Information processing method, program, and information processor

Abstract

To provide an information processing method, a program, and an information processor for providing more appropriate job information to a user.SOLUTION: On the basis of receiving registration of job information to job service, acquiring use history information of a user who uses the service other than the job service, identifying first job-related information related to work on the basis of the use history information, and identifying second job-related information related to the first job-related information and a job included in the job information, an information processor identifies job information to be recommended to the user, and outputs the identified job information to a processing device used by the user, the outputting being performed such that the fact that the job information is recommended is displayed in an identifiable manner.SELECTED DRAWING: Figure 10

Description

[Technical Field]

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

[0002] Systems that provide job information over a network have been put to practical use in the past. For example, a business support system has been disclosed that selects a means of notifying job seekers of job information by using job offer information, job seeker information, and reaction information regarding reactions to job information previously presented (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2023-133096 Summary of the Invention [Problem to be solved by the invention]

[0004] Although the above-mentioned business support system can present job offer information to users (job seekers), it has been difficult to select and present suitable job information to users.

[0005] An object of the present disclosure is to provide an information processing method, a program, and an information processing device that enable more appropriate job information to be provided to users. [Means for solving the problem]

[0006] An information processing method according to an embodiment of the present disclosure includes an information processing device receiving registration of job information to a job service, acquiring usage history information of users who use services other than the job service, identifying first job-related information related to work based on the usage history information, and identifying job information to be recommended to the user based on the first job-related information and second job-related information related to work included in the job information; The specified job information is output to a processing device used by the user, and the outputting is performed so that the job information is identifiably displayed as being recommended. [Effects of the Invention]

[0007] The disclosed technology makes it possible to provide more appropriate job information to users. [Brief explanation of the drawings]

[0008] [Figure 1] 1A and 1B are diagrams illustrating exemplary configurations of an information processing system according to an embodiment. [Figure 2] FIG. 1 is a block diagram illustrating an example of an information processing apparatus according to an embodiment. [Figure 3] FIG. 2 is a block diagram illustrating an example of a server according to an embodiment. [Figure 4] FIG. 2 is a block diagram illustrating an example of a server according to an embodiment. [Figure 5] FIG. 2 is a block diagram illustrating an example of a server according to an embodiment. [Figure 6] FIG. 4 is a diagram showing an example of first user information according to the embodiment. [Figure 7] FIG. 2 is a diagram illustrating an example of job information according to the embodiment. [Figure 8] FIG. 10 is a diagram showing an example of second user information according to the embodiment. [Figure 9] FIG. 10 is a diagram showing an example of third user information according to the embodiment. [Figure 10] 10 is a flowchart illustrating an example of a process for outputting job information recommended to a user. [Figure 11] FIG. 10 is a diagram illustrating an example of a screen that displays job information recommended to a user. [Figure 12] FIG. 10 is a diagram illustrating an example of a screen that displays job information recommended to a user. [Figure 13] 10 is a flowchart illustrating an example of a processing procedure for identifying job information to be recommended to a user based on a job category. [Figure 14] 10 is a flowchart illustrating an example of a process for identifying job listings to recommend to a user based on the brand offering the job. [Figure 15] 10 is a flowchart illustrating an example of a process for identifying job information to recommend to a user based on the work location where the job is offered. [Figure 16] 10 is a flowchart illustrating an example of a process for identifying job information to be recommended to a user based on job-related skills. [Figure 17] 10 is a flowchart illustrating an example of a process for identifying job information to be recommended to a user based on working hours. [Figure 18] 10 is a flowchart illustrating an example of a process for controlling the timing of outputting job information recommended to a user. [Figure 19] 10 is a flowchart illustrating an example of a process for controlling the timing of outputting job information recommended to a user. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the same elements are denoted by the same reference numerals, and redundant description will be omitted.

[0010] [Embodiment] In this embodiment, for users (hereinafter also referred to as "workers") who use a platform (hereinafter also referred to as a "job information providing platform") used for a service that provides job information (hereinafter also referred to as a "job service"), job information recommended to the user is identified based on information (hereinafter also referred to as "usage history information") that records the history of use of services other than the job service (hereinafter also referred to as "other services"), and the identified job information is provided to the user. This makes it possible to provide job information to the user based on information that cannot be obtained solely from the information registered in the job service, making it possible to provide more appropriate job information to the user.

[0011] <System configuration example> FIG. 1 is a diagram showing an example of each configuration of an information processing system 1 according to an embodiment. In the example shown in FIG. 1, information processing devices 10A and 10B used by each user, an information processing device 20A that manages a job information providing platform, information processing devices 20B and 20C that manage other services, and databases 30A, 30B, and 30C are connected via a network N. Note that when any number of the information processing devices 10A and 10B are connected to the network N and they are not distinguished from one another, they are also referred to as information processing devices 10. Furthermore, when the information processing devices 20A, 20B, and 20C are not distinguished from one another, they are also referred to as information processing devices 20. Furthermore, when the databases 30A, 30B, and 30C are not distinguished from one another, they are also referred to as databases 30.

[0012] The information processing device 10 is, for example, a smartphone, a computer, or a tablet terminal. By installing an application (hereinafter also referred to as a "recruitment app") that executes the recruitment service disclosed in the embodiment, the information processing device 10 can provide the recruitment service to users. Furthermore, if the recruitment service is implemented on a web page, the information processing device 10 can also use the recruitment service using a web browser.

[0013] Furthermore, the information processing device 10 can provide other services to the user by installing an application that executes the other services disclosed in the embodiments (hereinafter also referred to as "other service app") on the information processing device 10. Furthermore, if the other services are implemented on a web page, the information processing device 10 can also use the other services using a web browser.

[0014] The other service may be any service other than a recruitment service. For example, it may be a flea market service (hereinafter also referred to as a "flea market service") that enables users to buy and sell items online. An application that runs a flea market service is also referred to as a "flea market service app." The other service may also be an auction service that trades items or a payment service that purchases items or makes payments for services. In this embodiment, since the other service is assumed to be linked to the recruitment service, it may be any service from which useful information for the recruitment service can be obtained. For example, a service from which information about commercial transactions such as the items or services traded by users, the time of use, the amount of payment, the payment timing, the location of use, and the frequency of use can be obtained is suitable as the other service. The operator of the other service may be different from the operator of the recruitment service. In this case, the recruitment service system can obtain information / data from the system of the other service by linking with the recruitment service via an API (Application Programming Interface), for example.

[0015] The information processing device 20 is, for example, a server, and may be configured with one or more devices. The information processing device 20A manages a job information providing platform and performs the following: providing job information, user registration, job browsing, and job application processing. The information processing device 20B manages a platform that provides a flea market service (hereinafter also referred to as a "flea market service platform"), providing the flea market service, and registering users who use the flea market service. The information processing device 20C manages a platform that provides a payment service (hereinafter also referred to as a "payment platform"), providing the payment service, and registering users who use the payment service. In this embodiment, all or any two of the information processing devices 20A, 20B, and 20C may be implemented as the same device, or all may be different devices. Hereinafter, the information processing device 20 will also be referred to as a server 20.

[0016] Database 30A has a storage unit that stores or manages data related to a job recruitment service. Database 30B has a storage unit that stores or manages data related to a flea market service. Database 30C has a storage unit that stores or manages data related to a payment service. Databases 30A, 30B, and 30C may all be implemented as the same device, or any two of them may be implemented as different devices.

[0017] <Example of the configuration of each device> 2 is a block diagram showing an example of an information processing device 10 according to an embodiment. The information processing device 10 includes one or more processing units (CPUs) 110, one or more network or other communication interfaces 120, a memory 130, a user interface 150, and one or more communication buses 170 for interconnecting these components.

[0018] The user interface 150 is, for example, a user interface including a display device 151 and an input device (such as a keyboard and / or a mouse or any other pointing device) 152. The user interface 150 may also be a touch panel.

[0019] Memory 130 may be, for example, a high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state memory, or may be a non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. Memory 130 may also be a non-transitory computer-readable recording medium.

[0020] Another example of memory 130 may be one or more storage devices installed remotely from CPU 110. In one embodiment, memory 130 stores the following programs, modules, and data structures related to the recruitment application, or a subset thereof.

[0021] Operating system 131, for example, handles various basic system services and includes procedures for performing tasks with the hardware.

[0022] The network communication module 132 is used, for example, to connect the information processing device 10 to other computers via one or more network communication interfaces 120 and one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, etc.

[0023] The application data 133 includes data that is processed when a user uses a job recruitment service, a flea market service, and / or a payment service. For example, the application data 133 includes user information and information acquired from the server 20. Specifically, the application data 133 includes job recruitment information, information about the flea market service, information about the payment service, and the like.

[0024] The processing module 134 executes various processes related to the job information providing platform provided by the server 20A, various processes related to the flea market service platform provided by the server 20B, and / or various processes related to the payment platform provided by the server 20C. For example, the processing module 134 includes an acquisition module 135, an output module 136, and a reading module 137, which will be described later.

[0025] The acquisition module 135B acquires user operations on each button in the display screen displayed on the display 151B. For example, the acquisition module 135B acquires various information input by user operations on various screens of the job information providing platform, various screens of the flea market service platform, and various screens of the payment platform.

[0026] For example, when registration information for a new user is input by a user operation, the output module 136B transmits the registration information and a new registration request to the server 20. The registration information may include, for example, the user's name, address, telephone number, etc. input by the user. Upon receiving the new registration request, the server 20 performs registration processing for the new user based on the registration information.

[0027] Furthermore, when a user performs an operation to view job information, output module 136B outputs a view request to server 20A. Furthermore, when a user performs an operation to apply for a job from the job information viewing screen, output module 136B outputs an application request to server 20A. Furthermore, when a user performs an operation to view an item in a flea market service, output module 136B outputs a view request to server 20B. Furthermore, when a user performs an operation to purchase an item from the item viewing screen, output module 136B outputs a purchase request to server 20B. Furthermore, when a user performs an operation to pay for an item using a payment service, output module 136B outputs a payment request to server 20C.

[0028] The reading module 137B has a function of reading an information code (e.g., a barcode, a two-dimensional code, a three-dimensional code, etc.) including invitation information. For example, the reading module 137B may read the information code to access a web page for user registration for a job recruitment service and other services (e.g., a flea market service and a payment service), or to download a job recruitment app and other service apps.

[0029] Display control module 138B controls the display of one screen of the web page of the job application and other services. For example, display control module 138B controls the display of a user registration screen for the job service, a job information viewing screen, a job application screen, a user registration screen for the flea market service, a product viewing screen, a product transaction screen, a user registration screen for the payment service, and a payment screen, etc., on display 151B.

[0030] Note that one or more processing units (CPUs) 110 read and execute each module from memory 130 as necessary. For example, one or more processing units (CPUs) 110 may configure a communication unit by executing network communication module 132 stored in memory 130. Also, one or more processing units (CPUs) 110 may configure a processing unit, an acquisition unit, an output unit, a reading unit, and a display control unit by respectively executing processing module 134, acquisition module 135, output module 136, reading module 137, and display control module 138 stored in memory 130. Also, the respective processes of processing module 134, acquisition module 135, output module 136, reading module 137, and display control module 138 may be executed by one or more processing units (CPUs) 110.

[0031] In other embodiments, the processing module 134, the acquisition module 135, the output module 136, the reading module 137, and the display control module 138 may be standalone applications stored in the memory 130 of the information processing device 10. Standalone applications include, but are not limited to, a processing application, an acquisition application, an output application, a reading application, and a display control application. In yet other embodiments, the processing module 134, the acquisition module 135, the output module 136, the reading module 137, and the display control module 138 may be add-ons or plug-ins to another application.

[0032] Each of the above-identified elements may be stored in one or more of the aforementioned storage devices. Each of the above-identified modules corresponds to a set of instructions for performing a function described above. The above-identified modules or programs (i.e., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or reconfigured in various embodiments. In some embodiments, memory 130 may store a subset of the modules and data structures described above. Additionally, memory 130 may store additional modules and data structures not described above.

[0033] 3 is a block diagram illustrating an example of a server 20A according to an embodiment. The server 20A includes one or more processing units (CPUs) 210, one or more network or other communication interfaces 220, a memory 230, and one or more communication buses 270 for interconnecting these components.

[0034] Server 20A may optionally include a user interface 250, which may include a display device (not shown) and a keyboard and / or mouse (or some other input device, such as a pointing device, not shown).

[0035] Memory 230 may be, for example, a high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state memory, or may be a non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. Memory 230 may also be a non-transitory computer-readable recording medium.

[0036] Additionally, another example of memory 230 may include one or more storage devices located remotely from CPU 210. In one embodiment, memory 230 stores the following programs, modules, and data structures, or a subset thereof:

[0037] Operating system 231 includes, for example, procedures for handling various basic system services and for performing tasks with the hardware.

[0038] The network communications module 232 is used, for example, to connect the server 20 to other computers via one or more communications interfaces 220 and one or more communications networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, etc.

[0039] The first user information 233 includes information about users who use the job information providing platform. For example, the first user information 233 includes the user's name, address, telephone number, etc., associated with each user ID (user ID: Identifier). The first user information 233 will be described later with reference to FIG. 6.

[0040] The job information 234 includes one or more job information items registered in a job information providing platform or a job service. For example, the job information 234 includes information such as the job offer date, working hours, work location, job category, and skills required of users. The job information 234 will be described later with reference to FIG. 7.

[0041] The control module 240 manages processes related to job offers in the job information providing platform. For example, the control module 240 includes a reception module 241, an acquisition module 242, a first identification module 243, a second identification module 244, an output module 245, and a detection module 246 as processes related to job offers.

[0042] The reception module 241 accepts the registration of job information to the job service from the information processing device 10 used by a business providing the job service. For example, the reception module 241 acquires information entered on a screen for accepting the registration of job information and registers it in the job information 234. The reception module 241 also accepts registration to use the job service from the information processing device 10 used by the user. For example, the reception module 241 registers information such as name, address, and telephone number entered on a screen for accepting registration to use the job service in the first user information 233.

[0043] The acquisition module 242 acquires usage history information of users who use services other than the job recruitment service. For example, the acquisition module 242 accesses the server 20B and the server 20C to acquire usage history information of users who use the flea market service and usage history information of users who use the payment service. As a specific example, the acquisition module 242 may acquire usage history information of the other services via the APIs of the other services.

[0044] The first identification module 243 identifies information about jobs recommended to the user (hereinafter also referred to as "first job-related information") based on the usage history information acquired by the acquisition module 242. The first job-related information may be, for example, a job category, a brand that offers the job, a work time, a work location, and job skills. The first identification module 243 may, for example, extract, from the usage history information of other services, the presence or absence of preset information (keywords, etc.) or information that appears more frequently than a predetermined value, and identify the job-related information from the extracted information. The identification method may, for example, use a learning model that outputs information that associates information in the usage history information with the first job-related information, or an association between information in the usage history information and the first job-related information.

[0045] The second identification module 244 identifies job information to recommend to the user based on the first job-related information identified by the first identification module 243 and information about the job included in the job information (hereinafter also referred to as "second job-related information"). The second job-related information may be, for example, a job category, a brand offering the job, work hours, work location, and job skills. The second identification module 244 may identify job information to recommend to the user using, for example, information associating the first job-related information with the second job-related information, or a learning model that outputs the association between the first job-related information and the second job-related information.

[0046] The output module 245 outputs the job information identified by the second identification module 244 to the information processing device 10 used by the user. For example, the output module 245 may output the job information to the information processing device 10 so that the identified job information is displayed on the screen of the information processing device 10 in a manner that makes it identifiable that the job information is recommended to the user. As a specific example, the output module 245 makes it possible to identify the recommended job information by preferentially displaying the identified job information at the top of the job information list screen, by providing a recommended job column and displaying the identified job information in the recommended job column, or by highlighting the identified job information.

[0047] Through the above process, it becomes possible to provide suitable job information to a user by identifying job information recommended to the user using usage history information of other services used by the user. Furthermore, by making the recommended job information identifiable, the user can easily understand the job information recommended to them.

[0048] The first identification module 243 may identify a category of work to be recommended to the user (hereinafter also referred to as a "first job category") based on a category related to a store used or a purchased item included in the usage history information. For example, the first identification module 243 may identify the first job category by searching whether or not a keyword indicating a category related to a store used or a purchased item is present in the usage history information. The first identification module 243 may identify the first job category as "sports" if a keyword indicating a sports store is present in the usage history information. Furthermore, the first identification module 243 may identify the first category as "fashion" if a keyword indicating clothing is present in the usage history information.

[0049] The second identification module 244 may identify job information to recommend to the user based on the first job category identified by the first identification module 243 and the job category included in the second job-related information (hereinafter also referred to as the "second job category"). The job category of the job information may be set in advance by the business operator that registers the job information.

[0050] For example, assume that the second categories of jobs included in the second job-related information include "fashion" and "sports." If the first category of jobs identified by the first identification module 243 is "sports," the second identification module 244 may identify job information whose second category is "sports" as job information to recommend to the user.

[0051] Through the above processing, it becomes possible to identify job categories recommended to the user that can be identified from the usage history information of other services used by the user, and to output job information corresponding to the identified job categories to the user's information processing device 10.

[0052] The first identification module 243 may identify a brand that provides work recommended to the user (hereinafter also referred to as a "first brand that provides work") based on a brand related to a used store or a purchased product included in the usage history information. For example, the first identification module 243 may identify a first brand that provides work by searching whether or not a keyword representing a brand related to a used store or a purchased product exists in the usage history information.

[0053] The second identification module 244 may identify job information to recommend to the user based on the first brand that provides work identified by the first identification module 243 and the brand that provides work included in the second job-related information (hereinafter also referred to as the "second brand that provides work").

[0054] For example, assume that the second job-related information includes brands that offer jobs, such as "Convenience Store A" and "Restaurant B." If the brand that offers jobs recommended to the user, identified by the first identification module 243, is "Convenience Store A," the second identification module 244 may identify, as job information recommended to the user, job information in which the brand that offers jobs is "Convenience Store A."

[0055] Through the above process, it becomes possible to output to the user's information processing device 10 job information corresponding to the brand used by the user, which can be identified from the usage history information of other services used by the user.

[0056] The first identification module 243 may identify the location where the user uses other services based on the usage history information, and may identify the work location of the work recommended to the user (hereinafter also referred to as the "first work location").

[0057] The second identification module 244 may identify job information to recommend to the user based on the first work location of the job identified by the first identification module 243 and the work location included in the second job-related information (hereinafter also referred to as the "second work location").

[0058] For example, if the user's payment service usage history information records that the user purchased a product at the store of convenience store A in front of Station B, the first identification module 243 may identify the work location of the job recommended to the user (first work location) as the store of convenience store A in front of Station B. Also, if the job information includes the store of convenience store A in front of Station B and the store of convenience store A in front of Station C as work locations (second work locations), the second identification module 244 may identify the job information of the store of convenience store A in front of Station B as the job information recommended to the user.

[0059] Through the above process, it becomes possible to output to the information processing device 10 of the user job information corresponding to the user's location of use, which can be identified from the usage history information of other services used by the user.

[0060] The first identification module 243 may identify the user's work-related skills (hereinafter also referred to as "first skills") from the usage history information. For example, a user who frequently purchases sporting goods is expected to have a wealth of product knowledge about sporting goods. Therefore, the first identification module 243 can identify that the user has knowledge about sporting goods as a skill of the user.

[0061] The second identification module 244 may identify job information to recommend to the user based on the first skill identified by the first identification module 243 and the skills required of applicants included in the second job-related information (hereinafter also referred to as "second skills"). For example, if there is job information among the job information that seeks someone with extensive product knowledge about sporting goods, the second identification module 244 may identify that job information as the job information to recommend to the user.

[0062] Through the above process, it becomes possible to recommend to the user job information that matches the user's skills, which can be identified from the usage history information of other services used by the user.

[0063] The first identification module 243 may identify a time period during which the user uses other services based on the usage history information, and may identify work hours recommended to the user (hereinafter also referred to as "first work work time period") based on the identified time period. For example, if the user often uses payment services at convenience stores at night, the first identification module 243 may identify that the work time period during which the user is available to work is night. Also, if the user often uses flea market services in the morning, the first identification module 243 may identify that the time period during which the user is available to work is morning.

[0064] The second identification module 244 may identify job information to recommend to the user based on the first working time slot identified by the first identification module 243 and the working time slot of the job included in the second work-related information (hereinafter also referred to as "second working time slot of the job"). For example, if there is job information with working hours in the morning among the job information, the second identification module 244 may identify the job information as the job information to recommend to the user.

[0065] Through the above process, it becomes possible to recommend to the user job information that corresponds to the user's available working hours, which can be identified from the usage history information of other services used by the user.

[0066] The detection module 246 may detect a specific event related to a payment based on the usage history information. The specific event related to a payment may be, for example, a user purchasing a product worth more than a predetermined amount, or a scheduled payment amount for a credit card or the like used in a payment service exceeding a predetermined amount.

[0067] When the detection module 246 detects a specific event, the output module 245 may output job information recommended to the user in the manner described above.

[0068] Through the above process, when a specific payment-related event that can be identified from the usage history information of other services used by the user is detected, it becomes possible to recommend job information to the user.

[0069] The first identification module 247 may identify the payment deadline based on the usage history information. The payment deadline may be, for example, the deadline for debiting a credit card used in a payment service.

[0070] The output module 245 may output job information recommended to the user a predetermined period before the payment deadline identified by the first identification module 247.

[0071] By the above process, it becomes possible to recommend job information to the user so that payment deadlines can be met.

[0072] Fig. 4 is a block diagram showing an example of a server 20B according to the embodiment. In Fig. 4, components with the same reference numerals as those in Fig. 3 are the same as those in Fig. 3, and therefore description thereof will be omitted.

[0073] The second user information (user information of the flea market service) 235 includes information on users who use the flea market service platform. For example, the second user information 235 includes the user's name, address, telephone number, and auction and winning bid history, etc., associated with each user ID. The second user information 235 will be described later with reference to FIG. 8.

[0074] Fig. 5 is a block diagram showing an example of a server 20C according to the embodiment. In Fig. 5, components with the same reference numerals as those in Fig. 3 are the same as those in Fig. 3, and therefore description thereof will be omitted.

[0075] The third user information 236 includes information about users who use the payment service platform. For example, the third user information 236 includes the user's name, address, phone number, payment history, etc., associated with each user ID. The third user information 236 will be described later with reference to FIG. 9.

[0076] Each of the elements illustrated in Figures 2-5 above may be stored in one or more of the storage devices described above. Each of the modules illustrated above corresponds to a set of instructions for performing a function described above. The modules or programs (i.e., sets of instructions) illustrated above need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or reconfigured in various embodiments. In some embodiments, memory 230 may store a subset of the modules and data structures illustrated above. Additionally, memory 230 may store additional modules and data structures not described above.

[0077] Note that one or more processing units (CPUs) 210 read and execute each module from memory 230 as necessary. For example, one or more processing units (CPUs) 210 may configure a communication unit by executing network communication module 232 stored in memory 230. Also, one or more processing units (CPUs) 210 may configure a reception unit, an acquisition unit, a first identification unit, a second identification unit, an output unit, a detection unit, and a third identification unit by respectively executing reception module 241, acquisition module 242, first identification module 243, second identification module 244, output module 245, and detection module 246 stored in memory 230. Also, the processing of each of reception module 241, acquisition module 242, first identification module 243, second identification module 244, output module 245, and detection module 246 may be executed by one or more processing units (CPUs) 210.

[0078] While Figures 3-5 depict "servers," they are intended as an illustration of various features that may be present in a set of servers, rather than as a structural overview of the embodiments described herein. In practice, as will be recognized by those skilled in the art, items shown separately could be combined and certain items could be separated. For example, items shown separately in Figures 3-5 could be implemented on a single server, and a single item could be implemented by one or more servers.

[0079] The databases 30A, 30B, and 30C may have the same configurations as those shown in Figures 3, 4, and 5, respectively. At least one of the first user information 233 and the job information 234 shown in Figure 3 may be stored in the storage unit of the database 30A. The second user information 235 shown in Figure 4 may be stored in the storage unit of the database 30B. The third user information 236 shown in Figure 5 may be stored in the storage unit of the database 30C.

[0080] <Example of data structure> FIG. 6 is a diagram showing an example of first user information 233 according to the embodiment. The first user information 233 manages information about each member user created by a user who uses the job recruitment service. The "user ID" includes user identification information that allows the server 20 to uniquely identify the user. The user ID is associated with "first user information."

[0081] The "first user information" includes the user's personal information such as "name," "address," and "telephone number." The user ID may be included as part of the user information. The user information may also include an email address, a password, and the like.

[0082] FIG. 7 is a diagram showing an example of job information 234 according to the embodiment. Job information 234 registers job information received from companies and the like that are recruiting. "Job ID" includes identification information for the job information. The job information includes information such as "working hours," "work location," "brand / company name," "job category," and "desired skills" associated with the job ID.

[0083] The "job posting date and time" includes the date and working hours of the job posting. The "work location" includes the location (address) where the user will work. The "brand / company name" includes the brand name or company name of the company where the user will work. Note that for brands or companies with multiple stores, the "brand / company name" may also include the store name (e.g., XX Station Front Store). The "job category" includes a category that categorizes the work performed by the user. The job categories may be arbitrarily defined or may be defined according to job classifications such as those provided by government job information websites. Examples of job categories include convenience store clerk, customer service at a sports store, customer service at a clothing store, cooking, packing, cashier, security, cleaning, delivery work, and farm work. The "desired skills" indicate the skills desired by the user when registering the job information. For example, a company may desire someone with previous experience working for the same brand or company. For example, a chef may desire someone with cooking experience, or a customer service position at a sporting goods store may desire someone with product knowledge about sporting goods.

[0084] FIG. 8 is a diagram showing an example of second user information 235 according to the embodiment. The second user information 235 manages information about each member user created by a user who uses the flea market service. The "user ID" includes user identification information that allows the server 20 to uniquely identify the user. The user ID is associated with "second user information."

[0085] "Second user information" includes personal information about the user, such as "name," "address," and "telephone number." A user ID may be included as part of the user information. User information may also include an email address, password, and so on. "Listing / purchase history" includes historical information when a user uses a flea market service to list an item and when a user purchases an item listed by another user. The historical information includes the date and time of listing or purchase, the name of the item listed or purchased, and so on.

[0086] FIG. 9 is a diagram showing an example of third user information 236 according to the embodiment. The third user information 236 manages information about each member user created by a user who uses the payment service. The "user ID" includes user identification information that allows the server 20 to uniquely identify the user. The user ID is associated with "third user information."

[0087] "Third user information" includes personal information about the user, such as "name," "address," and "telephone number." A user ID may be included as part of the user information. User information may also include an email address and password. "Payment history" records the date and time when a user made a payment using the payment service, the brand name or company name that made the payment, the store name, and the amount paid.

[0088] <Operation description> Next, a description will be given of the operation of the information processing system 1 according to the embodiment. Fig. 10 is a flowchart showing an example of a process for outputting job information recommended to a user.

[0089] (Step S101) The first identification module 243 of information processing device 20A accesses the first user information, the second user information of information processing device 20B, and the third user information of information processing device 20C, and extracts, from among the users registered with the job service, users who are also registered with other services (flea market services and / or payment services) other than the job service. For example, the first identification module 243 may extract the same user using at least one of unique information, such as a user ID, name, address, or telephone number, from the user information registered with the job service and the user information registered with the other services.

[0090] (Step S102) The first identification module 243 of the information processing device 20A accesses the second user information of the information processing device 20B and acquires usage history information (listing / purchase history and / or payment history) of other services (flea market service and / or payment service) of the extracted user. For example, the information processing device 20A may acquire usage history information of other services provided by the information processing device 20B through a business partnership, use of an API, or the like.

[0091] (Step S103) The first identification module 243 of the information processing device 20A identifies information related to work (first work-related information) from the acquired usage history information (listing / purchase history and / or payment history) of other services (flea market services and / or payment services). The information related to work (first work-related information) may be, for example, at least one of the work category, the brand providing the work, the work hours, the work location, and the work skills.

[0092] (Step S104) The second identification module 244 of the information processing device 20A identifies job information to recommend to the user based on the job-related information (first job-related information) identified in the processing procedure of step S103 and the job-related information (second job-related information) included in the job information 234. Here, the job-related information (second job-related information) included in the job information 234 may be, for example, at least one of the job category, the brand providing the job, the work hours, the work location, and the job skills. The job category can be acquired from the "job category" in the job information 234. The brand providing the job can be acquired from the "brand / company name" in the job information 234. The work hours can be acquired from the "job recruitment date and time" in the job information 234. The work location can be acquired from the "work location" in the job information 234. The job skills can be acquired from the "desired skills" in the job information 234.

[0093] The second identification module 244 identifies a job vacancy ID that includes second work-related information that corresponds to the first work-related information identified in the processing procedure of step S103. The second work-related information that corresponds to the first work-related information may be second work-related information that is identical to the first work-related information, or may be second work-related information that is similar to the first work-related information. In other words, the second identification module 244 may identify a job vacancy ID that includes second work-related information that is identical to the first work-related information, or may identify a job vacancy ID that includes second work-related information that is similar to the first work-related information.

[0094] When identifying a job vacancy ID that includes second work-related information similar to the first work-related information, the second identification module 244 may calculate the similarity between the first work-related information and the second work-related information, for example, by using a trained model (such as word2vec) that outputs the similarity between keywords. The similarity may be expressed between 0 and 1, and the closer to 1 the number is, the more similar the keywords are. Specifically, the second identification module 244 may identify a job vacancy ID that includes the second work-related information with the highest similarity between the keywords representing the first work-related information and the keywords representing the second work-related information, where the similarity between the keywords representing the first work-related information is equal to or greater than a predetermined threshold.

[0095] (Step S105) The output module 245 outputs the job information of the job ID identified by the second identification module 244 as job information recommended to the user. The job information output by the output module 245 is displayed on the screen of the user's information processing device 10. A display example of job information recommended to the user will be described using Figs. 11 and 12.

[0096] FIG. 11 is a diagram showing an example of a screen that displays job information recommended to the user. FIG. 11 is an example of a screen of a job application. In the example of FIG. 11, job information W1 to W4 are displayed, and job information W1 is marked with the word "Recommended!" to indicate that it is job information recommended to the user. As shown in FIG. 11, the output module 245 may display the job information recommended to the user in a prominent location (for example, the top row) on the screen that displays the job information. This allows the user to easily identify the recommended job information among multiple job information.

[0097] FIG. 12 is a diagram showing an example of a screen that displays job information recommended to a user. FIG. 11 is an example of a screen of a service app other than a job service (for example, a flea market service app). In the example of FIG. 12, notices M1 to M4 are displayed side by side on a notice list screen of other services. Notice M1 is job information recommended to the user, and notices M2 to M4 are notice information related to the other services. As shown in FIG. 12, the output module 245 may display the job information recommended to the user in a prominent location (for example, the top row) on the screen that displays the notices. This allows the user to easily identify the recommended job information among multiple job information.

[0098] 13 is a flowchart showing an example of a procedure for identifying job information to be recommended to a user based on a job category, which is an example of the procedure for step S104 in FIG.

[0099] (Step S201) The first identification module 243 identifies a job category (first job category) to be recommended to the user based on categories related to stores used or purchased products included in the usage history information of other services. For example, the first identification module 243 may identify the first job category by searching for keywords related to the job category in the usage history information of other services for each category. Keywords related to the job category may be stored in advance in the memory 230 as a list for each category. For example, keywords related to the "sports" category may include keywords such as "sports," "soccer," "baseball," "tennis," and "skiing." Furthermore, keywords related to the "fashion" category may include keywords such as "clothes," "skirt," "pants," and "socks."

[0100] For example, if the keyword "tennis racket" exists in the selling / purchase history of the second user information of the user extracted in step S101, the first identification module 243 may identify that the category of work to be recommended to the user is "sports." Also, if the keyword "sports shop E" exists in the payment history of the third user information (payment service) of the user extracted in step S101, the first identification module 243 may identify that the category of work to be recommended to the user is "sports."

[0101] Furthermore, the first identification module 243 may use a trained model (such as word2vec) that outputs similarities between words to obtain, for each work category, the similarity between a keyword representing the work category and a keyword included in the usage history information, and search for whether or not there is usage history information in which the similarity is equal to or greater than a predetermined value. For example, the first identification module 243 may input, into the trained model, the keyword for "sports," which is a work category, and keywords included in the user's usage history information for other services (such as the listing / purchase history in FIG. 8 and the payment history in FIG. 9), to obtain the similarity between the keyword for "sports" and the keyword included in the usage history information.

[0102] If usage history information is found whose similarity to the keyword "sports" is equal to or greater than a predetermined value, the first identification module 243 may identify the first category of work as "sports." On the other hand, if usage history information whose similarity to the keyword "sports" is equal to or greater than a predetermined value is not found, the first identification module 243 may acquire the similarity between the character string "fashion" and the keywords included in the usage history information by inputting the keyword "fashion" and keywords included in the user's usage history information of other services (such as the listing / purchase history in FIG. 8 and the payment history in FIG. 9) into the trained model. If usage history information whose similarity to the keyword "fashion" is equal to or greater than a predetermined value is found, the first identification module 243 may identify the first category of work as "fashion."

[0103] (Step S202) The second identification module 244 identifies job information to recommend to the user based on the job category (first job category) identified in step S201 to be recommended to the user and the "job category" (second job category) of the job information 234. For example, if there is a job ID in the job information 234 that has a "job category" that matches the first job category identified in step S201, the second identification module 244 may identify the job ID as job information to recommend to the user. For example, if "sports" is identified as the first job category, the second identification module 244 may identify a job ID (W03 in the example of FIG. 7) that includes the keyword "sports" in the "job category" as job information to recommend to the user.

[0104] 14 is a flowchart showing an example of a process for identifying job information to be recommended to a user based on a brand that provides jobs. The processing procedure in FIG. 12 is an example of the processing procedure in step S104 in FIG.

[0105] (Step S211) The first identification module 243 identifies a brand (first brand providing jobs) that provides jobs recommended to the user based on a brand related to a store used or a purchased product included in the usage history information of the other service. For example, the first identification module 243 may identify the first brand providing jobs by searching for whether a keyword representing a brand name of a company providing jobs exists in the usage history information of the other service. For example, if the keyword "Brand M" exists in the listing / purchase history of the second user information (flea market service) of the user extracted in step S101, the first identification module 243 may identify the brand providing jobs recommended to the user as "Brand M." Also, if the keyword for the brand "Convenience Store A" exists in the payment history of the third user information (payment service) of the user extracted in step S101, the first identification module 243 may identify the brand providing jobs recommended to the user as "Convenience Store A." Keywords representing brand names of companies or stores may be stored in advance as a list in the memory 230. The first identification module 243 may acquire keywords representing brand names from the list, and may repeatedly perform a process for each keyword to search for whether the acquired keywords exist in the usage history information of other services.

[0106] (Step S212) The second identification module 244 identifies job information to recommend to the user based on the brand that provides jobs recommended to the identified user (first brand that provides jobs) and the brand that provides jobs to the user that is indicated by the "brand / company name" in the job information 234 (second brand that provides jobs). For example, if there is a job ID in the job information 234 that has a "brand / company name" that matches the first brand of the job identified in step S201, the second identification module 244 may identify the job ID as job information to recommend to the user. For example, if "Convenience Store A" is identified as the first brand that provides jobs, the second identification module 244 may identify a job ID (W01 in the example of FIG. 7) that includes the keyword "Convenience Store A" in the "brand / company name" as job information to recommend to the user.

[0107] 15 is a flowchart showing an example of a process for identifying job information to be recommended to a user based on the work location. The process procedure in FIG. 15 is an example of the process procedure in step S104 in FIG.

[0108] (Step S221) The first identification module 243 identifies the location where the user uses the other service based on the user's usage history information of the other service. For example, the first identification module 243 may identify the location where the user uses the other service by searching whether or not a keyword indicating the location of use exists in the usage history information of the other service. Furthermore, the first identification module 243 may identify the work location of a job recommended to the user (first work location) based on the location where the user uses the other service.

[0109] For example, if the payment history of the user's third user information (payment service) extracted in step S101 contains a location keyword "X Station Store," the first identification module 243 may identify the location where the user uses the other service as "X Station." Furthermore, since the location where the user uses the other service is "X Station," the first identification module 243 may identify the work location of the job recommended to the user (first work location of the job) as X Station. Note that the location where the user uses the other service and the work location of the job recommended to the user may be the same, or may be within a predetermined range from the location where the user uses the other service.

[0110] (Step S222) The second identification module 244 identifies job information to recommend to the user based on the work location of the job recommended to the user (first work location of the job) identified in step S221 and the "work location" of the job information 234. For example, if there is a job ID in the job information 234 that matches the first work location of the job identified in step S201 or has a "work location" within a predetermined range from the first work location of the job, the second identification module 244 may identify the job ID as job information to recommend to the user. For example, if "in front of X Station" is identified as the first work location of the job, the second identification module 244 may identify a job ID (W01 in the example of FIG. 7) whose "work location" is in front of X Station or within a predetermined range from X Station as job information to recommend to the user.

[0111] 16 is a flowchart showing an example of a process for identifying job information to be recommended to a user based on job-related skills. The process procedure in FIG. 16 is an example of the process procedure in step S104 in FIG.

[0112] (Step S231) The first identification module 243 identifies a work-related skill (first skill) of the user based on usage history information of the user of other services. For example, the first identification module 243 may identify the user as having a specific skill if a specific history exists a predetermined number of times in the usage history information of other services. Information indicating the correspondence between the content of the specific history and the predetermined number of times and the content of the identified skill may be stored in advance in the memory 230 as skill definition information.

[0113] For example, if the listing / purchase history of the second user information (flea market service) of the user extracted in step S101 records that the number of listings is a predetermined number or more, the first identification module 243 may identify the user's work-related skill as "packaging." Also, if the listing / purchase history of the second user information (flea market service) of the user extracted in step S101 records that the number of listings or purchases of sporting goods is a predetermined number or more, the first identification module 243 may identify the user's work-related skill as "product knowledge about sporting goods."

[0114] (Step S232) The second identification module 244 identifies job information to recommend to the user based on the identified user's work-related skill (first skill) and the "desired skill" in the job information 234. For example, if there is a job ID in the job information 234 that has a "desired skill" that matches the first skill identified in step S201, the second identification module 244 may identify the job ID as job information to recommend to the user. For example, if "product knowledge about sporting goods" is identified as the first job skill, the second identification module 244 may identify a job ID (W03 in the example of FIG. 7) whose "desired skill" is product knowledge about sporting goods as job information to recommend to the user.

[0115] In this embodiment, when a user uses a recruitment service to work, information indicating that the user has experience in that work (for example, points, badges, etc.) may be assigned. Furthermore, the first identification module 243 may identify the user's work-related skills (first skills) based on the amount of information. For example, a user who frequently works in customer service jobs can be evaluated as having the skills to work in customer service. Therefore, the first identification module 243 may identify such a user as having customer service skills.

[0116] 17 is a flowchart showing an example of a process for identifying job information to be recommended to a user based on working hours of the job. The processing procedure in FIG. 17 is an example of the processing procedure in step S104 in FIG.

[0117] (Step S241) The first identification module 243 identifies a time period during which the user uses the other service based on the user's usage history information of the other service. For example, the first identification module 243 may identify a time period during which the user uses the other service by searching for usage times of the other service included in the usage history information of the other service. Furthermore, the first identification module 243 may identify a work working time period (first work working time period) recommended to the user based on the time period during which the user uses the other service.

[0118] For example, if the payment history of the second user information of the user extracted in step S101 includes a predetermined number of records of listing or purchasing products between 8 PM and midnight, the first identification module 243 may identify that the time period during which the user uses other services is "nighttime." Furthermore, since the time period during which the user uses other services is "nighttime," the first identification module 243 may identify that the work hours recommended to the user (first work work hours) are nighttime.

[0119] Furthermore, if the payment history of the user's third user information (payment service) extracted in step S101 includes a predetermined number of records of using the payment service at night, the first identification module 243 may be configured to identify the time period during which the user uses other services as "nighttime." Furthermore, since the time period during which the user uses other services is "nighttime," the first identification module 243 may be configured to identify the work hours (first work work hours) recommended to the user as nighttime.

[0120] (Step S242) The second identification module 244 identifies job information to recommend to the user based on the working hours of the job recommended to the identified user (first working time slot of the job) and the "job posting date and time" of the job information 234. For example, if there is a job ID in the job information 234 that has a "job posting date and time" that matches or partially overlaps with the first working time slot of the job identified in step S201, the second identification module 244 may identify the job ID as job information to recommend to the user. For example, if "nighttime" is identified as the first working time slot of the job, the second identification module 244 may identify a job ID whose "job posting date and time" is a night shift as job information to recommend to the user.

[0121] 13 to 17. For example, the first identification module 243 may identify two or more pieces of information from among a job category recommended to the user (first job category), a brand offering jobs recommended to the user (first job-offering brand), a work location of the job recommended to the user (first work location), the user's job-related skills (first skills), and work hours of the job recommended to the user (first work hours). The second identification module 244 may identify job information recommended to the user based on the two or more pieces of information identified by the first identification module 243 and the job information 234.

[0122] This makes it possible, for example, if a brand offering work operates multiple stores, to recommend job openings to a user at stores close to where the user frequently uses the brand's services, or to recommend job openings where the user's skills match the skills the company is looking for and the job opening dates and times are during the time the user uses the company's services.

[0123] 18 is a flowchart illustrating an example of a process for controlling the timing of outputting job information recommended to a user. The process procedure in FIG. 18 is an example of the process procedure in step S105 in FIG.

[0124] (Step S301) The detection module 246 detects a specific event related to payment based on the usage history information of other services. The specific event may be, for example, that the credit payment for the next month is equal to or exceeds a predetermined amount, that the user has made a payment equal to or exceeds a predetermined amount, or that the user has borrowed money from a business providing another service. For example, the detection module 246 may detect that the credit payment for the next month is equal to or exceeds a predetermined amount, or that a payment equal to or exceeds a predetermined amount, by referring to the usage history information of the third user information (payment service). If the detection module 246 detects a specific event, the process proceeds to step S302.

[0125] (Step S302) The output module 245 outputs the job information of the job ID identified by the second identification module 244 as job information recommended to the user.

[0126] 19 is a flowchart illustrating an example of a process for controlling the timing of outputting job information recommended to a user. The process procedure in FIG. 19 is an example of the process procedure in step S105 in FIG.

[0127] (Step S311) The first identification module 247 identifies the payment deadline based on the usage history information of the other service. The payment deadline may be, for example, the next credit card withdrawal date or the payment deadline for the price of an item purchased at a flea market service. If the first identification module 247 identifies the payment deadline, the process proceeds to step S312.

[0128] (Step S312) The output module 245 outputs the job information of the job ID identified by the second identification module 244 as job information to be recommended to the user a predetermined period before the payment deadline identified by the first identification module 247.

[0129] The disclosed technology is not limited to the above-described embodiment, and can be implemented in various other forms without departing from the spirit of the disclosed technology. Therefore, the above-described embodiment is merely an example in all respects and should not be interpreted as being limiting. For example, the order of the above-described processing steps can be arbitrarily changed or executed in parallel as long as no contradiction occurs in the processing content.

[0130] The program of the embodiment of the present disclosure may be provided in a state stored in a computer-readable storage medium. The storage medium can store the program in a "non-transitory tangible medium." The program includes, but is not limited to, a software program or a computer program. [Explanation of symbols]

[0131] 1. Information Processing Systems 10, 10A, 10B Information processing device 20, 20A, 20B, 20C Information processing device (server) 30, 30A, 30B, 30C database 110, 210 Processing Unit (CPU) 120, 220 network communication interface 130, 230 memory 131, 231 Operating Systems 132, 232 Network Communication Module 133 App Data 134 Processing Module 135 Acquisition Module 136 Output Module 137 Reading Module 138 Display Control Module 150 User Interface 151 Display 152 Input Device 170, 270 communication bus 233 First User Information 234 Job Information 235 Secondary User Information 236 Third User Information 240 Control Module 241 Reception Module 242 Acquisition Module 243 First Specific Module 244 Second Identification Module 245 Output Module 246 Detection Module

Claims

1. The information processing device Accepting registration of job information for the recruitment service; Acquiring usage history information of users who use services other than the job recruitment service; Identifying first work-related information relating to work based on the usage history information; Identifying job information to be recommended to the user based on the first job-related information and second job-related information related to jobs included in the job information; outputting the identified job information to a processing device used by the user, the outputting displaying a identifiable indication that the job information is recommended; An information processing method that performs the above.

2. Identifying the first work-related information includes: identifying a first brand that provides work based on the brand of the store used or the product purchased that is included in the usage history information; Identifying the job information includes: identifying job information to recommend to the user based on the identified first brand and a second brand that provides jobs included in the second job-related information; The information processing method according to claim 1 .

3. Identifying the first work-related information includes: identifying a first category of work based on a category related to a store used or a purchased product included in the usage history information; Identifying the job information includes: identifying job information to be recommended to the user based on the identified first category and a second category of jobs included in the second job-related information; The information processing method according to claim 1 .

4. Identifying the first work-related information includes: Identifying a location where the user uses the other service based on the usage history information, and identifying a first work location based on the usage location, Identifying the job information includes: identifying job information to be recommended to the user based on the identified first work location and a second work location included in the second work-related information; The information processing method according to claim 1 .

5. Detecting a specific event related to a payment based on the usage history information; The outputting step includes: outputting job information recommended to the user when the specific event is detected; The information processing method according to claim 1 .

6. Identifying a payment deadline based on the usage history information; The outputting step includes: outputting job information recommended to the user a predetermined period before the payment deadline; The information processing method according to claim 1 .

7. Identifying the first work-related information includes: Identifying a first skill related to the user's work from the usage history information; Identifying the job information includes: identifying job information to recommend to the user based on the identified first skill and a second skill required of an applicant included in the second job-related information; The information processing method according to claim 1 .

8. Identifying the first work-related information includes: Identifying a time period in which the user uses the other service based on the usage history information; identifying a first work time slot for the job based on the identified time slot; Identifying the job information includes: identifying job information to be recommended to the user based on the identified first working time period and a second working time period of a job included in the second job-related information; The information processing method according to claim 1 .

9. In the information processing device, Accepting registration of job information for the recruitment service; Acquiring usage history information of users who use services other than the job recruitment service; Identifying first work-related information relating to work based on the usage history information; Identifying job information to be recommended to the user based on the first job-related information and second job-related information related to jobs included in the job information; outputting the identified job information to a processing device used by the user, the outputting displaying a identifiable indication that the job information is recommended; A program that executes the following.

10. a reception unit that receives registration of job information to the job service; an acquisition unit that acquires usage history information of users who use services other than the job recruitment service; a first identification unit that identifies first work-related information related to work based on the usage history information; a second identification unit that identifies job information to be recommended to the user based on the first job-related information and second job-related information related to a job included in the job information; an output unit that outputs the identified job information to a processing device used by the user, the output unit displaying that the job information is recommended in a identifiable manner; An information processing device having the above.

Images