figure 8 In FIG, the example of members P1 and P2 who are evaluated are evaluated by the evaluator member is shown. Figure 8 1 shows an example in which member P1 receives evaluations from evaluator members P5, P7, P11, and P12, respectively. The evaluation results (evaluation values) are expressed as numerical values ​​with 10 being the maximum value and 0 being the minimum value.

[0174] In the applicant evaluation unit 126B, the applicant (the person who accepts the order) who applies for the recruitment case corresponds to the evaluation object (the person being evaluated), and the recruiter (the person who issues the order) of the case corresponds to the evaluator. In the applicant evaluation unit 126B, the evaluation of the person being evaluated is registered for each evaluator. Figure 8, which shows an example where a member P7, which is a person to be evaluated, receives evaluations from members P1, P2, and P3, which are evaluators. Figure 8 Although examples of evaluation results in the applicant evaluation unit 126B are omitted, various evaluation results are registered therein similarly to the recruiter evaluation unit 126A.

[0175] After completing a job order from a recruiter (order issuer), an applicant (order taker) uses the applicant device 300 as an evaluator to evaluate the recruiter (evaluated person). The evaluator's evaluation results are recorded in the evaluation input database 126. If an applicant receives another job order from a recruiter who previously received an order, the applicant evaluates the recruiter again. In this case, the average of the previous and next evaluation results is recorded in the evaluation input database 126.

[0176] When an applicant (order taker) completes a task entrusted to them, the recruiter (order issuer) uses the recruiter device 200 to evaluate the applicant (evaluated person). The evaluator's evaluation results are recorded in the evaluation input database 126. If a recruiter issues another task to an applicant who has previously entrusted a task, the recruiter evaluates the applicant again. In this case, the average of the previous and next evaluation results is recorded in the evaluation input database 126.

[0177] Therefore, the evaluation results registered in the evaluation input database 126 reflect the average of each evaluator's evaluations of the evaluated individual. Alternatively, a weighted average calculated based on the number of evaluations, a variance, or the like may be used instead of the average. Evaluation results for each case ID may also be registered in the evaluation input database 126.

[0178] [Review Abstract Database 127]

[0179] Figure 9 This figure shows an example of the evaluation summary database 127. Information on department-specific evaluations of evaluated individuals is registered in the evaluation summary database 127. The organization-specific evaluation information includes the evaluation subject, the evaluated individual's member ID, the ID of the company to which the evaluated individual belongs, the ID of the company to which the evaluator belongs, the department to which the evaluator belongs, and an evaluation summary.

[0180] Evaluation summary database 127 includes a recruiter evaluation summary section 127A and an applicant evaluation summary section 127B. In recruiter evaluation summary section 127A, recruiters (order issuers) correspond to evaluation targets (evaluated individuals). In applicant evaluation summary section 127B, applicants (order takers) correspond to evaluation targets (evaluated individuals). Evaluation summary database 127 stores evaluation summaries for evaluation targets by department.

[0181] The evaluation summary is calculated based on the statistical results of the evaluation input database 126. Department categories include "System Department" and "Planning Department" belonging to the enterprise, as well as "Overall" representing the entire enterprise. The evaluation summary is calculated for these "departments".

[0182] exist Figure 9 In the example shown in FIG. 127A, the recruiter evaluation summary section 127A shows that member P1 corresponds to the person being evaluated. The company ID of the person being evaluated is "00A". Therefore, member P1 belongs to company A. Figure 9 In FIG. 1 , data group 1271 represents the evaluation of member P1 acting as a recruiter by company B, and data group 1272 represents the evaluation of member P1 acting as a recruiter by company C.

[0183] Referring to data group 1271, it can be seen that the evaluation of company B is classified into the evaluation of the entire company, the evaluation of the system department within company B, and the evaluation of the planning department within company B. The average value of the evaluation corresponding to each classified category is registered in the evaluation summary.

[0184] For example, as an evaluation summary corresponding to the entire company B, the average value of the evaluation results of the members of the company B who evaluated the member P1 acting as a recruiter is registered. Figure 9 In , the value is "4.75". As the evaluation summary corresponding to the system department, the average value of the evaluation results of the members belonging to the system department among the members of the company B who evaluated the member P1 acting as a recruiter is registered. Figure 9 In , the value is "4.0". As the evaluation summary corresponding to the planning department, the average value of the evaluation results of the members belonging to the planning department among the members of the company B who evaluated the member P1 acting as a recruiter is registered. Figure 9 In the example, the value is "5.0".

[0185] As with data group 1271, data group 1272 also categorizes the evaluation of Company C into an overall company evaluation and an evaluation of each department within Company C. Data groups 1271 and 1272 contain data that evaluates applicants. Therefore, the evaluation summaries registered in data groups 1271 and 1272 are employee evaluation summaries.

[0186] The above describes the recruiter evaluation summary unit 127A in detail. Next, the applicant evaluation summary unit 127B will be described. Figure 9 In the example, the applicant evaluation summary section 127B shows that member P7 is the person being evaluated. The company ID of the person being evaluated is "00C." Therefore, member P7 belongs to company C. The applicant evaluation summary section 127B contains evaluations of member P7 as an applicant, recorded by department.

[0187] The applicant evaluation summary unit 127B has the same structure as the recruiter evaluation summary unit 127A except that the evaluation target is not the "recruiter" but the "applicant". Therefore, the description of the applicant evaluation summary unit 127B will be replaced by the description of the recruiter evaluation summary unit 127A.

[0188] The shared server 100 determines the evaluation result of each member using the evaluation input database 126 and determines the affiliation of each member using the member database 122. The shared server 100 updates the data of the evaluation summary database 127 based on these determination results.

[0189] In addition, Figure 9 In the example, only members P1 and P7 are shown as evaluated persons, but other members P2 to P6, member P8, and member P9 are also registered as evaluated persons in the evaluation summary database 127. The evaluation summary database 127 may also include data on the same member being the recruiter and the applicant as the evaluation object. For example, Figure 9 In the evaluation summary database 127 shown, in addition to the recruiter evaluation summary related to the member P1, the applicant evaluation summary related to the member P1 is also registered.

[0190] [Shared server, recruiter device, and applicant device function]

[0191] Figures 10 to 12 This is a diagram for explaining the functions of a shared server, a recruiter device, and an applicant device.

[0192] like Figure 10 As shown, shared server 100 functionally includes community registration unit 140, company registration unit 141, member registration unit 142, member search unit 143, and case registration unit 144. These various functions are implemented by processor 101, memory 102, storage device 103, and communication interface 104 included in shared server 100.

[0193] The community registration unit 140 has a function of registering a community in the community database 123. A system administrator who manages the matching system 1 inputs information related to the community into the shared server 100 using an operation unit such as a keyboard (not shown).

[0194] The information about the community includes the community name and information about the companies belonging to the community. The community registration unit 140 registers the community in the community database 123 according to the input of the system administrator (step S1). The community registration unit 140 also has the function of updating the information of the community registered in the community database 123.

[0195] The company registration unit 141 has a function of registering a new company that joins the matching system 1. The system administrator inputs information related to the company into the shared server 100 using an operation unit such as a keyboard.

[0196] The information about the company includes the company name, address, and the upper limit of the side job period. The company registration unit 141 registers the company in the company database 121 according to the input of the system administrator (step S2). The company registration unit 141 also has the function of updating the information of the registered company.

[0197] The member registration unit 142 has the function of registering (registering) new members participating in the matching system 1. The member registration unit 142 issues a member ID and password in response to a request from a person belonging to a company that has joined the matching system 1. A person who wishes to become a member performs the registration process using a personal computer or the like (step S3).

[0198] Specifically, a person who wishes to become a member enters information such as their name, company affiliation, and department into a personal computer, etc., and transmits the entered information to the shared server 100. The member registration unit 142 registers the entered information in the member database 122. New members can log in to the shared server 100 using the personal computer used for member registration. In this case, the personal computer functions as the recruiter device 200 or the applicant device 300.

[0199] exist Figure 10 Two applicant devices 300 are shown. One is assumed to be operated by a manager at the applicant company. The other is assumed to be operated by someone other than the manager at the applicant company. The manager at the applicant company holds a management position such as a department head and acts as a supervisor to the applicant, who is a subordinate. In this embodiment, the manager at the applicant company serves as the person who approves the subordinate's application for the job opening.

[0200] The member search unit 143 has a function of searching for members of the matching system 1. In response to requests from the recruiter device 200 and the applicant device 300, the member search unit 143 provides information on members registered in the member database 122 to the recruiter device 200 and the applicant device 300.

[0201] When the recruiter's device 200 receives a search operation from the recruiter, it executes a member search process (step S4A). This allows the recruiter to browse applicant information, for example. The recruiter can then select a candidate from among multiple applicants to receive an order based on the applicant's information. Similarly, when the applicant's device 300 receives a search operation from a manager (e.g., a supervisor of an applicant), it executes a member search process (step S4A).

[0202] Then, when the applicant's search operation is received, the applicant device 300 executes a member search process (step S4B). This allows the applicant to browse the recruiter's information, for example. The applicant can select a job to be accepted from a plurality of recruitment jobs in consideration of the recruiter's information.

[0203] The member search process (step S4A) executed by the recruiter device 200 and the member search unit 143 will be described later. Figure 19 The member search process (step S4B) performed by the applicant device 300 and the member search unit 143 will be described in detail later. Figure 20 Let’s explain in detail.

[0204] The case registration unit 144 has the function of registering a recruitment case in the recruitment case database 124. Upon receiving an input operation for a recruitment case, the recruiter device 200 performs a process of registering the recruitment case (step S5). During the recruitment case registration process, the recruiter device 200 transmits the recruitment case information to the shared server 100. The case registration unit 144 registers the received recruitment case information in the recruitment case database 124.

[0205] The recruitment case registration process (step S5) executed by the recruiter device 200 and the process of the case registration unit 144 will be described later. Figure 14 Let’s explain in detail.

[0206] like Figure 11 As shown, the shared server 100 functionally includes a project extraction unit 145 , an application unit 146 , an approval unit 147 , and a notification unit 148 . These various functions are implemented by the processor 101 , memory 102 , storage device 103 , and communication interface 104 included in the shared server 100 .

[0207] The case extraction unit 145 extracts job openings that applicants can browse. The application unit 146 submits an application to the administrator (the applicant's supervisor). The approval unit 147 sends the details of the application to the recruiter, conditional on the administrator (approver) approving the application. The notification unit 148 receives the result of the recruiter's decision on whether to hire the applicant and notifies the applicant and the administrator of the result.

[0208] The application unit 146 , the approval unit 147 , and the notification unit 148 implement notification of approval requests to the manager, notification of applicants to the recruiter, and notification of application results to the applicants through the workflow system.

[0209] When the applicant's operation requesting the search for recruitment cases is received, the applicant device 300 executes a recruitment case search process (step S6 ). In the recruitment case search process, the applicant device 300 sends a search request to the case extraction unit 145 of the shared server 100 .

[0210] When receiving a search request, the case extraction unit 145 extracts cases that are allowed to be viewed by applicants from the recruitment cases registered in the recruitment case database 124 and sends the extracted cases to the applicant device 300. The case extraction unit 145 determines whether a case is allowed to be viewed by applicants based on the first and second criteria. The first criterion is the scope of disclosure set for the recruitment case. The second criterion is the applicant's spare time from his / her side job. The scope of disclosure is determined by Figure 14 The remaining capacity of the sideline business is calculated as Figure 15 The time available for side hustles is shown.

[0211] The case extraction unit 145 determines cases that meet both the first and second criteria as cases that applicants are permitted to view. Therefore, the case extraction unit 145 extracts cases registered in the recruitment case database 124 that are permitted to be made public to the applicant who received the search request. Furthermore, the case extraction unit 145 extracts cases registered in the recruitment case database 124 that can be handled within the available time of the applicant who received the search request. The case extraction unit 145 transmits the cases permitted to be viewed by the applicant to the applicant's device 300.

[0212] The case extraction unit 145 may also accept an operation to set a criterion for extracting cases. For example, a function may be added to the shared server 100 that allows the system administrator to select one of a first setting that enables only the first criterion, a second setting that enables only the second criterion, and a third setting that enables both the first and second criterion.

[0213] The applicant device 300 receives the recruitment case from the case extracting unit 145. The applicant device 300 displays the received recruitment case on the display 305 (step S7).

[0214] The recruitment case search process (step S6), the recruitment case display process (step S7), and the process of the case extraction unit 145 will be described later. Figure 15 Let’s explain in detail.

[0215] The applicant selects an application target from the recruitment cases displayed on the display 305 on the applicant device 300. Based on the applicant's operation, the applicant device 300 executes the application process (step S8). During the application process, the applicant device 300 transmits application information indicating the target case to the application unit 146 of the shared server 100. This transmits the desired business order from the applicant device 300 to the application unit 146.

[0216] The application unit 146 transmits the application information received from the applicant device 30 to the applicant device 300 of the manager (the applicant's supervisor). For example, the application unit 146 identifies the member ID of the supervisor of the applicant's manager based on the relationship between the applicant's member ID and the supervisor's member ID registered in the member database 122. The application unit 146 transmits the subordinate's application information to the applicant device 300 corresponding to the identified supervisor's member ID. The manager confirms the business applied for by the subordinate on his or her own applicant device 300. The manager performs an operation to approve the application on the applicant device 300. The applicant device 300 accepts the approval operation and executes the application approval process (step S9). During the application approval process, the applicant device 300 transmits the approval information to the approval unit 147 of the shared server 100. Thus, the approval information, an example of an approval notification, is transmitted from the applicant device 300 of the manager (approver) to the approval unit 147.

[0217] Approval unit 147 accepts an applicant's application conditionally upon receipt of approval information from the applicant's device 300. Thus, in this embodiment, an applicant's application is accepted conditionally upon approval by the applicant's manager. This allows managers to confirm in advance the details of the recruitment tasks for which their subordinates wish to apply. This prevents confidential information from being leaked outside the company through employees' side hustles.

[0218] In addition, Figure 11 The flow when the administrator approves an application is shown in FIG. If an application rejection operation is accepted in step S9, rejection information is sent from the administrator's applicant device 300 to the approval unit 147. Upon receiving the rejection information, the approval unit 147 may notify the applicant's applicant device 300 of the rejection of the application.

[0219] After accepting the applicant's application, the approval unit 147 sends the application information to the recruiter device 200. The application information includes the applicant's information and the details of the business to be applied for. The recruiter device 200 displays the application details on the display 205 (step S10). The recruiter confirms the applicant and the business to be applied for based on the display on the display 205 and determines whether to recruit the applicant.

[0220] The recruiter inputs the result of the hiring or rejection judgment to the recruiter device 200. The recruiter device 200 receives the input result (step S11). The recruiter device 200 transmits the received hiring or rejection result to the notification unit 148 of the shared server 100.

[0221] Upon receiving the result of hiring or rejection from the recruiter device 200 , the notification unit 148 transmits the application result (hiring or rejection) to the applicant device 300 of the applicant and the applicant device 300 of the manager.

[0222] The applicant's applicant device 300 and the manager's applicant device 300 display the application result on the display 305 (step S12, step S13). The applicant and the manager check the application result by viewing the display on the display 305.

[0223] like Figure 12 As shown, shared server 100 functionally includes performance reception unit 149, performance output unit 150, evaluation reception unit 151, and evaluation output unit 152. These various functions are implemented by processor 101, memory 102, storage device 103, and communication interface 104 included in shared server 100.

[0224] The performance receiving unit 149 has a function of receiving the applicant's planned side job time and side job actual time inputted in the applicant device 300. The performance output unit 150 has a function of outputting information including the applicant's planned side job time and side job actual time to the recruiter device 200 or the administrator's applicant device 300.

[0225] The evaluation accepting unit 151 has a function of accepting an evaluation of an applicant (order taker) input by a recruiter in the recruiter device 200. The evaluation output unit 152 has a function of outputting information indicating the evaluation of the applicant to the recruiter device 200.

[0226] When an applicant is engaged in a side job, they input their planned side job time and actual side job time into the applicant device 300. Typically, the applicant inputs their planned side job time into the applicant device 300 when they receive a new side job order, and inputs their actual side job time into the applicant device 300 at any time during their side job. For example, if an applicant receives a side job order that is expected to span multiple months, they would input their actual side job time into the applicant device 300 each month.

[0227] The applicant device 300 receives input of the planned time and the actual time of the side job (step S14 ) and transmits the received planned time and the actual time of the side job to the actual time receiving unit 149 of the shared server 100 .

[0228] The performance receiving unit 149 registers the received side job planned time and side job actual time in the side job database 125. The processing of step S14 executed by the applicant device 300 and the processing of the performance receiving unit 149 will be described later. Figure 16 Let’s explain in detail.

[0229] The performance output unit 150 transmits the side job planned time and side job actual time registered in the side job database 125 to the recruiter device 200 and the administrator's applicant device 300. The recruiter device 200 displays information including the received side job planned time and side job actual time on the display 205, and the administrator's applicant device 300 displays information including the received side job planned time and side job actual time on the display 305 (step S15). However, when comparing the information transmitted to the recruiter device 200 and the information transmitted to the administrator's applicant device 300, the cases to which the information was transmitted differ.

[0230] Data corresponding to the projects that the subordinate is in charge of among the large number of projects registered in the side-job database 125 is sent from the performance reception unit 149 to the manager's applicant device 300. The manager can check the status of the subordinate's side-job by viewing the display 305. In addition, the screen displayed on the manager's applicant device 300 when the manager checks the status of the subordinate's side-job will be described later. Figure 23 To explain.

[0231] Data corresponding to the cases recruited by the recruiter among the large number of cases registered in the side job database 125 is sent from the performance receiving unit 149 to the recruiter device 200. For example, consider the following case: Figure 7 In the side job database 125 shown, a first recruiter among a plurality of recruiters is recruiting for case 001 , and a second recruiter is recruiting for case 002 .

[0232] In this case, the performance receiving unit 149 transmits various data corresponding to the job 001 in the side job database 125 to the recruiter device 200 operated by the first recruiter. The performance receiving unit 149 transmits various data corresponding to the job 002 in the side job database 125 to the recruiter device 200 operated by the second recruiter.

[0233] The first recruiter and the second recruiter can check the progress of their own cases by viewing the side job planned time and side job actual time displayed on the display 305 of the recruiter device 200 .

[0234] When the recruiter completes the side job, he / she inputs his / her evaluation of the applicant to the recruiter device 200. The recruiter device 200 receives the input of the applicant's evaluation (step S16A). Therefore, when receiving the input evaluation, the recruiter device 200 functions as an evaluator device operated by the evaluator (recruiter).

[0235] The recruiter device 200 transmits the received evaluation to the evaluation receiving unit 151 of the shared server 100. Based on the received evaluation, the evaluation receiving unit 151 updates the evaluation input database 126 and the evaluation summary database 127. As a result, the information in the applicant evaluation unit 126B in the evaluation input database 126 is updated, and the information in the applicant evaluation summary unit 127B in the evaluation summary database 127 is updated.

[0236] The processing of step S16A executed by the recruiter device 200 and the processing of the evaluation receiving unit 151 will be described later. Figure 17 Let’s explain in detail.

[0237] When the recruiter device 200 receives an operation for the recruiter to view the applicant's evaluation, it executes a view request process (step S17A). During the view request process, the recruiter device 200 transmits the view request to the evaluation output unit 152 of the shared server 100. In response to the view request, the evaluation output unit 152 transmits the applicant's evaluation (applicant evaluation summary) registered in the evaluation summary database 127 to the recruiter device 200. The recruiter device 200 displays the received applicant's evaluation on the display 205 (step S18A).

[0238] The processing of step S17A and step S18A executed by the recruiter device 200 and the processing of the evaluation output unit 152 will be described later. Figure 19 Let’s explain in detail.

[0239] Figure 13 This is a diagram for further explaining the function of the applicant device 300. Figure 13The input and output of a recruiter's evaluation will be described below. The evaluation accepting unit 151 also has the function of accepting applicants' evaluations of the recruiter input into the applicant device 300. The evaluation output unit 152 also has the function of outputting information indicating the recruiter's evaluation to the applicant device 300. Upon completing the work they have received, the applicant inputs their evaluation of the recruiter into the applicant device 300. There are various key points for applicants to evaluate the recruiter.

[0240] For example, if communication with the recruiter is smooth and the job is completed within a reasonable timeframe, the applicant will rate the recruiter highly. Conversely, if there are frequent requests for additions, changes, or revisions to the job description, if excessive time is taken up outside the scope of the job description, if instructions are communicated too late, or if the recruiter unilaterally issues instructions regarding revisions to the job description without prior consultation, the applicant will rate the recruiter low.

[0241] The applicant device 300 receives input of an evaluation for the applicant (step S16B). Therefore, when receiving the input evaluation, the applicant device 300 functions as an evaluator device operated by the evaluator (applicant).

[0242] Applicant device 300 transmits the received evaluation to evaluation reception unit 151 of shared server 100. Based on the received evaluation, evaluation reception unit 151 updates evaluation input database 126 and evaluation summary database 127. Consequently, information in recruiter evaluation unit 126A is updated in evaluation input database 126, and information in recruiter evaluation summary unit 127A is updated in evaluation summary database 127.

[0243] The processing of step S16B executed by the applicant device 300 and the processing of the evaluation receiving unit 151 will be described later. Figure 18 Let’s explain in detail.

[0244] When the applicant device 300 receives an operation for the applicant to view the evaluation of the recruiter, it executes a view request process (step S17B). During the view request process, the recruiter device 200 transmits the view request to the evaluation output unit 152 of the shared server 100. In response to the view request, the evaluation output unit 152 transmits the evaluation of the recruiter (recruiter evaluation summary) registered in the evaluation summary database 127 to the applicant device 300. The applicant device 300 displays the received evaluation of the recruiter on the display 305 (step S18B).

[0245] The processing of step S17B and step S18B executed by the applicant device 300 and the processing of the evaluation output unit 152 will be described later. Figure 20Let’s explain in detail.

[0246] [Details of Processing by the Case Registration Unit 144 and the Recruiter Device 200]

[0247] Figure 14 1 is a diagram for explaining the process of registering a recruitment case in the recruitment case database 124. Figure 14 To explain in more detail Figure 10 Step S5 and the function of the case registration unit 144.

[0248] A recruiter registering a recruitment case first logs into shared server 100 using recruiter device 200. This establishes a logical communication path identified by the recruiter's member ID between recruiter device 200 and shared server 100. The recruiter then uses operating unit 206, such as a mouse and keyboard, to input the case's business information and public information into recruiter device 200.

[0249] Information inputted through the operation unit 206 is notified to the processor 201 via the input / output interface 204 of the recruiter device 200. The operation unit 206 and the input / output interface 204 constitute an interface for accepting operations for inputting the content of a task and inputting public information specifying a target for publicizing the task.

[0250] Job information for a job offer includes the job title, job content, estimated man-months, and estimated duration. Public information includes a disclosure level. Public information may also include the ID of a company that is not publicly available, depending on the job offerer's preference.

[0251] The recruiter device 200 receives input of the business information and public information of the recruitment case and performs a process of registering the recruitment case (step S5 ). In the process of registering the recruitment case, the recruiter device 200 transmits the business information and public information of the recruitment case to the shared server 100 .

[0252] The project registration unit 144 of the shared server 100 acquires the information of the recruiter (step S1441 ). Specifically, the project registration unit 144 identifies the company to which the recruiter belongs.

[0253] When a member logs in to the shared server 100 using the recruiter device 200 or the applicant device 300, the shared server 100 stores the member ID used during login. When the shared server 100 receives certain information from the recruiter device 200 or the applicant device 300 during communication established using the member ID, the shared server 100 uses the member ID used during login to identify the member who sent the information.

[0254] Therefore, when receiving business information and public information about a recruitment business from the recruiter device 200, the case registration unit 144 uses the member ID used when logging in to identify the recruiter who is operating the recruiter device 200. The case registration unit 144 uses the identified member ID, the member database 122, and the company database 121 to identify the member who is the recruiter and the company to which the recruiter belongs.

[0255] Next, the case registration unit 144 registers the recruitment case in the recruitment case database 124 (step S1442). Specifically, after generating a case ID, the case registration unit 144 registers company information (company ID), the company ID set to non-public, the disclosure level, the case title, the estimated working hours, the estimated period, and the case details in the recruitment case database 124 in association with the generated case ID.

[0256] According to this embodiment, recruiters can freely control the scope of disclosure of recruitment projects at different levels, such as "within the company," "within the community," and "unlimited." As a result, it is possible to prevent recruitment projects that recruiters do not want from being disclosed to specific companies.

[0257] According to this embodiment, companies that are not disclosed can be set independently of the disclosure level. Therefore, recruiters can exclude some companies from the community with which their company is affiliated and set the scope of disclosure. This prevents business related to a specific company within the community from being disclosed to that specific company.

[0258] Instead of or in addition to the non-public company ID list, a non-public member ID list for registering member IDs for prohibited public recruitment cases may be provided in the recruitment case database 124. The recruiter device 200 may also accept an operation from a member designating a prohibited public recruitment case and transmit the member ID to the shared server 100. The shared server 100 may also not provide recruitment cases corresponding to the member ID listed in the non-public member ID list to the member. In this manner, the recruiter device 200 may accept either a company or a member as a subject for prohibited public business operations.

[0259] Figure 15 1 is a diagram for explaining the process of searching for recruitment cases from the database 120. Figure 15 To explain in more detail Figure 11 The processing of steps S6 and S7 and the function of the case extraction unit 145.

[0260] When the applicant's operation requesting the search for recruitment cases is received, the applicant device 300 executes a recruitment case search process (step S6 ). In the recruitment case search process, the applicant device 300 sends a search request to the case extraction unit 145 of the shared server 100 .

[0261] When receiving the search request, the project extraction unit 145 extracts projects that applicants are permitted to browse from the recruitment projects registered in the recruitment project database 124. To this end, the project extraction unit 145 executes the processing of steps S1451 to S1454.

[0262] Steps S1451 and S1452 are the process of extracting projects that applicants are allowed to view based on the public scope set for the recruitment project. In step S1451, the applicant's company and the company's community are determined. In step S1452, the projects that can be made public are extracted.

[0263] Step S1453 is a process for extracting jobs that the applicant is allowed to browse based on the applicant's spare time in the side job. Step S1454 is a process for finally extracting jobs that match the applicant.

[0264] [Handling of cases extracted based on the scope of disclosure]

[0265] Step S1451 includes step S1451A and step S1451B.

[0266] In step S1451A, the company to which the applicant belongs is identified based on the member ID used at the time of login, the company database 121, and the member database 122.

[0267] In step S1451B, based on the ID of the company to which the applicant belongs and the community database 123 , the community of the company to which the applicant belongs is determined.

[0268] Step S1452 includes step S1452A and step S1452B.

[0269] In step S1452A, based on the community to which the applicant's company belongs and the level of disclosure, job openings that can be disclosed are extracted from the job opening database 124 .

[0270] In step S1452B, the recruitment cases extracted in step S1452A for companies to which applicants belong are excluded. Here, the cases extracted in step S1452B are referred to as cases X.

[0271] [Handling of cases involving the withdrawal of surplus labor from a side job]

[0272] Step S1453 includes step S1453A, step S1453B, and step S1453C.

[0273] In step S1453A, the applicant's available time for side jobs, T1, is calculated. The available time for side jobs is derived by calculating "the maximum time for side jobs - the total time for side jobs." The maximum time for side jobs is set by the applicant's company and is registered in the company database 121. The calculated available time for side jobs is registered in the member database 122. The case extraction unit 145 may also calculate the available time for side jobs for all members at regular intervals and register the calculated available time for side jobs in the member database 122.

[0274] The total time spent on side jobs is calculated using the formula "total estimated time spent on side jobs + total actual time spent on side jobs" based on the estimated time and actual time registered in the side job database 125. In other words, the total time spent on side jobs includes not only the time already spent on the side job but also the estimated time not yet spent on the side job.

[0275] In step S1453B, the time T2 required to handle the work is calculated for each recruitment case. Time T2 is calculated based on the assumed man-hours (person / month) and the assumed period registered in the recruitment case database 124. For example, the assumed man-hours (month) can be used as time T2. For example, for the recruitment case corresponding to case ID 001, time T2 can be set to 5 hours per month.

[0276] In step S1453C, recruitment cases that meet the condition "time T2 ≤ time available for side job T1" are extracted from the recruitment case database 124. Here, the cases extracted in step S1453C are referred to as cases Y.

[0277] [Handling of cases based on the scope of disclosure and the remaining capacity of side jobs]

[0278] After extracting the project X based on the public scope and extracting the project Y based on the spare time of the side job, the project extracting unit 145 extracts the overlapping projects between project X and project Y as matching projects for the applicant (step S1454 ).

[0279] [Provide processing of extracted cases]

[0280] Next, the job extracting unit 145 transmits the matching job information to the applicant device 300 (step S1455). The applicant device 300 receives the matching job and displays the received matching job on the display 305 as a list of recruitment jobs (step S7).

[0281] This allows for the provision of job offers that are appropriate for applicants from two perspectives. First, applicants are provided with job offers that they can handle within the timeframe of their side hustle. This prevents applicants from becoming overworked. Second, the offer is only provided to applicants whose applications fall within the scope of the applicant's desired disclosure. This prevents the confidential information of the applicant's company from being leaked to competing companies.

[0282] [Registration of sideline business plan time and sideline business actual performance time]

[0283] Figure 16 This is a diagram for explaining the process of registering the sideline business plan and performance in the database 120. Figure 16 To explain in more detail Figure 12 Step S14 and the function of the performance receiving unit 149.

[0284] For example, when an applicant accepts a new side job, they enter their planned side job time into the applicant device 300. At any time during their side job, they enter their actual side job time into the applicant device 300. The applicant device 300 receives the input of the planned side job time (step S14). The applicant device 300 transmits the received planned side job time and actual side job time to the performance receiving unit 149 of the shared server 100.

[0285] The performance receiving unit 149 receives the applicant's planned side job time and actual side job time, and registers the received applicant's planned side job time and actual side job time in the side job database 125 (step S1511). Thus, the applicant's planned side job time and actual side job time are registered in the side job database 125 for each case ID each month.

[0286] Typically, after an applicant enters their planned side job time, they enter their actual side job performance time at the end of the month. Therefore, the side job database 125 may contain cases where the planned side job time is registered but the actual side job performance time is not. For example, when an applicant who has accepted a side job enters their planned side job time, the planned side job time is registered as the data corresponding to the side job, but the actual side job performance time is not registered.

[0287] Next, the performance acceptance unit 149 automatically calculates the estimated time for the side job for the current month (step S1512). The performance acceptance unit 149 calculates the estimated time for the side job based on the planned time for the side job and the actual time for the side job. Specifically, as already explained, the "estimated time for the side job" is calculated based on the formula "(working hour progress rate / progress rate)× planned time for the side job-actual time for the side job". In addition, the performance acceptance unit 149 can also calculate the "estimated time for the side job" by the formula "planned time for the side job-actual time for the side job". The performance acceptance unit 149 registers the calculated estimated time for the side job in the side job database 125. Figure 7 As shown in the side job database 125, the estimated time of the side job is registered for each case ID.

[0288] [Handling of Registration Evaluation Results (Evaluation of Applicants)]

[0289] Figure 17 1 is a diagram for explaining the process of registering the evaluation of the applicant in the database 120. Figure 17 To explain in more detail Figure 12 Step S16A and the function of the evaluation reception unit 151.

[0290] When the applicant completes the side job, they submit a completion report to the recruiter and receive the recruiter's approval. The recruiter then operates recruiter device 200 to input their evaluation of the applicant. Recruiter device 200 accepts the input evaluation (step S16A). Recruiter device 200 transmits the received evaluation to evaluation reception unit 151 of shared server 100. The information transmitted from recruiter device 200 to shared server 100 includes the member ID of the applicant being evaluated and an evaluation value (0-10).

[0291] Upon receiving information on the evaluation of the person to be evaluated (applicant) from the recruiter device 200 , the evaluation reception unit 151 reflects the evaluation of the person to be evaluated in the evaluation input database 126 (step S1513A).

[0292] If evaluation results for the evaluated person (applicant) are already registered in the evaluation input database 126, the evaluation receiving unit 151 calculates the average of the evaluation results for the evaluated person, including the value of the currently received evaluation. The evaluation receiving unit 151 uses the calculated average to update the evaluation results registered in the evaluation input database 126. As a result, the average (evaluation result) of the evaluations for the evaluated person (applicant) is registered in the evaluation input database 126 for each evaluator (recruiter). This updates the information in the applicant evaluation unit 126B in the evaluation input database 126.

[0293] Next, the evaluation reception unit 151 performs evaluation summary processing (step S1514A). During the evaluation summary processing, the evaluation reception unit 151 calculates the average of the evaluation results for each evaluated person (applicant) by company and department, and registers the calculated results in the evaluation summary database 127. This updates the information in the applicant evaluation summary unit 127B in the evaluation summary database 127.

[0294] For example, the evaluation acceptance unit 151 identifies the evaluator (recruiter) using the member ID used by the recruiter device 200 when logging in to execute step S16A. Based on the evaluation information received in step S1513A, the company database 121, and the member database 122, the evaluation acceptance unit 151 identifies the ID of the company to which the evaluator belongs, the department to which the evaluator belongs, the member ID of the person being evaluated, and the ID of the company to which the person being evaluated belongs. The "member ID" is an example of "identification information that allows the shared server 100, including the evaluation acceptance unit 151, to identify the company and department to which the person accessing the shared server 100 belongs."

[0295] The evaluation receiving unit 151 accesses the evaluation summary database 127 and detects a row of data containing the specified IDs (the member ID of the evaluated person, the ID of the company to which the evaluated person belongs, and the ID of the company to which the evaluator belongs). The evaluation receiving unit 151 updates the value of the applicant evaluation summary corresponding to the detected row of data.

[0296] [Handling of Registration Evaluation Results (Evaluation of Recruiters)]

[0297] Figure 18 This is a diagram for explaining the process of registering the evaluation of the applicant in the database. Figure 18 To explain in more detail Figure 13 Step S16B and the function of the evaluation receiving unit 151.

[0298] As described above, when the applicant completes the side job, they submit a completion report to the recruiter and receive the recruiter's approval. The applicant then operates the applicant device 300 to input their evaluation of the recruiter. The applicant device 300 accepts the input evaluation (step S16B). The applicant device 300 transmits the received evaluation to the evaluation receiving unit 151 of the shared server 100. The information transmitted from the applicant device 300 to the shared server 100 includes the member ID of the recruiter being evaluated and an evaluation value (0-10).

[0299] Upon receiving information on the evaluation of the person to be evaluated (recruiter) from the applicant device 300 , the evaluation reception unit 151 reflects the evaluation of the person to be evaluated in the evaluation input database 126 (step S1513B).

[0300] If evaluation results for the evaluated person (recruiter) are already registered in the evaluation input database 126, the evaluation receiving unit 151 calculates the average of the evaluation results for the evaluated person, including the value of the currently received evaluation. The evaluation receiving unit 151 uses the calculated average to update the evaluation results registered in the evaluation input database 126. As a result, the average (evaluation result) of the evaluation results for the evaluated person (recruiter) is registered for each evaluator (applicant) in the evaluation input database 126. This updates the information in the recruiter evaluation unit 126A in the evaluation input database 126.

[0301] Next, the evaluation reception unit 151 performs evaluation summary processing (step S1514B). During the evaluation summary processing, the evaluation reception unit 151 calculates the average of the evaluation results for the evaluated individuals (recruiters) by company and department, and registers the calculated results in the evaluation summary database 127. This updates the information in the recruiter evaluation summary unit 127A in the evaluation summary database 127.

[0302] For example, the evaluation acceptance unit 151 identifies the evaluator (applicant) using the member ID used by the applicant device 300 when logging in to execute step S16B. Based on the evaluation information received in step S1513B, the company database 121, and the member database 122, the evaluation acceptance unit 151 identifies the ID of the company to which the evaluator belongs, the department to which the evaluator belongs, the member ID of the person being evaluated, and the ID of the company to which the person being evaluated belongs. The "member ID" is an example of "identification information that allows the shared server 100, including the evaluation acceptance unit 151, to identify the company and department to which the person accessing the shared server 100 belongs."

[0303] The evaluation receiving unit 151 accesses the evaluation summary database 127 and detects a row containing the specified IDs (evaluee's member ID, the ID of the company to which the evaluated person belongs, and the ID of the company to which the evaluator belongs). The evaluation receiving unit 151 updates the value of the recruiter evaluation summary corresponding to the detected row.

[0304] For example, in Figure 9 The data group 1271 contains the member ID of the evaluated person = P1, the company ID of the evaluated person = 00A, and the company ID of the evaluator = 00B. If a member of the system department of company B evaluates member P1, the evaluation is accepted in step S1513B.

[0305] In this case, in step S1514B, the evaluation received in step S1513B is reflected in the recruiter evaluation summary corresponding to “all” and the recruiter evaluation summary corresponding to “system department” in the data group 1271 .

[0306] More specifically, the evaluation accepting unit 151 uses the average of the evaluations of the entire company B, included in the evaluations accepted in step S1513B, as the recruiter evaluation summary corresponding to "Overall" in data group 1271. Similarly, the evaluation accepting unit 151 uses the average of the evaluations of the system department, included in the evaluations accepted in step S1513B, as the recruiter evaluation summary corresponding to "System Department" in data group 1271.

[0307] Figure 19 2 is a diagram for explaining the process of displaying the evaluation of the applicant and the member search results on the display 205. Figure 19 To explain in more detail Figure 10 Step S4A (processing of the recruiter device 200) and the function of the member search unit 143, and Figure 12 Step S17A, step S18A and the function of the evaluation output unit 152.

[0308] [Processing of outputting applicant's evaluation summary]

[0309] First, yes Figure 19 The processing of step S17A, step S18A, step S1521A, and step S1522A shown in FIG.

[0310] When the recruiter device 200 receives an operation for the recruiter to view the evaluations of the applicant, it executes a view request process (step S17A). In the view request process, the recruiter device 200 sends the view request to the evaluation output unit 152 of the shared server 100. In response to the view request, the evaluation output unit 152 selects the applicant evaluation summaries for which the recruiter (the view requester) has been granted viewing permission from the evaluation summary database 127 (step S1521A).

[0311] The recruiter who made the browsing request is granted permission to browse the applicant evaluation summaries for the entire company to which the recruiter belongs and the applicant evaluation summaries for the department to which the recruiter belongs. The recruiter who made the browsing request is not granted permission to browse evaluation summaries other than these. The evaluation output unit 152 determines browsing permission based on the member ID of the recruiter who sent the browsing request, the company database 121, and the member database 122. The "member ID" is an example of "identification information that allows the shared server 100, including the evaluation reception unit 151, to identify the affiliation (company and department) and browsing permission of the person accessing the shared server 100."

[0312] The evaluation output unit 152 selects an applicant evaluation summary corresponding to the browsing permission from the evaluation summary database 127. The evaluation output unit 152 transmits data including the selected applicant evaluation summary to the recruiter device 200 (step S1522A). The transmitted data includes, in addition to the applicant evaluation summary, the applicant's (evaluated person's) member ID, information about the applicant's company, information about the applicant's department, and other information. Depending on the browsing request, the transmitted data may also include applicant evaluation summaries corresponding to each of multiple applicants (evaluated persons).

[0313] The recruiter device 200, having received the applicant evaluation summary, displays the applicant evaluation summary on the display 205 along with information about the company to which the applicant belongs and information about the department to which the applicant belongs (step S18A). When the recruiter device 200 receives applicant evaluation summaries corresponding to multiple applicants (evaluated persons), the recruiter device 200 displays the applicant evaluation summaries as a list of the multiple applicants (evaluated persons).

[0314] As described above, when the shared server 100 receives a browsing request through communication using a member ID that can identify the company and department to which the recruiter belongs, it transmits the applicant evaluation summary as an example of evaluation information to the recruiter device 200 that is the source of the browsing request.

[0315] [Member (Applicant) Search Process]

[0316] Next, refer to Figure 19 The respective processes of step S4A, step S19A, and step S1431A to step S1433A will be described.

[0317] When the recruiter device 200 receives a search operation from the recruiter, it executes a member search process for searching for information related to the applicant (step S4A). During the member search process, the recruiter device 200 sends a search request to the member search unit 143 of the shared server 100. The search request includes a reference value for excluding members with low applicant evaluations. This reference value is determined, for example, based on the applicant's evaluation summary.

[0318] The member search unit 143 that has received the search request identifies the company to which the recruiter who sent the search request belongs (step S1431A). Here, the company identified in step S1431A is referred to as "company Xa."

[0319] The member search unit 143 uses the member ID used by the recruiter device 200 to log into the shared server 100 to identify the recruiter operating the recruiter device 200. The member search unit 143 uses the company database 121 and the member database 122 to identify the company Xa to which the recruiter belongs.

[0320] Next, the member search unit 143 extracts members whose applicant evaluation summary values ​​for the identified company Xa as a whole exceed the reference value from the evaluation summary database 127 (step S1432A). In other words, the member search unit 143 extracts the search results after excluding members with low evaluations of the company Xa as a whole.

[0321] It should be noted here that the member search unit 143 determines whether the evaluation is low based on the applicant's evaluation summary. Specifically, member α, who possesses both applicant and recruiter authority, may sometimes act as an applicant and sometimes as a recruiter. Therefore, both the applicant's evaluation summary and the recruiter's evaluation summary are registered in the evaluation summary database 127 as evaluation summaries of member α. Member α may have a high evaluation as a recruiter but a low evaluation as an applicant. In this case, member α may be excluded from the extraction target in step S1432A.

[0322] The shared server 100 may be provided with a function for accepting reference value setting information from each company's recruiter device 200. In this way, each company can exclude members with low evaluations from the search results using its own reference value.

[0323] Next, the member search unit 143 outputs the extracted member information as a search result to the recruiter device 200 that has requested the search (step S1433A). The recruiter device 200 displays a list of the received search results on the display 205 (step S19A).

[0324] As a result, the recruiter can view search results excluding members with low overall evaluations of the company to which the recruiter belongs on the display 205. Therefore, the recruiter can save the trouble of visually excluding members with low overall evaluations of the company when selecting an order taker from the applicants.

[0325] In this embodiment, even if a member has a low evaluation in a department of the company to which the recruiter belongs, the member is not excluded from the search results if the company's overall evaluation is not low. However, the member search unit 143 may further exclude such members from the search results.

[0326] Figure 20 305 is a diagram for explaining the process of displaying the evaluation of the recruiter and the search results of the members on the display 305. Figure 20To explain in more detail Figure 10 Step S4B (processing of the applicant device 300) and the function of the member search unit 143, and Figure 13 Step S17B, step S18B and the function of the evaluation output unit 152.

[0327] [Processing of outputting the applicant's evaluation summary]

[0328] First, yes Figure 20 The processing of step S17B, step S18B, step S1521B, and step S1522B shown in FIG.

[0329] When the applicant device 300 receives an operation requesting the applicant to view reviews of a recruiter, it executes a view request process (step S17B). In the view request process, the applicant device 300 sends the view request to the review output unit 152 of the shared server 100. In response to the view request, the review output unit 152 selects, from the review summary database 127, a review summary of a recruiter for which the applicant (the view requester) has been granted viewing permission (step S1521B).

[0330] An applicant who has made a browsing request is granted permission to browse the applicant evaluation summary for the entire company to which the applicant belongs and the applicant evaluation summary for the department to which the applicant belongs. The applicant who has made a browsing request is not granted permission to browse evaluation summaries other than these. The evaluation output unit 152 determines browsing permission based on the member ID of the applicant who sent the browsing request, the company database 121, and the member database 122. The "member ID" is an example of "identification information that allows the shared server 100, including the evaluation reception unit 151, to identify the affiliation (company and department) and browsing permission of the person accessing the shared server 100."

[0331] The evaluation output unit 152 selects a recruiter evaluation summary corresponding to the browsing permission from the evaluation summary database 127. The evaluation output unit 152 transmits data including the selected recruiter evaluation summary to the applicant device 300 (step S1522B). The transmitted data includes, in addition to the recruiter evaluation summary, the recruiter's (evaluated person's) member ID, information about the recruiter's company, information about the recruiter's department, and so on. Depending on the browsing request, the transmitted data may also include recruiter evaluation summaries corresponding to each of multiple recruiters (evaluated persons).

[0332] The applicant device 300, having received the recruiter evaluation summary, displays the recruiter evaluation summary on the display 305 along with information about the company to which the recruiter belongs and information about the department to which the recruiter belongs (step S18B). If the applicant device 300 receives recruiter evaluation summaries corresponding to each of a plurality of recruiters (evaluated persons), the applicant device 300 displays the recruiter evaluation summaries in a list of the plurality of recruiters (evaluated persons).

[0333] As described above, when the shared server 100 receives a browsing request in communication established using a member ID that can identify the company and department to which the applicant belongs, it transmits the recruiter evaluation summary as an example of evaluation information to the applicant device 300 that sent the browsing request.

[0334] [Member (recruiter) search process]

[0335] Next, refer to Figure 20 The respective processes of step S4B, step S19B, and step S1431B to step S1433B will be described.

[0336] When the applicant device 300 receives a search operation from the applicant, it executes a member search process for searching for information related to the recruiter (step S4B). During the member search process, the applicant device 300 sends a search request to the member search unit 143 of the shared server 100. The search request includes a reference value for excluding members with low evaluations as recruiters. This reference value is determined, for example, based on the recruiter's evaluation summary.

[0337] The member search unit 143 that has received the search request identifies the company to which the applicant who sent the search request belongs (step S1431B). Here, the company identified in step S1431B is referred to as "company Xb."

[0338] The member search unit 143 identifies the applicant operating the applicant device 300 using the member ID used by the applicant device 300 when logging into the shared server 100. The member search unit 143 identifies the company Xb to which the applicant belongs using the company database 121 and the member database 122.

[0339] Next, the member search unit 143 extracts members whose evaluation summary values ​​of the recruiter for the identified entire company Xb exceed the reference value from the evaluation summary database 127 (step S1432B). In other words, the member search unit 143 extracts the search results after excluding members with low evaluations of the entire company Xb.

[0340] The shared server 100 may be provided with a function for accepting reference value setting information from each company's recruiter device 200. In this way, each company can exclude members with low evaluations from the search results using its own reference value.

[0341] Next, the member search unit 143 outputs the extracted member information as a search result to the applicant device 300 that has requested the search (step S1433B). The applicant device 300 displays a list of the received search results on the display 305 (step S19B).

[0342] As a result, the applicant can view search results excluding members with low overall evaluations of the applicant's company through the display 305. Therefore, the applicant can save the trouble of visually excluding members with low overall evaluations of the company when selecting an order taker from the recruiter.

[0343] In this embodiment, even if a member has a low evaluation in a department of the company to which the applicant belongs, the member is not excluded from the search results if the company's overall evaluation is not low. However, the member search unit 143 may further exclude such members from the search results.

[0344] [Browsable range of evaluation summary database 127]

[0345] Figure 21 This is a diagram for explaining the browsable range of the evaluation summary database 127. Figure 9 The browsable range will be described using the applicant evaluation summary section 127A shown in FIG. 1 as an example.

[0346] Figure 21 The recruiter evaluation summary section 127A shown contains evaluation summaries for member P1, who is acting as a "recruiter," from each of companies B and C. Member P1 belongs to company A. Company B's evaluation summaries are categorized into "General," "System Department," and "Planning Department." Company C's evaluation summaries are categorized into "General" and "Planning Department," among others. Members belonging to companies B and C view the evaluation summaries for member P1 as "applicants."

[0347] The browsing permission for the evaluation summary calculated based on the overall evaluation of enterprise B is as follows Figure 21 As shown in the "Viewable Range" column of , it is granted to all members belonging to Company B.

[0348] The right to view the evaluation summary calculated based on the evaluation of Company B's System Department is granted to members of Company B's System Department, but not to members outside of Company B's System Department. The right to view the evaluation summary calculated based on the evaluation of Company B's Planning Department is granted to members of Company B's Planning Department, but not to members outside of Company B's Planning Department.

[0349] The right to view the evaluation summary calculated based on the overall evaluation of Company C is granted to all members belonging to Company C. The right to view the evaluation summary calculated based on the evaluation of Company C's Planning Department is granted to members of Company C's Planning Department, but is not granted to members outside of Company C's Planning Department.

[0350] The above description takes the applicant evaluation summary section 127A as an example to explain the browsable range. Figure 9 ), the browseable range is also defined with the same design concept as the recruiter evaluation summary section 127A.

[0351] If the viewer is a member of the first department of company X and a member of the second department of company X, the viewer's authority for the overall evaluation summary of company X, the evaluation summary of the first department of company X, and the evaluation summary of the second department of company X is as follows: Figure 21 Here, when the applicant is equivalent to the "browser", the evaluation summary of the "recruiter" is browsed. Conversely, when the recruiter is equivalent to the "browser", the evaluation summary of the "applicant" is browsed.

[0352] Members belonging to the first department of Company X can view the overall evaluation summary of Company X and the evaluation summary of the first department of Company X, but cannot view the evaluation summary of the second department of Company X. Members belonging to the second department of Company X can view the overall evaluation summary of Company X and the evaluation summary of the second department of Company X, but cannot view the evaluation summary of the second department of Company X. Members belonging to Company Y other than Company X cannot view the overall evaluation summary of Company X, the evaluation summary of the first department of Company X, or the evaluation summary of the second department of Company X.

[0353] The overall evaluation summary of Company X, the evaluation summary of Company X's first department, and the evaluation summary of Company X's second department are not disclosed to members of companies other than Company X. Therefore, when a member belonging to Company Y and acting as an applicant evaluates a recruiter belonging to Company X, they can objectively evaluate the recruiter belonging to Company X without considering the relationships between the companies. Similarly, when a member belonging to Company Y and acting as a recruiter evaluates an applicant belonging to Company X, they can objectively evaluate the applicant belonging to Company X without considering the relationships between the companies.

[0354] Furthermore, evaluations by members of Company X (evaluations of recruiters and applicants) are shared within Company X as recruiter evaluation summaries and applicant evaluation summaries. This allows evaluators to realize that the accumulation of individual evaluations yields useful information, motivating them to provide accurate evaluations.

[0355] As a result, the accuracy of the recruiter evaluation summary and the applicant evaluation summary is improved. Thus, the recruiter evaluation summary can be effectively used as reference data when selecting recruiting jobs. Similarly, the applicant evaluation summary can be effectively used as reference data when selecting order takers.

[0356] Furthermore, according to this embodiment, when the recruiter device 200 performs a member search process (step S4A), search results excluding members with low evaluations are provided to the recruiter (step S1432A). Similarly, when the applicant device 300 performs a member search process (step S4B), search results excluding members with low evaluations are provided to the recruiter (step S1432B). In other words, the matching system 1 has a filtering function for providing search results that exclude members with low evaluations.

[0357] Therefore, when recruiters decide who to hire for a job, they can prevent the mistaken hiring of members with low ratings on a company-by-company basis. Similarly, when applicants decide who to apply for from a large number of jobs, they can prevent the mistaken selection of jobs offered by members with low ratings on a company-by-company basis. Furthermore, shared server 100 can also perform filtering using evaluation summaries on a department-by-department basis.

[0358] Alternatively, a command signal instructing whether to use filtering using the overall enterprise evaluation summary or filtering using the departmental evaluation summary may be sent from the recruiter device 200 to the shared server 100. In this case, the shared server 100 is provided with a function for changing the evaluation summary used for filtering according to the command signal.

[0359] [Example of setting the disclosure scope based on the disclosure level]

[0360] Figure 22 is a diagram showing an example of setting a disclosure range according to a disclosure level. Figure 22 As shown, consider the case where companies A to E form a community relationship, and company F does not have a community relationship with any company. In this case, the disclosure scope of the recruitment case is as shown in Table 402, based on the company to which the recruiter belongs and the disclosure level set by the recruiter.

[0361] Figure 22 The disclosure levels of "Level 1" to "Level 3" shown correspond to the three levels of "Our Company", "Within the Community" and "All" already explained. Therefore, in Level 1, the recruitment case of the recruiter is disclosed only to applicants belonging to the same company as the company to which the recruiter belongs. In Level 2, in addition to the scope of Level 1, the recruitment case of the recruiter is also disclosed to applicants belonging to companies that have a community relationship with the company to which the recruiter belongs. In Level 3, the recruitment case of the recruiter is disclosed to applicants belonging to all companies including the company to which the recruiter belongs. However, in the case where the recruiter specifies a company ID that is set to be non-public, regardless of the set disclosure level, the company corresponding to the company ID is excluded from the companies to which the disclosure is to be made. Among the disclosure levels of this embodiment, "Level 1" is the level corresponding to "disclosure of business information to the first applicant is allowed, and disclosure of business information to applicants who do not belong to the first group is prohibited". "Level 2" corresponds to "disclosure of business information to applicants belonging to any of the first group and any social groups with which the first group has a social relationship, but disclosure of business information to applicants not belonging to the first group or any of the social groups is prohibited." "Level 3" corresponds to "disclosure of business information to applicants, regardless of the group to which the applicant belongs."

[0362] Here, as an example of multiple levels of disclosure, the above-mentioned levels 1 to 3 are described. However, the multiple levels of disclosure are not limited to these. For example, a certain community can be divided into multiple small communities, and whether to publicly recruit business can be set for each small community. More specifically, Figure 5 Community 02 is shown as being divided into a first sub-community and a second sub-community. Assume that Enterprise C belongs to the first sub-community, while Enterprises D and E belong to the second sub-community. In this case, recruiters at Enterprise D can choose whether to disclose their recruitment services within the first or second sub-community.

[0363] The shared server 100 may also accept an operation to set a different disclosure range for each recruitment case. For example, a specific example of setting a different disclosure range for each recruitment case will be described using Cases 001 to 003 among a large number of recruitment cases.

[0364] For example, the disclosure scope of recruitment case 001 can be limited to only companies A and C belonging to the community identified by community ID = 03. Alternatively, the disclosure scope of recruitment case 002 can be limited to only companies C, D, and C belonging to the community identified by community ID = 02. Alternatively, the disclosure scope of case 003 can be limited to companies C, D, and C belonging to the community identified by community ID = 02 and companies A and C belonging to the community identified by community ID = 03.

[0365] Enterprise A can also form a community independent of the community identified by community ID = 01 or 02. For example, Figure 22 As shown by the dotted line in , company A can form a community with company Z identified by community ID = Z. For example, if the recruiter belongs to company A, the recruiter's recruitment case can be made public to applicants belonging to company A and applicants belonging to company Z. Figure 22 As shown, such a public level is adopted as a modified example of "Level 3".

[0366] In this case, "Level 3" corresponds to "allowing disclosure of business information to applicants belonging to the first group (Enterprise A) and a specific community group (a community identified by community ID = Z) that is different from the second-level community group (Enterprise A to Enterprise C) and has formed a community relationship with the first group, and prohibiting disclosure of business information to applicants who do not belong to either the first group or the specific community group."

[0367] [Example of the screen displayed when checking the status of side jobs]

[0368] Figure 23 3 is a diagram showing a screen displayed on the applicant device 300 of the manager (the applicant's supervisor) when the manager confirms the status of the subordinate's side job. Figure 23 3 shows an example in which the status of the side jobs of the manager's subordinates is displayed on the applicant device 300. The applicant device 300 is provided with a keyboard 306A and a mouse 306B as operation units.

[0369] Here, the manager is, for example, the head of the sales department of Company C. Display 305 shows the status of side jobs for employees in the sales department. The manager can confirm the status of side jobs for employees in the sales department by selecting any of tabs 307A, 307B, 307C, etc. using keyboard 306A or mouse 306B. This allows the manager to manage the working hours of their subordinates to prevent them from being overworked. The progress rate can also be displayed on the screen.

[0370] [Details of the case]

[0371] Figure 24 1 is a diagram showing the details of the case contents included in the recruitment case database 124. The case contents include recruitment points. Figure 24 As shown, the case contents are registered in the recruitment case database 124 according to the case ID.

[0372] The job description includes sections on required skills, required experience, and required qualifications. These sections describe the requirements for applicants. Required skills refer to the skills required for the job. Required experience refers to the number of years of experience using the required skills. Required qualifications include national and private qualifications.

[0373] The case details also include the issuer and the company to which the issuer belongs. The issuer is the person who drafted the case, also known as the recruiter. The company to which the issuer belongs is the name of the company to which the recruiter belongs.

[0374] Project details also include the timeframe, unit price (hourly rate), planned total time, and actual total time. The timeframe refers to the time when the project begins. The unit price (hourly rate) refers to the salary per unit of time. The planned total time is the time planned from the start to the end of the project. The planned total time varies depending on the progress of the project. The actual total time is calculated by re-estimating the time until project completion based on the progress of the project.

[0375] Applicants study the case details and decide which one they want to apply for from a large pool of cases. Before finally being accepted, applicants may interview the case recruiter, as needed. Furthermore, after selecting a specific candidate from the applicant pool as a provisional contractor, the recruiter may interview the provisional contractor before signing the contract. After signing the contract, the recruiter may interview the applicant (contractor) regarding the details of the job, depending on the progress of the job.

[0376] [Overview of the Advertisement Posting Function]

[0377] Figure 25This diagram outlines the advertising distribution functionality of matching system 1. Here, among the users (members) of matching system 1, users belonging to Company A are advertisers. Users belonging to Companies B and C work in the production technology department, respectively. Companies A and C compete with each other. Companies A and B do not compete with each other.

[0378] An advertiser uploads an advertisement related to a factory-oriented solution system to matching system 1. For example, the advertisement may be a promotional advertisement for an exhibition or business conference. The advertiser wishes to target users interested in factory-oriented solution systems. The advertiser considers users related to production technology as the target audience for the advertisement. However, the advertiser does not wish to target users of competing companies.

[0379] The matching system 1 has a function of analyzing the attributes and action histories of all users and selecting users who are estimated to be highly interested in the content of the advertisement. Therefore, even if the advertiser does not obtain information related to the characteristics of the user who wants to post the advertisement, the matching system 1 can still post the advertisement to the appropriate user. In this example, the information related to the characteristics of the user is the department (production technology) to which the target user belongs. Figure 25 In the example shown, if the issue of competitive relationship is eliminated, users belonging to the production technology departments of each of Company B and Company C can be selected as advertisement targets by the matching system 1 .

[0380] Matching system 1 has a registered advertising non-disclosure list 1291. This list is an example of data that can identify competitive relationships between companies. List 1291 shows the relationship between advertisers' company IDs and the company IDs (non-disclosure company IDs) of companies whose advertisements the advertisers do not want to be made public. Matching system 1 uses list 1291 to determine that companies A and C are in a competitive relationship. Matching system 1 excludes users belonging to company C from being targeted for advertising. Matching system 1 distributes advertisements to users of company B, which does not compete with company A, while refraining from distributing advertisements to users of company C, which does compete with company A.

[0381] Companies participating in the matching system 1 can effectively distribute their advertisements to companies they believe are interested in their products or services. The matching system 1 prevents advertisers from distributing their advertisements to companies that have competing relationships with the advertiser. Therefore, advertisers do not need to worry about their advertisements being distributed to competing companies.

[0382] In particular, the matching system 1 utilizes a platform for crowdsourcing between businesses to implement such advertising. Compared with conventional targeted advertising systems, this system has the following advantages:

[0383] Similar to matching system 1, conventional targeted advertising systems analyze user attributes and behavioral history to determine advertising targets. However, there is a significant difference in the reliability of the data analyzed between conventional targeted advertising systems and matching system 1. As will be explained later, matching system 1 extracts user attributes based on highly reliable member data registered in database 21. Consequently, the attribute information extracted for targeted advertising is extremely accurate.

[0384] Furthermore, the matching system 1 analyzes the user's activity history using the user device 500 used by the user as a recruiter or applicant. The user operating the user device 500 inputs information related to a business of particular interest to the user device 500. The user operating the user device 500 uses the user device 500 to retrieve information related to the business of particular interest to the user. It is believed that the user operating the user device 500 is more likely to use the user device 500 for business purposes and less likely to use the user device 500 for personal purposes such as hobbies. Therefore, the activity history information obtained from the user device 500 contains a large amount of information with little noise and is useful for analyzing advertising targets.

[0385] Matching system 1 offers the advantages described above over conventional targeted advertising systems. Consequently, matching system 1 enables efficient advertising delivery from a group, such as a business, to other groups, while limiting advertising delivery to competing groups. Consequently, advertisers can minimize unnecessary exposure to their ads and expect a sufficient return on their advertising costs.

[0386] In addition, the matching system 1 may also obtain information related to the characteristics of the user that the advertiser wants to target as part of the advertising information. Figure 25 In the example shown, the matching system 1 can obtain the affiliation information (production technology) of the target user from the advertiser. The matching system 1 can compare the acquired affiliation information with the affiliation information of the members registered in the database 21 to set the target range.

[0387] As described below, matching system 1 utilizes a prediction model that uses a predetermined algorithm to determine advertisement targets to distribute advertisements. Matching system 1 incorporates each user's attribute information and behavior history information into the prediction model to determine the target. Matching system 1 may also incorporate affiliation information received from advertisers into the prediction model to determine the target.

[0388] Alternatively, the matching system 1 can select users from the database 21 corresponding to the affiliation information received from the advertiser without using a predictive model, and deliver advertisements to the selected users. For example, if the affiliation information is "Production Technology," the matching system 1 refers to the "Department" column in the member database 122 to identify users belonging to "Production Technology." The matching system 1 then refers to the non-disclosure list 1291 of advertisements and excludes users from companies competing with the advertiser from the identified users. The matching system 1 delivers advertisements to the users thus selected.

[0389] Shared server 100 may also set up "advertiser members" who are not granted the authority to act as recruiters or applicants, but are granted the authority to act as advertisers. In this case, "advertiser" is set as the type of authority within member data 122. Alternatively, shared server 100 may recruit advertisers rather than limiting advertiser authority to members.

[0390] [Other databases]

[0391] In the following, the Figure 2 In addition to the various databases 121 to 127 shown, other databases are used in this embodiment.

[0392] Figure 26 1 is a diagram showing an example of the profile database 129 and the action history database 131. Figure 26 As shown, profile database 129 stores member (user) profile information by member ID. Some of this profile information may overlap with the information registered in member database 122. Profile information includes the member's name, age, and gender. It also includes affiliation information that identifies the member's affiliation (company or department). Affiliation information is an example of group information used to identify either a company or a department within a company.

[0393] Furthermore, the profile information includes the member's ability information. The member's ability information is classified by skills, experience, and qualifications. These classifications are consistent with the recruitment points of the case (see Figure 24 For example, the attribute information of each member is composed of age, gender, affiliation, and possessed ability information. When the attribute information of these members is integrated for each company, the attribute information of each company is generated.

[0394] like Figure 26 As shown, member action history information is registered for each action ID in the action history database 131. The action history information includes information indicating the member's actions in response to information displayed on the screen of the user device 500. The action ID is information for identifying each of the member's actions.

[0395] Specifically, action history information includes the member ID, action category, and action details. Action categories include, for example, clicks on information areas displayed on the screen and searches for information displayed on the screen. Action details include, for example, log information consisting of the information area clicked and the time of the click. Whenever the shared server 100 detects a member's action, new action history information is accumulated in the action history database 131.

[0396] The shared server 100 associates the member's profile information in the profile database 129 with the member's action history information in the action history database 131 .

[0397] Figure 27 FIG. 1 is a diagram showing an example of the advertisement database 132. Figure 27 As shown, advertisement information classified by advertisement ID and an advertisement non-disclosure list 1291 are registered in the advertisement database 132 .

[0398] Advertisement information includes the ad title, company ID, ad content, major, medium, and minor categories, and ad effectiveness. The advertiser is identified by the company ID within the ad information. Advertisement content includes detailed information such as the ad text, images, and dynamic images. Advertisements are categorized based on their content. Major, medium, and minor categories include names corresponding to those categories. Ad effectiveness includes numerical values ​​corresponding to the actions of users viewing the ad. For example, ad effectiveness includes the average number of clicks on the ad and the number of times the ad is displayed.

[0399] The advertising non-disclosure list 1291 shows the relationship between the advertiser's company ID and the company IDs (non-disclosure company IDs) of companies whose advertisements the advertiser does not want to be disclosed. According to the advertising non-disclosure list 1291, company A's advertisement is prohibited from being disclosed to company C, company B's advertisement is prohibited from being disclosed to company C, and company C's advertisement is prohibited from being disclosed to company A. In addition, if company A wants to avoid disclosing its advertisements to companies C and D, it registers 00C and 00D in the non-disclosure company ID column corresponding to company ID = 00A. The shared server 100 may also adopt a function that allows users to set companies whose advertisements are prohibited from being disclosed according to advertisement information (by advertisement ID). The advertising non-disclosure list 1291 is an example of information showing the competitive relationship between each of a plurality of groups.

[0400] The matching system identifies the advertiser based on the company ID included in the advertisement information. Using the advertisement private list 1291, the matching system 1 identifies companies that compete with the advertiser. The matching system 1 excludes users belonging to the identified competing companies from being targeted for the advertisement. Furthermore, the matching system 1 uses the member database 122 to identify users belonging to competing companies.

[0401] Non-disclosure list 1291 is an example of prohibited information that can identify, among multiple pieces of advertising information, advertising information that is prohibited from being associated with users belonging to the first group. The company ID included in the advertising information is an example of information used to identify the advertiser. Alternatively, a member ID can be used instead of a company ID as information used to identify the advertiser. The matching system 1 utilizes the member database 122 to determine the relationship between the member ID and the company ID.

[0402] Figure 28 133 is a diagram showing an example of the priority database 133. Figure 28 As shown, priority information is registered in the priority database 133 by priority ID. This priority information includes information related to the priority of advertisements delivered to users. This priority information includes content algorithm priority, collaborative algorithm priority, and integrated priority (final priority). Each of these priority levels includes an advertisement category and a priority value.

[0403] The shared server 100 integrates the advertisement categories and priority values ​​based on the content algorithm priority and the advertisement categories and priority values ​​based on the collaborative algorithm priority to determine an advertisement category and priority value based on the integrated priority (final priority). The shared server 100 uses the advertisement categories and priority values ​​based on the integrated priority (final priority) to determine the advertisements (targeted advertisements) to be delivered to the user.

[0404] The shared server 100 uses the trained prediction model to calculate the content algorithm priority and the collaborative algorithm priority. Figure 28 As shown, the prediction model is stored in the memory 102 of the shared server 100. The prediction model is generated by machine learning and is updated by relearning using the output of the prediction model.

[0405] As a method for extracting information that is highly preferred by users from a large amount of information, methods known as content-based filtering and collaborative filtering are known. Generally, content-based filtering is a method of recommending to a user products with labels that are highly relevant to the label information of the product that the user is browsing. Collaborative filtering is a method of determining the information recommended to the user based on the browsing history of people with similar preferences to the user. In the generation of the prediction model involved in this embodiment, these content-based filtering and collaborative filtering methods are adopted. As the label information based on content filtering, the user's attribute information is used. This is because it is assumed that recommendations are made based on the proximity of the user's attribute information (assuming that the "user" in the previous example is the "product"). On the other hand, the user's action history record information is used in collaborative filtering. This is because, like general collaborative filtering, recommendations are made based on the user's interests regardless of the user's attribute information.

[0406] Prediction models include content algorithms generated based on content filtering and collaborative algorithms generated based on collaborative filtering. In addition, the generation of prediction models can also adopt any learning method such as supervised learning and reinforcement learning.

[0407] The shared server 100 calculates the priority of the content algorithm by incorporating user-specific characteristics (such as affiliation, skills, and age) into the content algorithm. The shared server 100 calculates the priority of the collaborative algorithm by incorporating the user's action history (such as case browsing history and search history) into the collaborative algorithm.

[0408] [Description of the processing procedures related to the advertisement publishing function]

[0409] Next, refer to Figures 29 to 38 To illustrate the various processing procedures related to the advertising publishing function. Figure 29 1 is a flowchart showing a processing procedure related to the advertisement distribution function of the matching system 1 .

[0410] exist Figure 29 In the flowchart shown, first, the shared server 100 registers advertisement information in the advertisement database 132 (step Sa1). In step Sa1, the shared server 100 functions as an advertisement information registration unit.

[0411] Next, the shared server 100 acquires the user information from the profile database 129 (step Sa2). In step Sa2, the shared server 100 functions as a user information acquisition unit.

[0412] Next, the shared server 100 sets a display priority (content algorithm priority) for the advertisement based on the user's attribute information (step Sa3). The user's attribute information includes the user's job history. In step Sa3, the shared server 100 uses the content algorithm included in the prediction model to calculate the display priority.

[0413] Next, the shared server 100 sets display priority (cooperative algorithm priority) for the advertisement information based on the user's action history information (step Sa4). In step Sa4, the shared server 100 calculates the display priority using the cooperative algorithm included in the prediction model.

[0414] Next, after weighting the attribute-based priority (content algorithm priority) and the action history-based priority (collaborative algorithm priority), shared server 100 integrates the two priorities and determines the advertising information to display based on the integrated priority (step Sa5). In step Sa5, shared server 100 uses the decision algorithm. In this way, shared server 100 uses attribute information and action history information to associate one or more of the multiple advertising information with the user. Action history information includes information related to the user's actions in response to the advertising information.

[0415] The algorithm included in steps Sa3 through Sa5 constructs a prediction model. The prediction model is stored in the memory 102 of the shared server 100. Steps Sa3 through Sa5 illustrate the process of inputting attribute information and action history information into the trained prediction model to associate one or more pieces of advertising information with users belonging to a specific company (or group). The prediction model is trained through machine learning based on the attribute information and action history information.

[0416] Next, the shared server 100 acquires the determined advertisement information (step Sa6 ). In step Sa6 , the shared server 100 functions as an advertisement information acquisition unit.

[0417] Next, the shared server 100 displays the acquired advertisement information on the screen of the user's user device 500 (step Sa7 ). In step Sa7 , the shared server 100 functions as a display unit.

[0418] Next, the shared server 100 feeds back the display effect of the advertisement to the advertiser (step Sa8 ). In step Sa8 , the shared server 100 functions as an advertisement result feedback unit.

[0419] Next, shared server 100 learns (or relearns) the algorithm (step Sa9). In step Sa9, shared server 100 functions as a learning unit. Shared server 100's processor 101 updates the prediction model stored in memory 102. The prediction model is relearned (retrained) through machine learning based on user attribute information and user behavior history information.

[0420] Figure 30 This is a flowchart showing the processing procedure of the advertisement information registration unit (Sa1). The advertisement information registration unit receives the registration operation of advertisement information from the advertiser and registers the advertisement information in the advertisement database 132 (step Sa11).

[0421] For example, an advertiser operates the user device 500 to input advertisement information to the user device 500. The user device 500 transmits the input advertisement information to the shared server 100. The shared server 100 registers the received advertisement information in the advertisement database 132 in step Sa11.

[0422] Alternatively, the shared server 100 receives an operation from the server administrator and registers the advertisement information requested by the advertiser in the advertisement database 132 in step Sa11. In this manner, the shared server 100 registers the advertisement information received from the user device 500 in the advertisement database 132.

[0423] The processing of the advertisement information registration unit is thus completed. In addition, the advertisement information registration unit registers the advertisement information including the category information of the advertisement. If the advertiser cannot determine the category, the server administrator or the like assists the advertiser.

[0424] Figure 31 This is a flowchart showing the processing procedure of the user information acquisition unit Sa2. The user information acquisition unit acquires user information from the profile database 129 and the action history database 131 (step Sa21). The user information acquisition unit acquires user attribute information from the profile database 129 and acquires user action history information from the action history database 131. The user information acquisition unit performs the above processing for all users. This completes the processing of the user information acquisition unit.

[0425] Figure 32 This is a flowchart showing the processing procedure related to the content algorithm (Sa3). The shared server 100 performs processing using the content algorithm according to the following procedure. First, the shared server 100 extracts the user's attribute information (step Sa31). Next, the shared server 100 applies the attribute information to the content algorithm (step Sa32).

[0426] Next, the shared server 100 creates advertisement priority information using the content algorithm (step Sa33). The shared server 100 registers the created advertisement priority information as "content algorithm priority" in the priority database 133. The content algorithm priority includes advertisement classification and priority value (see Figure 28 ). The shared server 100 executes the above processing for all users. With the above, the processing of the content algorithm is completed.

[0427] In addition, the shared server 100 may store the generated advertisement priority information in a cache instead of storing it in the priority database 133 .

[0428] Figure 33 This is a flowchart showing the processing procedure of the collaborative algorithm (Sa4). The shared server 100 executes the processing using the collaborative algorithm according to the following procedure. First, the shared server 100 extracts the user's attribute information (step Sa41). Next, the shared server 100 feeds the attribute information into the collaborative algorithm (step Sa42).

[0429] Next, the shared server 100 creates advertisement priority information using the collaborative algorithm (step Sa43). The shared server 100 registers the created advertisement priority information as "collaborative algorithm priority" in the priority database 133. The collaborative algorithm priority includes advertisement classification and priority value (see Figure 28 The shared server 100 executes the above processing for all users. The above processing of the collaborative algorithm ends.

[0430] In addition, the shared server 100 may store the generated advertisement priority information in a cache instead of storing it in the priority database 133 .

[0431] Figure 34 The shared server 100 executes the process using the decision algorithm according to the following procedure. First, the shared server 100 obtains the content algorithm priority and the cooperation algorithm priority from the priority database 133 (step Sa51).

[0432] Next, the shared server 100 puts the content algorithm priority and the collaboration algorithm priority into the decision algorithm (step Sa52). Next, the shared server 100 uses the decision algorithm to create the integrated advertising priority (step Sa53). The decision algorithm determines the deviation between content and collaboration, etc.

[0433] Next, the shared server 100 registers the created advertisement priority as "integration priority (final priority)" in the priority database 133. With the above, the algorithm determination process is completed.

[0434] In addition, the shared server 100 may store the integrated advertisement priority information in a cache instead of in the priority database 133. In addition, the shared server 100 may use either the content algorithm or the collaborative algorithm to determine the final advertisement priority.

[0435] Figure 35 This is a flowchart showing the processing procedure of the advertisement information acquisition unit (Sa6). First, the advertisement information acquisition unit acquires the final integrated advertisement priority information from the priority database 133 (step Sa61). Specifically, the advertisement information acquisition unit acquires the "integrated priority" from the priority database 133.

[0436] Next, the advertisement information acquisition unit acquires advertisement information from the advertisement database 132 (step Sa62). Next, the advertisement information acquisition unit refers to the advertisement non-disclosure list 1291 registered in the advertisement database 132 to exclude advertisements for competing companies (step Sa63).

[0437] More specifically, the advertising information acquisition unit identifies the company to which the advertiser belongs based on the company ID included in the advertising information. The advertising information acquisition unit then references the public list 1291 to identify competing companies of the advertiser's company. The advertising information acquisition unit identifies the company to which the user, the target of the advertisement, belongs based on the user's profile information. Based on these identification results, the advertising information acquisition unit excludes advertisements intended for competitors from the large amount of advertising information selected as display candidates for display to the user.

[0438] Next, the advertisement information acquisition unit determines the advertisement information to be displayed to the user from among a large amount of advertisement information based on the integration priority (step Sa64 ).

[0439] Figure 36 This is a flowchart showing the processing procedure of the display unit (Sa7). The display unit displays the advertisement information determined by the advertisement information acquisition unit on the screen of the user device 500 of the target user (step Sa71). With the above, the processing of the display unit is completed.

[0440] Figure 37 Flowchart showing the processing procedure of the advertisement result feedback unit (Sa8): First, the advertisement result feedback unit acquires action history information from the action history database 131 (step Sa81).

[0441] Next, the advertising result feedback unit retrieves the advertisement information from the advertisement database 132 (step Sa82). Next, the advertising result feedback unit calculates an indicator of the advertisement's display effectiveness (step Sa83). An example of an indicator of the advertisement's display effectiveness is the click-through rate (CTR). The CTR is calculated by dividing the number of clicks on the advertisement by the number of times the advertisement was displayed.

[0442] Next, the advertising result feedback unit registers the advertising display effectiveness index value in the advertising database 132 (step Sa84). Information related to the advertising display effectiveness is used to improve the accuracy of the matching algorithm and to communicate the advertising display effectiveness to the advertiser. This information related to the advertising display effectiveness may include, for example, the viewing time of images (including dynamic images) related to the advertisement. Next, the advertising result feedback unit displays the advertising display effectiveness index value on the screen of the advertiser's user device 500 (step Sa85). This completes the processing of the advertising result feedback unit.

[0443] Figure 38 This is a flowchart showing the processing procedure of the learning unit (Sa9). First, the learning unit accesses the profile database 129 and the advertisement database 132 to obtain information on all users (attribute information and behavior information) and advertisement information (step Sa91). Next, the learning unit obtains algorithm parameter information (content algorithm and collaborative algorithm) from the prediction model (step Sa92).

[0444] Next, the learning unit updates the algorithm's parameter information (step Sa93). Before the learning unit begins learning, hyperparameters are used as algorithm parameters. Algorithm hyperparameter values ​​can also be determined using other learning algorithms, such as deep learning. Furthermore, even parameters other than hyperparameters can be manually updated without relying on a learning algorithm such as deep learning.

[0445] Next, the learning unit learns the algorithm based on the index value of the advertising display effect, etc. (step Sa94). Next, the learning unit stores the learned algorithm as an updated prediction model in the memory 102 of the shared server 100 (step Sa95). With the above, the processing of the learning unit ends.

[0446] In addition, while this example describes the use of a prediction model trained through machine learning to determine which advertisements to display to users, the shared server 100 may also determine which advertisements to display to users based on rules defined by a human-created program, rather than using such a prediction model.

[0447] As described above, matching system 1 effectively utilizes a platform for matching recruiters with applicants to deliver targeted advertising. In particular, matching system 1 analyzes user information based on their attribute information and their activity history, and provides users with advertisements that match their needs. Matching system 1 also allows for limiting the scope of advertisement disclosure.

[0448] This allows advertisements to be targeted to specific companies, industries, or groups. Furthermore, matching system 1 ensures the reliability of information about the user's company, enabling more precise targeted advertising. Furthermore, matching system 1 can provide feedback to the algorithm regarding ad display results, improving the accuracy of the matching algorithm. Consequently, matching system 1 enables more precise matching, enabling the delivery of cost-effective advertising to users.

[0449] As described so far, the shared server 100 communicates with multiple user devices 500, including user devices 500 operated by users belonging to a first group (any of companies A, B, C, etc.), via the communication interface 104. The shared server 100 accesses the database 120 (profile database 129, advertisement database 132), which contains group information (user affiliation information) identifying each of the multiple groups, multiple advertisements, and prohibition information (advertisement non-disclosure list 1291) identifying advertisements that are prohibited from being associated with users belonging to the first group. The shared server 100 associates one or more of the multiple advertisements with the users belonging to the first group (step Sa64), and based on the association, distributes the one or more advertisements to the first user device (step Sa71). The shared server 100 associates the advertisements with the users belonging to the first group, excluding the advertisements for which association has been prohibited by the prohibition information (step Sa63).

[0450] In order to utilize crowdsourcing to find more suitable talent, it is desirable to expand the scope of crowdsourcing beyond specific companies or a small number of companies. In this case, it is necessary to consider the interests of the recruiter (who takes orders for the job) and the applicants who will apply for the job. In this embodiment, the recruiter device 200 transmits the job information of the job taker and public information indicating the scope of disclosure of the job information to the shared server 100. The shared server 100 registers the job information and the public information in the database 120. Based on the public information, the shared server 100 determines which job information in the registered job information in the database 120 is permitted to be disclosed to applicants, and provides the permitted job information to the applicant device 300. Therefore, according to this embodiment, it is possible to select suitable applicants while taking into account the interests of the recruiter and applicants.

[0451] In the embodiment described above, "groups by company" and "groups by department within the same company" are examples of "groups." For example, applicants who are not affiliated with a company, such as freelancers, can constitute a single "group." Alternatively, a "company group" can be formed by multiple companies.

[0452] In this embodiment, “companies forming a social relationship” is an example of a “social group”.

[0453] In the present embodiment, the “non-disclosure target” information included in the public information is an example of “information capable of identifying a target person to whom disclosure of business information is prohibited”.

[0454] The communication ( Figure 11 S9) is performed in a logical communication path identified by the member ID of the approver. "The approval unit 147 receives approval information in such a communication path" is an example of "receiving approval notification in a communication accompanied by the identification information of the approver of the first applicant."

[0455] In this embodiment, the "applicant evaluation summary" registered in the evaluation summary database 127 is an example of "evaluation information based on the evaluation received from the recruiter device 200 functioning as an evaluator device." In this embodiment, the "recruiter evaluation summary" registered in the evaluation summary database 127 is an example of "evaluation information based on the evaluation received from the applicant device 300 functioning as an evaluator device."

[0456] exist Figure 91 shows only one example of the data registered in the evaluation summary database 127. In this embodiment, it is also assumed that members belonging to company A evaluate members belonging to companies A, B, C, etc., who act as recruiters, from the perspective of applicants. In this embodiment, it is also assumed that members belonging to company B evaluate members belonging to companies A, B, C, etc., who act as recruiters, from the perspective of applicants. In this embodiment, it is also assumed that members belonging to company A evaluate members belonging to companies A, B, C, etc., who act as applicants, from the perspective of recruiters. In this embodiment, it is also assumed that members belonging to company B evaluate members belonging to companies A, B, C, etc., who act as applicants, from the perspective of recruiters.

[0457] In this embodiment, the "recruiter device 200A" operated by a recruiter belonging to Company A functions as an evaluator device and is an example of a "first evaluator device (recruiter-side first evaluation device) operated by one or more evaluators belonging to the first group." In this embodiment, the "applicant device 300A" operated by an applicant belonging to Company A functions as an evaluator device and is an example of a "first evaluator device (applicant-side first evaluation device) operated by one or more evaluators belonging to the first group."

[0458] In this embodiment, the "recruiter device 200B" operated by a recruiter belonging to Company B functions as an evaluator device and is an example of a "second evaluator device (recruiter-side second evaluation device) operated by one or more evaluators belonging to a second group different from the first group." In this embodiment, the "applicant device 300B" operated by an applicant belonging to Company B functions as an evaluator device and is an example of a "second evaluator device (applicant-side second evaluation device) operated by one or more evaluators belonging to a second group different from the first group."

[0459] exist Figure 21 In FIG, the system department and the planning department are exemplified as departments of company B. In this embodiment, "one of the system department and the planning department" is an example of the "first subgroup" included in the first group, and the other is an example of the "second subgroup" included in the first group.

[0460] Shared server 100 extracts job information from the list in job case database 124 that indicates the applicant's work hours do not exceed the upper limit, based on the assumed working hours registered in job case database 124, the upper limit of side job hours registered in company database 121, the actual side job hours registered in side job database 125, and the estimated side job hours registered in side job database 125. Specifically, if an applicant has multiple side jobs, for example, shared server 100 calculates the total actual side job hours by summing the actual side job hours corresponding to each side job, and calculates the total estimated side job hours by summing the estimated side job hours corresponding to each side job.

[0461] Shared server 100 calculates the total side job time by adding the calculated total actual side job time and the calculated total side job time. Shared server 100 calculates the applicant's available side job time by subtracting the applicant's total side job time from the applicant's maximum side job time. Shared server 100 searches the list in recruitment case database 124 for cases that can be handled with the calculated available side job time.

[0462] At this point, shared server 100 calculates the time required to respond to each job offer based on the assumed working hours in job offer database 124 and searches for job offers that fall within the time available for side jobs. Here, "side job upper limit time" is an example of the upper limit of an applicant's working hours, "side job actual time" is an example of the time an applicant has actually worked as a performance, and "side job estimated time" is an example of the estimated time expected to be the applicant's working hours. The upper limit time applies not only to side jobs but also to the total time spent on the main job and side jobs.

[0463] The first upper limit time may not be the upper limit time for the side job, but may be the upper limit time for all tasks including the main job and the side job. The first actual time and the first estimated time may not only be the time for the side job, but also the total time for all tasks including the side job and the main job.

[0464] The recruiter device 200 and the applicant device 300 are not only equipped with Figure 2All of the devices shown, including the processor, memory, communication interface, and input / output interface, may also be thin client systems utilizing VDI (Virtual Desktop Infrastructure). A thin client system utilizing VDI transfers a desktop environment located on a server to a remote terminal for use. The recruiter device 200, the applicant device 300, and the shared server 100 do not necessarily need to be independent devices. When utilizing a thin client system such as the one described above, the functions of the recruiter device 200, the applicant device 300, and the shared server 100 can be provided on the same integrated server.

[0465] The database 120 is not limited to a relational database, and an object-based database, a NoSQL-based database, or the like may be used.

[0466] The shared server 100 is an example of a computing device. A computing device can also be composed of a server (a local server, a cloud server, etc.), a serverless system, etc. Here, a local server refers to a server that is installed and managed in a device managed within the company. A cloud server refers to a server provided by another operator via the Internet (a rented server). A serverless system is a system that is unaware of the existence of a server and can use computing / storage functions only when needed. Computing devices include servers and serverless systems. Servers include local servers and cloud servers.

[0467] <Variation 1>

[0468] Next, refer to Figures 39 to 41 Modification 1 will be described. In Modification 1, a reverse invitation function that can encourage a recruiter to recruit a person selected from a large number of members to a recruitment business will be described.

[0469] [Background of the reverse invitation feature]

[0470] In crowdsourcing, recruiters typically publish job postings and wait for applications from interested parties. However, this recruitment method can take a long time to receive responses from applicants. Furthermore, it's unclear whether applicants with the skills the recruiter is looking for will actually apply.

[0471] Therefore, it is possible to have a recruiter search for members and specify appropriate members (reverse solicitation). However, if the recruiter only knows the member ID and the member's name, it is difficult for the recruiter to specify the desired applicant. In addition, in order to prevent confidential information from being leaked to rival companies, the member information of rival companies must be excluded from the search results.

[0472] In light of this background, in Modification 1, search results containing detailed member profile information are provided to recruiters who have performed a member search. Furthermore, in Modification 1, member information for companies that are competitors of the recruiter's company is excluded from the search results. Modification 1 is described in detail below using the accompanying drawings.

[0473] Figure 39 This is a diagram for explaining the functions of the shared server 100 , the recruiter device 200 , and the applicant device 300 according to the first modification.

[0474] like Figure 39 As shown, shared server 100 functionally includes, in addition to member search unit 143, reverse invitation request unit 161, reverse invitation approval request unit 162, and reverse invitation request acceptance notification unit 163. These various functions are implemented by processor 101, memory 102, storage device 103, and communication interface 104 included in shared server 100.

[0475] As described above, the member search unit 143 has the function of searching for members of the matching system 1. In particular, in Modification 1, the member search unit 143 has the function of providing the searcher with detailed profile information of the members. When the recruiter's search operation is accepted, the recruiter device 200 performs a member search process (step S21). In particular, in step S21, the recruiter device 200 accepts a search operation for the recruiter to make a reverse invitation. The member search unit 143 provides the recruiter device 200 with the information of the members registered in the member database 122. The provided member information includes the member's detailed profile information. However, the member search unit 143 excludes the member information of companies that are rivals to the recruiter's company from the search results.

[0476] The recruiter device 200 receives member information (search results) from the member search unit 143 and displays the member information as the search results on the display 205 (step S22). The recruiter device 200 then accepts an operation from the recruiter to select an applicant from the search results. Specifically, the recruiter selects a member to make a reverse invitation based on the search results and implements the reverse invitation by operating the recruiter device 200 (step S23). The recruiter device 200 transmits the member ID of the member to be reversely invited to the shared server 100.

[0477] The reverse invitation request unit 161 receives the member ID of the member targeted for the reverse invitation from the recruiter device 200. The reverse invitation request unit 161 identifies the member corresponding to the received member ID. The reverse invitation request unit 161 notifies the applicant device 300 of the member targeted for the reverse invitation that the reverse invitation request has been received. This notification may also include information about the recruitment case targeted for the reverse invitation. The member targeted for the reverse invitation receives the reverse invitation request through the applicant device 300. The "request" received here is an example of "information encouraging the applicant to apply." The member targeted for the reverse invitation decides whether to accept the reverse invitation request. The member targeted for the reverse invitation can use the applicant device 300 to accept or reject the reverse invitation request. For example, the applicant device 300 accepts the reverse invitation request (step S24). The applicant device 300 that accepts the reverse invitation request transmits the application information to the reverse invitation approval request unit 162.

[0478] The reverse invitation approval request unit 162 sends the subordinate's application information to the applicant's supervisor. Based on the relationship between the applicant's member ID and the supervisor's member ID registered in the member database 122, the reverse invitation approval request unit 162 identifies the supervisor's member ID, who is the applicant's manager. The applicant's supervisor confirms the application information on his or her applicant device 300 and approves the application (step S25).

[0479] The reverse invitation commission acceptance notification unit 163 receives approval information from the applicant's supervisor. Subject to receiving the approval information, the reverse invitation commission acceptance notification unit 163 accepts the applicant's application. The reverse invitation commission acceptance notification unit 163 notifies the recruiter device 200 that the application from the member who made the reverse invitation has been accepted. Based on this notification, the recruiter device 200 notifies the recruiter that the reverse invitation has been accepted (step S26). More specifically, the recruiter device 200 displays a message on the display 205 notifying the recruiter that the reverse invitation has been accepted.

[0480] Figure 40 1 is a diagram showing an example of a member database 122A according to Modification 1. Figure 40 In the member database 122A shown, compared to Figure 4 The member database 122 shown has profile information and profile disclosure information indicating whether the profile is to be disclosed.

[0481] The matching system 1 grants members the ability to register and modify their profile information in the member database 122A using the applicant device 300. Members register various profile information in the member database 122A using the applicant device 300. This profile information includes, for example, the member's SPI (Synthetic Personality Inventory) information, their job history, their performance, and their qualifications.

[0482] Members use the applicant device 300 to set their profile disclosure information. Members whose profile disclosure information is set to "Yes" have their profile information provided to searchers. Members whose profile disclosure information is set to "No" have their profile information not provided to searchers. Based on the settings selected by each member, the shared server 100 registers the profile disclosure information in the member database 122A. In this manner, the shared server 100 accepts input from multiple members indicating whether or not to allow their profile information to be included in search results.

[0483] Here, an example of determining whether to allow disclosure of a member's profile information based on the setting of profile disclosure information is described. However, the shared server 100 can also accept setting operations for whether to allow disclosure according to the type of profile information. Thus, for example, a member can set performance and qualifications as public objects but set SPI information as non-public objects. Or, in the case where the profile information includes age, the member can set age as non-public objects and set other profile information as public objects. In this case, the shared server 100 registers multiple profile information of multiple registrants (members) in the member database 122A. The shared server 100 accepts input from multiple registrants for setting the scope of disclosure as a search result in multiple profile information.

[0484] Figure 41 1 is a flowchart showing a processing procedure of reverse invitation member search processing according to Modification 1. The processing based on this flowchart is executed by the shared server 100 .

[0485] First, the shared server 100 accepts a search request from a searcher to search for members suitable for a recruitment case (step S211). Here, the searcher is a recruiter with a recruitment case. To make a reverse offer to members with skills suitable for the recruitment case, the recruiter uses their recruiter device 200 to search for members. The recruiter's search request is accepted by the shared server 100 in step S211. The search request may also include the searcher's member ID and the case ID of the recruitment case.

[0486] Next, the shared server 100 identifies the company to which the searcher belongs from the member database 122A and the company database 121 (step S212 ). Next, the shared server 100 identifies the community to which the searcher belongs from the community database 123 (step S213 ).

[0487] Next, the shared server 100 determines the disclosure level and the non-disclosure company ID list of the recruitment case registered in the recruitment case database 124 (step S214). Next, the shared server 100 extracts members who can be disclosed to the searcher (step S215).

[0488] More specifically, the shared server 100 identifies companies whose recruitment projects held by the searcher (recruiter) should not be disclosed based on the list of non-disclosed companies and their disclosure levels in the recruitment project database 124. The shared server 100 determines members belonging to such companies as members whose information cannot be disclosed to the searcher. The shared server 100 then extracts members other than those belonging to such companies as members whose information can be disclosed to the searcher.

[0489] Next, the shared server 100 refers to the member database 122A and excludes the profile information of the member whose profile information is set to non-public from the extracted member information (step S216 ).

[0490] Next, shared server 100 transmits the extracted member information to the search request source (step S217), terminating the process according to this flowchart. Recruiter device 200, acting as the search request source, receives the member information transmitted from shared server 100 and displays it on display 205. The information displayed on display 205 shows the ID, name, and profile information of each extracted member. However, for members who have set their profile information to private, only the member's ID and name are displayed, without the profile information.

[0491] As described above, according to Modification 1, recruiters can refer to detailed member profile information to search for members deemed most suitable for recruitment work and make counter-invitations to these members. Furthermore, members of companies that are competitors of the recruiter's company or community are excluded from the members displayed as search results. This prevents recruiters from offering work to members of such rival companies. Furthermore, since members can decide whether to disclose their profile information, a system that respects the free will of each member can be provided.

[0492] Furthermore, members may be able to set not only whether to disclose their profile information but also whether to disclose their name. Alternatively, profile information may be divided into several categories, and members may be able to set whether to disclose their profile information by category.

[0493] By adding the invitation functionality described above to the matching system 1, recruiters can confirm the profile information of members who are allowed to view recruitment cases. Furthermore, recruiters can encourage members they want to advertise to apply. Furthermore, recruitees can encourage members who have applied to view case information and agree or decline to apply. Furthermore, each member can decide whether to disclose their profile information when registering or editing their member information. This allows recruiters to proactively select invitation targets and ensure that the best candidates are engaged in business as soon as possible.

[0494] <Variation 2>

[0495] Next, refer to Figures 42 to 46 Modification 2 will be described. In modification 2, a member group application function will be described in which a plurality of members can apply for a recruitment task as a group.

[0496] [Background on the Member Group Recruitment Feature]

[0497] In crowdsourcing, a recruiter typically posts job postings, and individuals interested in the content apply. However, there are also many cases where a team of multiple individuals is required or desired to handle comprehensive tasks, ranging from business planning to acquiring related intellectual property rights. Therefore, if the number of recruits is limited to one, it can be difficult for the prospective hire to take on more work than they can handle individually.

[0498] In view of such a background, in Modification 2, a member group application function is provided, which enables a plurality of members to apply for recruitment work as a group. Modification 2 will be described in detail below.

[0499] Figure 42 : is a block diagram showing the configuration of the shared server 100, the recruiter device 200, and the applicant device 300 according to Modification 2. Figure 42 As shown in the block diagram, compared to Figure 2 The block diagram shown in FIG. 1 adds a member group database 128. Figure 42 In the recruitment case database 124A shown, Figure 6 The recruitment case database 124 shown has been added with a function of being able to register recruitment cases that allow applications to be made by member groups.

[0500] Member groups consisting of multiple members are registered in the member group database 128. Recruiters can use the recruiter device 200 to register recruitment cases that allow applications from member groups in the recruitment case database 124A. Applicants can use the applicant device 300 to apply for recruitment cases that allow applications from member groups using the member groups registered in the member group database 128.

[0501] Figure 43 This figure shows an example of the member group database 128 according to Modification 2. Member group information is registered in the member group database 128. The member group information includes a group ID for identifying the member group, a company ID of the company to which each member of the member group belongs, and a member ID of each member of the member group.

[0502] Hereinafter, member groups corresponding to respective group IDs may be referred to as member group G1, member group G2, member group G3, . . . using group IDs.

[0503] Member group G1 is composed of three members identified by member ID = P1, P2, P5. Since the company ID registered corresponding to member group G1 is 00A, it can be known that the three members all belong to company A.

[0504] Member group G2 consists of two members identified by member IDs P1 and P3. Since the company IDs registered for member group G2 are 00A and 00B, it can be seen that one of the two members belongs to company A and the other to company B. As can be seen by comparing member groups G1 and G2, member ID P1 is registered in both member groups G1 and G2. Therefore, member P1 belongs to both member groups.

[0505] Member group G3 is composed of four members identified by member ID = P4, P7, P8, P14. Since the company ID registered corresponding to member group G3 is 00C, it can be known that the four members all belong to company C.

[0506] like Figure 42 As shown, the member group database 128 is stored in the storage device 103 of the shared server 100. Members form a member group with the consent of other members they know through the same company or community, and register the member group in the member group database 128. A "member group" is an example of an "applicant group."

[0507] Figure 44 This is a diagram showing an example of the recruitment case database 124A according to the second modification. Figure 44 The recruitment case database 124A shown is Figure 6 Compared to the recruitment case database 124 shown, recruitment method information is added. The recruiter sets the recruitment method by operating the recruiter device 200. The shared server 100 registers the recruitment method based on the setting in the recruitment case database 124A in a manner associated with the work information.

[0508] Recruiters can select a recruitment method from groups and individuals. If a recruiter does not select a recruitment method, the recruitment case is deemed to have a recruitment method that is neither limited to groups nor individuals. Cases where the recruitment method is set to group are set to be accepted only by the member group. Cases where the recruitment method is set to individual are set to be accepted only by individual members. Cases where the recruitment method is not limited are set to be accepted by either the member group or the individual. "Information on the recruitment method" is an example of "information that can determine whether the business of the recruitment order-taker is a business that should be jointly applied for by multiple recruiters."

[0509] Figure 45 1 is a diagram for explaining the functions of the shared server 100, the recruiter device 200, and the applicant device 300 according to Modification 2. Figure 45 In, compared to Figure 11 , a determination unit 145A is added to the shared server 100. Figure 45 In, compared to Figure 11 , step S7A is added after step S7, and step S8A of group application is adopted instead of step S8 of application.

[0510] Here, it is assumed that the applicant belongs to a plurality of member groups. The applicant operates the applicant device 300 to search for recruitment cases (step S6). The applicant device 300 sends a search request to the case extraction unit 145 of the shared server 100.

[0511] When the case extraction unit 145 receives a search request, Figure 11 As described above, cases that applicants are permitted to view are extracted from the recruitment cases registered in the recruitment case database 124. The cases extracted by the case extraction unit 145 include cases where the recruitment method is "Group," "Individual," or "Unrestricted." The case extraction unit 145 transmits the extracted recruitment cases to the applicant device 300. The applicant device 300 receives the recruitment cases from the case extraction unit 145. The applicant device 300 displays the received recruitment cases on the display 305 (step S7).

[0512] The display 305 displays the disclosure level, project title, estimated working hours, estimated period, project content, and recruitment method for each recruitment case. If the applicant wishes to apply as a member group, he or she uses the operation unit 306 such as a mouse and keyboard to select a case with the recruitment method set to "group" or "unlimited" after specifying the member group. Based on the applicant's operation, the applicant's device 300 accepts the member group and the case he or she wishes to apply for (step S7A). The applicant's device 300 sends the group ID of the accepted member group and the case ID of the accepted case to the shared server 100. The judgment unit 145A of the shared server 100 obtains the group ID and the case ID.

[0513] The determination unit 145A accesses the member group database 128 to identify the member ID registered in correspondence with the acquired group ID. The determination unit 145A accesses the member database 122 to identify the company ID corresponding to the identified member ID.

[0514] The determination unit 145A accesses the community database 123 to identify the community ID of the community to which the company with the identified company ID belongs. The determination unit 145A accesses the recruitment case database 124A to identify the company ID (the company ID of the recruiter), the private company ID, the disclosure level, and the recruitment method registered corresponding to the acquired case ID.

[0515] Based on the information identified above, the determination unit 145A determines whether the recruitment case accepted by the applicant device 300 is a case in which the member group specified by the applicant is permitted to apply. In other words, the determination unit 145A determines whether the member group is permitted to apply.

[0516] For example, if a member in the member group belongs to a company listed in the non-public company ID list corresponding to the job posting, the determination unit 145A will not allow the member group to apply. Alternatively, if a member in the member group belongs to a company outside the community despite the job posting's public level being "within the community," the determination unit 145A will not allow the member group to apply.

[0517] The determination unit 145A returns the determination result to the applicant device 300. Figure 45 The flow chart for the case where the determination unit 145A permits the application from the member group is shown in FIG. If the determination unit 145A permits the application from the member group, the applicant device 300 accepts the application from the member group (step S8A). For example, the applicant device 300 displays a screen on the display 305 indicating the acceptance of the application accepted in step S7A and a screen confirming whether to apply. The applicant selects the application using the operation unit 306, such as a mouse or keyboard.

[0518] When the applicant device 300 receives an application from a member group (step S8A), it transmits the application information to the shared server 100. The application unit 146 of the shared server 100 acquires the application information. Figure 11 The description is the same. However, the application unit 146 sends the application information to the supervisor of each member belonging to the member group. Therefore, the application approval process in step S9 is performed for each supervisor of each member belonging to the member group. Therefore, the approval unit 147 receives approval information indicating approval of the subordinate's application or rejection information indicating whether the subordinate's application is rejected from multiple supervisors.

[0519] The approval unit 147 accepts the applicant's application only when it has received approval information from the superiors of each member belonging to the member group. The approval unit 147 that has accepted the applicant's application sends the application information to the recruiter device 200. Figure 11 As described above, the recruiter device 200 displays the application details on the display 205 (step S10). The recruiter inputs the result of the hiring / rejection decision to the recruiter device 200. The recruiter device 200 receives the input result (step S11) and transmits the received hiring / rejection decision to the notification unit 148 of the shared server 100.

[0520] The notification unit 148 transmits the application result (result of acceptance or rejection) to the applicant's applicant device 300 and the supervisor's (manager's) applicant device 300. However, the notification unit 148 transmits the application result to the supervisor of each member belonging to the member group.

[0521] The applicant's device 300 and the applicant's supervisor's device 300 display the application result on the display 305 (steps S12 and S13). The applicant and the supervisor of each member in the member group confirm the application result by viewing the display 305.

[0522] Figure 46 1 is a diagram for explaining the process of registering a recruitment case according to Modification 2 in the recruitment case database 124A. Figure 46 In, compared to Figure 14 , a recruitment method is added to the business information input to the recruiter device 200.

[0523] In Variation 2, when a recruiter registers a recruitment case and inputs the business information and public information of the recruitment case into the recruiter device 200, they can include the recruitment method of the recruitment case in the business information. The recruitment method can be either group or individual. The case registration unit 144 of the shared server 100 registers the recruitment case in the recruitment case database 124A in a manner that includes the recruitment method selected by the recruiter (step S1442). If the recruiter does not select a recruitment method, the case registration unit 144 registers information in the recruitment case database 124A indicating that the recruitment method is not limited. Figure 46 Other contents shown are the same as those already explained Figure 14 The same, so the description is not repeated here.

[0524] As described above, according to Variation 2, multiple members can apply for recruitment projects as a group. Furthermore, according to Variation 2, whether to approve a member group's application is determined based on the relationship between the recruiter's company and community and the companies and communities to which each member of the member group belongs. This prevents a member group containing members of a competing organization from accepting a recruitment project from an applicant.

[0525] By adding the member group application function described above to the matching system 1, a system can be provided in which the order-receiving side can browse recruitment cases and apply for them as a member group. This allows the matching system 1 to handle large-scale business that requires teamwork and order placement.

[0526] The present embodiment described above has the following configurations.

[0527] (a) In the matching system, the recruiter device sends the business information of the recruited order-taker and the public information indicating the disclosure scope of the business information to the computing device. The computing device registers the business information together with the public information in a database. The computing device determines, based on the public information, the business information registered in the database that is allowed to be disclosed to the first applicant, and provides the business information allowed to be disclosed to the first applicant to the first applicant device.

[0528] (b) The matching system further includes a second applicant device operated by a second applicant different from the first applicant, and the computing device determines, based on the public information, business information registered in the database that is permitted to be disclosed to the second applicant, and provides the business information permitted to be disclosed to the second applicant to the second applicant device.

[0529] (c) The matching system further includes a third applicant device operated by a third applicant different from the first applicant and the second applicant, a plurality of disclosure levels are set for the public information, and the calculation device determines whether to allow disclosure for each of the first to third applicants based on the disclosure level.

[0530] (d) In the matching system, the first applicant belongs to a first group, and the second applicant belongs to a second group different from the first group. The multiple disclosure levels include a first level and a second level. The first level corresponds to the following situation: business information is allowed to be disclosed to the first applicant, and business information is prohibited to be disclosed to applicants who do not belong to the first group. The second level corresponds to the following situation: business information is allowed to be disclosed to applicants who belong to the first group and any community group that has formed a community relationship with the first group, and business information is prohibited to be disclosed to applicants who do not belong to the first group and any community group.

[0531] (e) In the matching system, the first applicant belongs to a first group, and the second applicant belongs to a second group different from the first group. Multiple disclosure levels include a first level, a second level, and a third level. The first level corresponds to the following situation: business information is allowed to be disclosed to the first applicant, and business information is prohibited to be disclosed to applicants who do not belong to the first group. The second level corresponds to the following situation: business information is allowed to be disclosed to applicants who belong to the first group and any social group that has formed a social relationship with the first group. The third level corresponds to the following situation: business information is allowed to be disclosed to applicants who belong to the first group and a social group different from the second level that has formed a social relationship with the first group, and business information is prohibited to be disclosed to applicants who do not belong to the first group and any social group.

[0532] (f) In the matching system, the plurality of disclosure levels include a disclosure level corresponding to a case where disclosure of the business information to the applicant is permitted regardless of a group to which the applicant belongs.

[0533] (g) In the matching system, attribute data capable of identifying a social group is registered in a database, and the computing device identifies applicants who are allowed to disclose job information based on the public information and the attribute data.

[0534] (h) In the matching system, the recruiter device accepts an operation to input a target group for which disclosure of business information is prohibited, and sends information that can identify the accepted target group to the computing device. Even if the disclosure level is a level that allows disclosure of business information to the target group, the computing device prohibits disclosure of business information to applicants belonging to the target group.

[0535] (i) In the matching system, a first applicant belongs to a first company, and a second applicant belongs to a second company different from the first company.

[0536] (j) In the matching system, the computing device accepts a request from a recruiter device to retrieve information of a plurality of registrants registered in a database, provides a search result based on the accepted request to the recruiter device, the recruiter device accepts an operation by the recruiter to select an applicant recommender to be recommended as an applicant from the search result, sends identification information of the selected applicant recommender to the computing device, and the computing device sends a message urging the applicant device of the selected applicant recommender to apply.

[0537] (k) In the matching system, the calculation device registers a plurality of profile information of each of a plurality of registrants in a database, and the calculation device accepts input from each of the plurality of registrants for setting a range of the plurality of profile information to be disclosed as a search result.

[0538] (l) In the matching system, the recruiter device sends recruitment method information to the computing device, and the computing device registers the recruitment method information in a database in a manner that establishes a correspondence with the business information, wherein the recruitment method information is used to determine whether the business of the recruited order-taker is a group business that can be accepted when multiple applicants apply together, or a business that can be accepted when a single applicant applies.

[0539] (m) In the matching system, the computing device registers an applicant group consisting of a plurality of applicants in a database, and can accept applications from the applicant group for business information that is permitted to be disclosed to all applicants belonging to the applicant group.

[0540] [Way]

[0541] The following lists the aspects of the present disclosure.

[0542] (Item 1) The matching system described in Item 1 provides advertisements matched with each of a plurality of groups including an enterprise, and the matching system comprises: a plurality of user devices; and a computing device that communicates with each of the plurality of user devices and can access a database, wherein the plurality of user devices includes a first user device operated by a user belonging to a first group, and the database contains group information capable of identifying each of the plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information in the plurality of advertisement information that prohibits the advertisement information from being matched with the user belonging to the first group. The computing device matches one or more of the plurality of advertisement information with the user belonging to the first group, publishes the one or more advertisement information to the first user device based on the established correspondence, and the computing device excludes the advertisement information identified by the prohibition information and then matches the advertisement information with the user belonging to the first group.

[0543] (Item 2) The matching system described in Item 2 is a matching system described in Item 1, wherein the plurality of user devices include a second user device operated by an advertiser belonging to a group different from the first group, the second user device sends the advertiser's advertising information to the computing device, and the computing device registers the advertising information received from the second user device in a database.

[0544] (Item 3) The matching system according to Item 3 is the matching system according to Item 1 or Item 2, wherein the group information includes information for specifying either the enterprise or a department within the enterprise.

[0545] (Item 4) The matching system according to Item 4 is the matching system according to any one of Items 1 to 3, wherein the prohibition information includes information indicating a competitive relationship between the plurality of groups.

[0546] (Item 5) In the matching system described in any one of Items 1 to 4, the database includes attribute information of the user and action history information of the user, and the computing device uses the attribute information and action history information to establish a correspondence between one or more of the multiple advertising information and the user belonging to the first group.

[0547] (Item 6) In the matching system described in Item 6, in the matching system described in Item 5, the computing device inputs attribute information and action history information into the trained prediction model to establish a correspondence between one or more of the multiple advertising information and the user belonging to the first group, the action history information includes information related to the user's action on the advertising information, and the prediction model is trained by machine learning based on the attribute information and the action history information.

[0548] (Item 7) The matching system described in Item 7 is the matching system described in any one of Items 1 to 6, wherein the first user device has a display that displays the advertisement information.

[0549] (Item 8) The matching system described in Item 8 is a matching system described in any one of Items 1 to 7, and has a function of matching a recruiter of a recruiting order-taker with an applicant, wherein the plurality of user devices include a recruiter device operated by the recruiter and a first applicant device operated by the first applicant, the recruiter device sends business information of the recruiting order-taker and public information indicating the scope of disclosure of the business information to a computing device, the computing device registers the business information together with the public information in a database, the computing device determines, based on the public information, the business information registered in the database that is permitted to be disclosed to the first applicant, and provides the business information permitted to be disclosed to the first applicant to the first applicant device.

[0550] (Item 9) The computing device described in Item 9 is included in a matching system for providing advertisements matched with each of a plurality of groups including an enterprise, the computing device comprising: a communication interface for communicating with a plurality of user devices including a first user device operated by a user belonging to a first group; and a processor for accessing a database, wherein group information capable of identifying each of the plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information in the plurality of advertisement information that is prohibited from being associated with the user belonging to the first group are registered in the database, the processor associates one or more of the plurality of advertisement information with the user belonging to the first group, publishes one or more of the advertisement information to the first user device, and the processor associates the advertisement information with the user belonging to the first group after excluding the advertisement information identified by the prohibition information.

[0551] (Item 10) The method described in Item 10 is a method for providing advertisements that match each of a plurality of groups including an enterprise, the method comprising the following steps: communicating with a plurality of user devices including a first user device operated by a user belonging to a first group; accessing a database that registers group information capable of identifying each of a plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information in a plurality of advertisement information that is prohibited from being associated with the user belonging to the first group; establishing a correspondence between one or more advertisement information in the plurality of advertisement information and the user belonging to the first group, and publishing one or more advertisement information to the first user device; and establishing a correspondence between the advertisement information and the user belonging to the first group after excluding the advertisement information identified by the prohibition information.

[0552] The embodiments disclosed herein are to be considered in all respects as illustrative and non-restrictive. The scope of the present invention is indicated not by the above description of the embodiments but by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims.

[0553] Description of Reference Numerals

[0554] 1: Matching system; 50: Internet; 100: Shared server; 101: Processor; 102: Memory; 103: Storage device; 104: Communication interface; 120: Database (DB); 121: Enterprise database (Enterprise DB); 122, 122A: Member database (Member DB); 123: Community database (Community DB); 124, 124A: Recruitment case database (Recruitment case DB); 125: Sideline database (Sideline DB); 126: Evaluation input database (Evaluation input DB); 126A: Recruiter evaluation Department; 126B: Applicant Evaluation Department; 127: Evaluation Summary Database (Evaluation Summary DB); 127A: Recruiter Evaluation Summary Department; 127B: Applicant Evaluation Summary Department; 128: Member Group Database (Member Group DB); 129: Profile Database (Profile DB); 131: Action History Database (Action History DB); 132: Advertisement Database (Advertisement DB); 133: Priority Database (Priority DB); 1271, 1272: Data Group; 140: Community Registration Department; 141: Enterprise Registration Department; 142: Member Registration Unit; 143: Member Search Unit; 144: Case Registration Unit; 145: Case Extraction Unit; 146: Application Unit; 147: Approval Unit; 148: Notification Unit; 149: Performance Acceptance Unit; 150: Performance Output Unit; 151: Evaluation Acceptance Unit; 152: Evaluation Output Unit; 161: Reverse Invitation Entrustment Unit; 162: Reverse Invitation Approval Entrustment Unit; 163: Reverse Invitation Entrustment Acceptance Notification Unit; 200, 200A, 200B, 200C: Recruiter Device; 201: Processor; 202: Memory; 203: Communication Interface; 20 4: Input / output interface; 205: Display; 206: Operation unit; 206A: Keyboard; 206B: Mouse; 207, 250, 350: Screen; 300, 300A, 300B, 300C: Applicant device; 301: Processor; 302: Memory; 303: Communication interface; 304: Input / output interface; 305: Display; 306: Operation unit; 306A: Keyboard; 306B: Mouse; 307A~307C: Labels; 401, 402: Table; 500: User device; 1291: Non-public list of advertisements.

Claims

1. A matching system for providing an advertisement matched to each of a plurality of groups including an enterprise, the matching system comprising: a plurality of user devices; and a computing device in communication with each of the plurality of user devices and capable of accessing a database, in, The plurality of user devices include a first user device operated by a user belonging to a first group, Registered in the database are group information capable of identifying each of the plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information, among the plurality of advertisement information, that is prohibited from being associated with users belonging to the first group. The computing device associates one or more pieces of advertising information with users belonging to the first group, and publishes the one or more pieces of advertising information to the first user device. The computing device associates the advertising information with users belonging to the first group after excluding the advertising information identified by the prohibition information.

2. The matching system according to claim 1, wherein: the plurality of user devices including a second user device operated by an advertiser belonging to a group different from the first group, The second user device sends the advertisement information of the advertiser to the computing device, The computing device registers the advertisement information received from the second user device in the database.

3. The matching system according to claim 1 or 2, wherein: The group information includes information for specifying any one of an enterprise and a department within the enterprise.

4. The matching system according to any one of claims 1 to 3, wherein: The prohibition information includes information indicating a competitive relationship between the plurality of groups.

5. The matching system according to any one of claims 1 to 4, wherein: The database contains the user's attribute information and the user's action history information, The computing device uses the attribute information and the action history information to associate one or more of the plurality of advertisement information with the user belonging to the first group.

6. The matching system according to claim 5, wherein: The computing device inputs the attribute information and the action history information into the trained prediction model to establish a correspondence between one or more of the plurality of advertisements and the users belonging to the first group. The action history information includes information related to the user's action with respect to the advertisement information. The prediction model is trained by machine learning based on the attribute information and the action history record information.

7. The matching system according to any one of claims 1 to 6, wherein: The first user device has a display that displays the advertisement information.

8. The matching system according to any one of claims 1 to 7, wherein: The matching system has the function of matching the recruiter of the recruitment business with the applicant. The plurality of user devices include a recruiter device operated by the recruiter and a first applicant device operated by a first applicant, The recruiter device sends the business information of recruiting order takers and the public information indicating the disclosure range of the business information to the computing device. The computing device registers the business information together with the public information in the database, The calculation device determines, based on the disclosure information, business information permitted to be disclosed to the first applicant among the business information registered in the database, and provides the business information permitted to be disclosed to the first applicant to the first applicant device.

9. A computing device included in a matching system for providing an advertisement matched with each of a plurality of groups including businesses, the computing device comprising: a communication interface that communicates with a plurality of user devices including a first user device operated by a user belonging to the first group; and A processor, which accesses a database, in, Registered in the database are group information capable of identifying each of the plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information, among the plurality of advertisement information, that is prohibited from being associated with users belonging to the first group. The processor associates one or more of the plurality of advertisement information with users belonging to the first group, and publishes the one or more of the advertisement information to the first user device. The processor associates the advertisement information with users belonging to the first group after excluding the advertisement information identified by the prohibition information.

10. A method for providing an advertisement matched to each of a plurality of groups comprising businesses, the method comprising the steps of: communicating with a plurality of user devices including a first user device operated by a user belonging to a first group; accessing a database in which group information capable of identifying each of the plurality of groups, a plurality of advertisement information, and prohibition information capable of identifying advertisement information, among the plurality of advertisement information, that is prohibited from being associated with users belonging to the first group are registered; Associating one or more pieces of advertising information among the plurality of pieces of advertising information with users belonging to the first group, and publishing the one or more pieces of advertising information to the first user device; as well as After excluding the advertisement information identified by the prohibition information, the advertisement information is associated with the users belonging to the first group.

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