Information processing method, program, and information processor

Abstract

To enable simple and flexible recruitment when recruiting by using a group to which one or more workers belong.SOLUTION: An information processing method causes an information processor to execute: receiving selection of a plurality of groups from among groups to which one or a plurality of users belong, from another information processor used by a business operator; setting priorities for each group within the plurality of groups; and publishing, on the basis of priorities of each group, job offer information for each group.SELECTED DRAWING: Figure 12

Description

Technical Field

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

Background Art

[0002] Conventionally, there is known a technique for setting labor conditions specific to a worker in accordance with the experience, skills, etc. of a user (also referred to as a "worker") who applies for a job opening. For example, there is known a technique for setting the specific salary of this worker based on the job conditions and basic salary associated with the job opening and the work history information of the worker (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] As described above, in the above technique, a specific salary can be set for each individual worker. However, even when the business operator who hires the worker wants to collectively manage the labor conditions including the specific salary for a plurality of workers including the newly registered worker for the service, the labor conditions have to be set for each worker, and complicated processing and management are required.

[0005] On the one hand, there is also a method in which an employer registers a group of workers, creates and publishes job offers only for that group, and thereby uniformly sets the working conditions for the group of workers registered in that group. However, since the scope of publication of job offers is limited to that group and the number of workers in the original population is small in the first place, there is a possibility that the number of workers desired to be recruited will not gather. If they do not gather, the employer must create job offers for another group again or change the conditions by itself, and thus complicated processing and management are still required.

[0006] One of the objectives of the present disclosure is to provide an information processing method, a program, and an information processing apparatus that enable simple and flexible job recruitment when recruiting workers using a group or groups to which one or more workers belong.

Means for Solving the Problem

[0007] In an information processing method according to an embodiment of the present disclosure, an information processing apparatus receives a selection of a plurality of groups out of each group to which one or more users belong from another information processing apparatus used by an employer, sets a priority for each group within the plurality of groups, and publishes job offers for each group based on the priority of each group.

Effect of the Invention

[0008] According to the disclosed technology, simple and flexible job recruitment is enabled when recruiting workers using a group or groups to which one or more workers belong.

Brief Description of the Drawings

[0009]

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[0010] 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 descriptions are omitted.

[0011] [Embodiment] In this embodiment, in a platform that provides job information (also referred to as a "job information providing platform"), a group that can be selected by a business operator is provided, and it is possible to set common labor conditions for one or more workers belonging to the group. Thereby, when a business operator wants to set common labor conditions without setting individual labor conditions for individual workers, the business operator can set a group and set the labor conditions corresponding to this group for the workers belonging to the group. Note that when the worker is referred to as the first user and the business operator is referred to as the second user, and the two are not distinguished, they may be referred to as "users".

[0012] Further, in this embodiment, when a business operator sets job information for a service (hereinafter also referred to as a "job service") that enables viewing, application, etc. of job information provided on the job information providing platform and discloses it to each group, a priority is set for each group, and the job information is disclosed in order based on the priority. Also, in this embodiment, for each condition information of the recruitment conditions in the job information, the system side appropriately sets items for which the business operator has not made settings.

[0013] <System Configuration Example> FIG. 1 is a diagram showing each configuration example of the information processing system 1 in the embodiment. In the example shown in FIG. 1, each information processing device 10A, 10B used by each user, an information processing device or server 20 that manages the job information providing platform, for example, a server or database 30 that manages user data, group data, job data, etc. are connected via a network N. Note that any number of information processing devices 10A, 10B are connected to the network N, and when they are not individually distinguished, they may also be referred to as information processing device 10.

[0014] The information processing device 10 is, for example, a smartphone, a computer, a tablet terminal, or the like. By installing an application (hereinafter also referred to as a "job hunting application") that executes the job hunting service disclosed in the embodiment, the information processing device 10 can provide the job hunting service to the user. Further, when the job hunting service is implemented on a web page, the information processing device 10 can also use the job hunting service using a web browser.

[0015] The information processing device 20 is, for example, a server and may be composed of one or more devices. Further, the information processing device 20 manages a job information providing platform, provides job information, registers users, sets groups, and processes job browsing, applications, and the like. Hereinafter, the information processing device 20 is also referred to as the server 20.

[0016] The database 30 has a storage unit that stores or manages user data, group data, job data, etc. of users registered in the job hunting service.

[0017] <An example of the configuration of each device> FIG. 2 is a block diagram showing an example of the information processing device 10 according to the embodiment. The information processing device 10 includes one or more processing devices (CPUs) 110, one or more networks 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 (keyboard and / or mouse or some other pointing device, etc.) 152. Further, the user interface 150 may be a touch panel.

[0019] Memory 130 is, for example, a high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state storage devices, and may also 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 storage devices. Further, memory 130 may be a computer-readable non-transitory recording medium.

[0020] As another example of memory 130, it may be one or more storage devices installed remotely from CPU 110. In certain embodiments, memory 130 stores programs, modules, and data structures related to the following job hunting application, or subsets thereof.

[0021] Operating system 131 includes, for example, procedures for processing various basic system services and executing tasks using hardware.

[0022] Network communication module 132 is used, for example, to connect 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] App data 133 includes data processed when the user uses the job hunting service. For example, app data 133 includes user information and information obtained from server 20. Specifically, job hunting information related to job openings is included in app data 133. This job hunting information will be described later with reference to FIG. 7.

[0024] The service processing module 134 executes each process in the job offer information providing platform provided by the server 20. For example, the service processing module 134 includes an acquisition module 135, an output module 136, and a processing module 137, which will be described later. Also, the service processing module 134 may change the processing content according to whether the user who has logged in to the job offer information providing platform is a business operator or a worker. Further, the service processing module 134 corresponds to the above-described job application or web browser.

[0025] For example, assume that the information processing device 10A is a device used by a user on the business operator side, and the information processing device 10B is a device used by a user on the worker side. Hereinafter, the reference numeral of the information processing device 10A on the business operator side is appended with A, and the reference numeral of the information processing device 10B on the worker side is appended with B. Hereinafter, an example of dividing the processing according to the logged-in user for the job application will be described, but the business operator application and the worker application may be separately implemented.

[0026] ≪Business operator side≫ First, each process in the information processing device 10A on the business operator side will be described. The acquisition module 135A acquires a user operation on a button (an example of a UI component) within the display screen displayed on the display 151A. For example, the acquisition module 135A acquires, via the user interface 150A, a command corresponding to a click operation on a job offer setting button within a web page or an application screen. The setting button is a button for a business operator to set recruitment conditions and the like when recruiting a job. At this time, it is possible to publicly disclose job offer information to each group to which one or more workers belong as the disclosure destination of the job offer information.

[0027] The group is a group generated by the operating organization of the job information providing platform or by an operator including a store or an operator. It is possible to set common working conditions for a plurality of workers belonging to the group. An operator can select the group to which a worker belongs for the workers who use the job service.

[0028] Further, the acquisition module 135A may acquire, via the user interface 150A, a command corresponding to a click operation on a job setting button within a web page or an application screen. The job setting button is a button used when an operator wants to set and publish job information.

[0029] The job information includes generally public job information that is generally made public to users registered in the job service, and limited public job information that is made public only to users within a predetermined group.

[0030] The output module 136A outputs the job information set by the operator-side user and the job setting request to the server 20.

[0031] The processing module 137A performs processes such as creation of the above-described group, setting of job information, and setting of each condition information of the job for the group. For example, the processing module 137A receives an operation by an operator, cooperates with the server 20, and performs a process of including a predetermined worker in a predetermined group, a setting process of common condition information included in the job information, a setting process related to the publication of job information for each group, and the like.

[0032] The display control module 138A controls the display of one screen of the job application or the web page. For example, the display control module 138A controls to display a group creation screen, a job information setting screen, a setting screen for each group, etc. on the display 151A.

[0033] ≪Worker side≫ Next, each process in the information processing apparatus 10B on the worker side will be described. The operating system 131B accesses the server 20 based on the operation of the worker, downloads and installs the program of the job hunting application. Thereby, the service processing module 134B becomes executable.

[0034] Also, the service processing module 134B may be a job hunting application as described above, or may be a web browser. The service processing module 134B accesses the URL providing the job information providing platform, acquires screen information regarding the job service from the server 20 via the job hunting application, or transmits information to the server 20.

[0035] The acquisition module 135B acquires the user operation for each button in the display screen displayed on the display 151B. For example, the acquisition module 135B acquires the registration information set by the user operation of the worker on the user registration screen.

[0036] When the registration information of a new user is set based on the user operation, the output module 136B transmits the registration information and the new registration request to the server 20. The registration information includes, for example, the name, address, telephone number, etc. of the user input by the worker and the stored business operator information. When the server 20 receives the new registration request, it performs the registration process of the new user based on the registration information.

[0037] Also, when the worker performs an operation to view job information, the output module 136B outputs a view request to the server 20. Also, when the worker performs an operation to apply for a job from the job information viewing screen, the output module 136B outputs an application request to the server 20.

[0038] The processing module 137B performs processing related to the job service. For example, on the worker side, it has functions such as a function to notify favorite jobs, a message function with business operators, and a function to notify recommended jobs.

[0039] The display control module 138B controls the display of the screens of the job application and web pages. For example, the display control module 138B controls to display a user registration screen, a job information viewing screen, a job application screen, etc. on the display 151B.

[0040] Note that one or more processing devices (CPUs) 110 read out and execute each module from the memory 130 as necessary. For example, one or more processing devices (CPUs) 110 may configure the communication unit by executing the network communication module 132 stored in the memory 130. Also, one or more processing devices (CPUs) 110 may configure the service processing unit, the acquisition unit, the output unit, the processing unit, and the display control unit by executing the service processing module 134, the acquisition module 135, the output module 136, the processing module 137, and the display control module 138 stored in the memory 130, respectively. Further, the respective processes of the service processing module 134, the acquisition module 135, the output module 136, the processing module 137, and the display control module 138 may be executed by one or more processing devices (CPUs) 110.

[0041] In other embodiments, the service processing module 134, the acquisition module 135, the output module 136, the processing module 137, and the display control module 138 may be stand-alone applications stored in the memory 130 of the information processing apparatus 10. Examples of the stand-alone 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 still other embodiments, the service processing module 134, the acquisition module 135, the output module 136, the processing module 137, and the display control module 138 may be add-ons or plugins to another application.

[0042] Each of the elements shown above may be stored in one or more of the aforementioned storage devices. Each of the modules shown above corresponds to a set of instructions for performing the functions described above. The modules or programs (i.e., sets of instructions) shown 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 one embodiment, the memory 130 may store a subset of the modules and data structures shown above. Further, the memory 130 may store additional modules and data structures not described above.

[0043] As described above, the business operator's application and the worker's application may each be implemented as separate applications. In this case, the worker downloads and installs the program of the job application for workers from a predetermined website or the like to his / her information processing device 10B, and the business operator downloads and installs the program of the job application for business operators from a predetermined website or the like to his / her information processing device 10A, whereby the above-described job applications become available respectively.

[0044] FIG. 3 is a block diagram showing an example of a server 20 according to an embodiment. The server 20 includes one or more processing units (CPUs) 210, one or more networks or other communication interfaces 220, a memory 230, and one or more communication buses 270 for interconnecting these components.

[0045] The server 20 may optionally include a user interface 250, which may include a display device (not shown) and a keyboard and / or a mouse (or other input device such as some other pointing device, not shown).

[0046] The memory 230 is, for example, a high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state storage devices, and may also 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 storage devices. Further, the memory 230 may be a computer-readable non-transitory recording medium.

[0047] Also, other examples of the memory 230 can include one or more storage devices installed remotely from the CPU 210. In certain embodiments, the memory 230 stores the following programs, modules, and data structures, or subsets thereof.

[0048] The operating system 231 includes, for example, procedures for processing various basic system services and executing tasks using the hardware.

[0049] The network communication module 232 is used, for example, to connect the server 20 to other computers via one or more communication interfaces 220 and one or more communication networks such as the Internet, other wide area networks, local area networks, metropolitan area networks, etc.

[0050] The user data 233 includes information of users who utilize the job information providing platform. For example, the user data 233 includes, in association with each user ID, the user's name, address, phone number, group, etc. The user data 233 will be described later with reference to FIG. 4.

[0051] The group data 234 includes data regarding groups that are utilized, for example, when a job advertisement is to be issued only to one or more workers in common. For example, the group data includes a group name, a business operator, a generation entity, a user ID, etc. The group data 234 will be described later with reference to FIG. 5 or FIG. 6.

[0052] The job opening data 235 includes one or more job opening information registered in the job opening information providing platform or job opening service. For example, the job opening data 235 includes information such as the job opening date, working hours, public / limited, group, hourly wage, etc. The job opening data 235 will be described later with reference to FIG. 7.

[0053] The service control module 236 manages the processing related to job openings in the job opening information providing platform. For example, the service control module 236 has, as processing related to job openings, a reception module 237, a setting module 238, a publication module 239, and a proposal module 240.

[0054] When a setting operation regarding the recruitment conditions for job openings by an operator is performed, the service control module 236 acquires each setting information together with a recruitment request from the information processing device 10A used by the operator.

[0055] The reception module 237 receives the selection of a plurality of groups from among the groups to which one or more users belong from another information processing device (information processing device 10A) used by the operator. For example, the reception module 237 receives the selection of a group including a group of workers that the operator wants to recruit for job openings from among the groups generated by the operator or the operation organization.

[0056] For example, the operator selects, from among the group lists displayed on the screen of the information processing device 10A, a group including a group of workers who have worked at the operator's store in the past, a group including a group of workers who are okay with early morning work, etc., which are groups including the group of workers that the operator wants to recruit for job openings. The reception module 237 acquires the identification information of the selected group from the information processing device 10A.

[0057] In addition, when the operator sets job opening information, the service control module 236 may identify a group that matches the set job opening through similarity determination between each condition information of the recruitment conditions in the job opening information and the attribute information of the group, and select and receive the identified group.

[0058] The setting module 238 sets a priority for each group within the selected multiple groups. The priority may be set by the operator for each group, or may be set by the service control module 236 for each group using predetermined rules or a learning model.

[0059] For example, the setting module 238 may calculate the similarity between each condition information of the recruitment conditions set for the job information and each attribute information set for the group, and set the priority for the group in descending order of the similarity. Also, the setting module 238 may input each condition information and each attribute information into a learning model that has learned the relevance using the each condition information and each attribute information as learning data to obtain a score regarding similarity, and set the priority based on this score.

[0060] The disclosure module 239 discloses job information for each group based on the priority set for each group. For example, the disclosure module 239 sequentially discloses job information to each worker within the group in descending order of the priority. As a specific example, each time the disclosure time of each group set in the order of priority arrives, the disclosure module 239 discloses the job information set for that group to each worker belonging to that group. "Disclosing job information" includes, for example, making the job information viewable when a worker views a list of job offers on a job information providing platform. The disclosure time represents, for example, the disclosure date and time when the job information is disclosed, or the disclosure timing such as the disclosure date.

[0061] According to the above-described processing, even if the number of workers required for recruitment does not gather among the group of workers in a certain group, the job information is disclosed to the group of workers in the next group according to the priority order, so there is no need to reset the job information or set the group each time, and the recruitment and management of job offers for the operator becomes simple. Also, the operator can set the priority for the group for which the operator wants to recruit workers according to the recruitment, disclose the job information in the order of the group of workers suitable for the recruitment content, and enable a more flexible job offer setting than the current system.

[0062] For example, as described above, according to the present system 1, by setting priorities for each group, it becomes possible to automatically distribute job information from the highest priority, taking into account the number of job openings and the disclosure time (e.g., the disclosure date and time) of the job offers. Specifically, job information is distributed to Group A with the highest priority. If the number of recruits has not been reached after a certain period, job information (which may have different recruitment conditions from those of Group A) is distributed to Group B. In this case, even if job information is disclosed to Group B, basically, the job information remains disclosed to Group A. During the period when job information is not disclosed to Group B (i.e., the period when it is only disclosed to Group A), workers belonging to Group B cannot view this job information. Also, when job information is only disclosed to Group A, workers belonging to a group with a lower priority than Group A (e.g., Group B) cannot view the job information disclosed to Group A.

[0063] In addition, the reception module 237 includes receiving a setting of disclosure information regarding the disclosure time of job information for each group from another information processing device (e.g., the information processing device 10A). The disclosure information includes information that can specify the disclosure time, such as a specific disclosure time or the number of days from the date of first disclosure. For example, when an operator sets the disclosure time for each group from the setting screen of the information processing device 10A, the reception module 237 of the server 20 receives the disclosure information for each group from the information processing device 10A.

[0064] The disclosure module 239 includes disclosing job information to the next group to be disclosed when the disclosure time based on the disclosure information of the next group to be disclosed arrives. For example, when the disclosure time is set for each group, the disclosure module 239 discloses job information in the order of the groups for which the disclosure time has arrived.

[0065] By the above process, priorities are assigned to each group in advance. In the case where there is a group for which the number of applicants has not been collected, job offers will be automatically disclosed to the next group based on the priority. Therefore, the business operator does not need to determine whether to disclose to each group each time, and the management of job offers becomes easier.

[0066] Also, the disclosure module 239 may include disclosing job offers to the next group to be disclosed before the disclosure time of the next group when the number of users corresponding to the number of applicants set for the group for which job offers are being disclosed has been collected. For example, the service control module 236 counts the number of applicants of workers belonging to the group for which job offers are being disclosed. When the number of applicants reaches the number of applicants set for the group for which job offers are being disclosed, the disclosure module 239 may disclose job offers for the next group to be disclosed at that time. Note that the number of applicants may be the number of people actually hired.

[0067] Here, when priorities 1, 2, and 3 are assigned to groups A, B, and C, first, job offers are disclosed to group A with priority 1. At this point, the group for which job offers are being disclosed is group A, and the next group to be disclosed is group B with priority 2. The number of applicants set for the group for which job offers are being disclosed at this time is the number of applicants for group A. When the number of users corresponding to the number of applicants for group A has been collected, job offers may be disclosed to group B without waiting for the disclosure time of group B.

[0068] Next, when the disclosure time of group B with priority 2 arrives and job offers are disclosed to group B, the groups for which job offers are being disclosed become groups A and B, and the next group to be disclosed becomes group C. The number of applicants set for the groups for which job offers are being disclosed at this time is the sum of the number of applicants for group A and the number of applicants for group B. When the number of users corresponding to the sum has been collected, job offers may be disclosed to group C without waiting for the disclosure time of group C.

[0069] By the above processing, when the number of recruited workers reaches the number of recruits set for each group, recruitment can be carried out for the workers in the next group, so the possibility of reaching the total number of recruits earlier can be increased.

[0070] The proposal module 240 proposes to change the recruitment conditions set for the currently public group if the workers of the recruitment number of the currently public group do not gather a predetermined number of days before the public release date of the next group to be released. For example, if the number of applicants counted by the service control module 236 on the day a predetermined number of days before the public release date of the next group to be released is less than the recruitment number of the currently public group, the proposal module 240 proposes to change the recruitment conditions such as salary and working hours. As a specific example, the proposal module 240 may output inquiry information for selecting whether to approve or reject increasing the salary or reducing the working hours for the salary or working hours included in the condition information of the recruitment conditions to the information processing apparatus 10A of the business operator. Note that the salary is represented by hourly wage × working hours and may be replaced by the hourly wage.

[0071] Also, the proposal module 240 may determine the content of the proposal using machine learning. For example, the proposal module 240 can learn the relevance of past recruitment content, the attributes of the workers who applied, etc., and can propose what recruitment conditions will increase the probability of application. The processing related to machine learning will be described later using specific examples.

[0072] By the above processing, it becomes possible to increase the possibility of reaching the recruitment number in the currently public group. For example, when workers in a group with a high priority are needed, the possibility of application can be improved by changing the recruitment conditions.

[0073] In addition, the reception module 237 may include receiving an approval operation from another information processing device (e.g., the information processing device 10A) regarding a change in recruitment conditions. For example, the reception module 237 obtains response information to inquiry information for selecting whether to approve or reject the above-described change content of the recruitment conditions from the information processing device 10A. At this time, when the business operator selects approval, the reception module 237 receives the approval operation.

[0074] In addition, the proposal module 240 may include changing the recruitment conditions of the current group according to the approval operation. That is, the proposal module 240 changes the condition information of the recruitment conditions of the current group triggered by the approval operation of the business operator, and if the business operator rejects the proposal, no change process is performed.

[0075] By the above processing, it is possible to prevent an unintended change from being made by executing a change process triggered by the approval operation of the business operator regarding the proposed content related to the recruitment conditions from the system side.

[0076] In addition, when public information regarding the disclosure timing of job information is not set for at least one group among a plurality of groups, the proposal module 240 may include obtaining public information from a learning model that has learned the relationship between each condition information included in the recruitment conditions set for each group and the public information. For example, for the group with the highest priority, the proposal module 240 may disclose it in the shortest time, and for the group with the second highest priority, propose when to disclose it (public information) by machine learning using the previous recruitment conditions, the attributes of the applying workers, etc. as learning data.

[0077] In addition, the proposal module 240 may include inputting each condition information of at least one group into the above-described learning model to obtain public information. As a specific example, the proposal module 240 may estimate using a learning model whether the number of recruits will be gathered under the recruitment conditions of the group currently being disclosed, and if it is unlikely that the number of recruits will be gathered, determine the disclosure of job information to the next group to be disclosed.

[0078] In addition, the proposal module 240 may set the acquired public information to at least one group for which the public information is not set. As described above, the public information may be set by machine learning, and may include information on the release time itself, or information including the availability of the next group to be released based on the information on the release time and the possibility of the number of applicants for the group being announced gathering.

[0079] Through the above processing, even if the business operator does not set the release time for each group, it becomes possible to determine when to release or set the release time for the group for which the release time has not been set, reducing the burden on the business operator.

[0080] In addition, the reception module 237 may include receiving the setting of the number of applicants and the budget for the job offer itself from another information processing device (e.g., information processing device 10A). For example, the reception module 237 may receive the setting of the number of applicants and the budget for a specific job offer together with a job offer setting request from the information processing device 10A of the business operator, and may not receive the setting of detailed recruitment conditions in some cases.

[0081] In this case, the proposal module 240 inputs the information on the number of applicants and the budget for the received job offer into a learning model that has learned the relationship between at least the information on the number of applicants and the budget for the specific job offer and the condition information including the number of applicants, the release time, and the hourly wage set for each group, and may include obtaining the condition information including the number of applicants, the release time, and the salary in each group. In addition, the proposal module 240 sets the condition information including the obtained number of applicants, release time, and salary to the corresponding group for which the condition information is not set.

[0082] Through the above processing, as long as the business operator sets the total number of applicants and the budget for the job offer, the system 1 can appropriately set each condition information of the other recruitment conditions based on past cases and the like, making it possible to further reduce the burden on the business operator.

[0083] Before the arrival of the publication time based on the publication information of the next group to be published, the proposal module 240 may include determining whether to change the recruitment conditions of the group in which the job information is being published or to publish the job information in the next group to be published, based on the update information of each condition information input to the learning model. For example, after a predetermined period has elapsed since the group being published was published, the proposal module 240 obtains by machine learning whether the number of recruits for the group being published is likely to be collected. For example, an index indicating the likelihood of the number of recruits being collected is output by machine learning.

[0084] At this time, if the index indicating the likelihood of the number of recruits being collected is less than the threshold value, the proposal module 240 determines whether to propose changes to conditions such as salary and working hours included in the recruitment conditions of the group being published or to publish the job information in the next group. If the index indicating the likelihood of the number of recruits being collected is greater than or equal to the threshold value, the publication of the group being published is continued. The proposal module 240 outputs inquiry information for inquiring the business operator about whether to publish or change to the information processing device 10A. The proposal module 240 determines whether to perform a change process or a publication process according to the inquiry result from the information processing device 10A. When performing a publication process, it instructs the publication module 239 to publish to the next group to be published.

[0085] Through the above processing, after a predetermined period has elapsed since the job information was published, it becomes possible to appropriately execute any of the review of conditions, publication to the next group, and continued publication to the group being published according to the current situation.

[0086] In addition, the setting module 238 identifies the characteristic information of each group based on the attribute information set for each group. For example, the setting module 238 may extract attribute information common to each worker from attribute information such as the gender, salary, and working day of the worker set for each group, and use the extracted attribute information as characteristic information. As a specific example, the characteristic information is that it is possible to work on Saturdays and Sundays, and there is work experience at a predetermined store.

[0087] Further, the setting module 238 may determine the priority of each group using the identified feature information. The setting module 238 may calculate the degree of matching between the feature information and the condition information of the job requirements information, and determine the priority order in descending order of the degree of matching. Also, for the jobs that each worker within each group has matched, by learning the relevance between the job requirements information of the job and the attribute information of the worker who has matched, the setting module 238 may obtain the degree of matching between the feature information of each group and a predetermined job using this learning model.

[0088] Through the above processing, it becomes possible to automatically set the priority of each group based on past cases and the like, and it becomes possible to further reduce the burden on the business operator.

[0089] Each of the elements shown above may be stored in one or more of the aforementioned storage devices. Each of the modules shown above corresponds to a set of instructions for executing the functions described above. The modules or programs (i.e., sets of instructions) shown above do not have to 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 one embodiment, the memory 230 may store a subset of the modules and data structures shown above. Furthermore, the memory 230 may store additional modules and data structures not described above.

[0090] One or more processing devices (CPUs) 210 read out and execute each module from the memory 230 as necessary. For example, one or more processing devices (CPUs) 210 may configure the communication unit by executing the network communication module 232 stored in the memory 230. Also, one or more processing devices (CPUs) 210 may configure the service control unit, reception unit, setting unit, publication unit, and proposal unit by executing the service control module 236, reception module 237, setting module 238, publication module 239, and proposal module 240 stored in the memory 230, respectively. Further, the processing of each of the service control module 236, reception module 237, setting module 238, publication module 239, and proposal module 240 may be executed by one or more processing devices (CPUs) 210.

[0091] FIG. 3 shows a "server", but FIG. 3 is intended to explain various features that may exist in a set of servers rather than as a structural overview of the embodiments described in this specification. In practice, as will be recognized by those skilled in the art, the separately shown items may be combined and some items may be separated. For example, the items separately shown in FIG. 3 may be implemented on a single server, and a single item may be implemented by one or more servers.

[0092] The database 30 may have the same configuration as the configuration shown in FIG. 3. Note that at least one of the user data 233, group data 234, and job offer data 235 shown in FIG. 3 may be stored in the storage unit of the database 30.

[0093] <An example of a data structure> FIG. 4 is a diagram showing an example of user data 233 according to an embodiment. In the user data 233, information regarding each member user created by a user who uses the job recruitment service is managed. The "user ID" includes user identification information (user ID: Identifier) for the server 20 to uniquely identify the user. The user ID is associated with "user information".

[0094] The "user information" includes "name", "address", "phone number", etc., which are personal information of the user (e.g., worker). Also, the user ID may be associated with a "group" set by the business operator. Note that the user ID may be included in one of the user information. Also, the user information may include an email address, a password, etc.

[0095] FIG. 5 is a diagram showing an example of group data 234 according to an embodiment. The "group name" in the group data 234 includes the name of the group. Regarding the group name, it may be generated by the operation organization of the job information providing platform or may be independently generated by the business operator. The group name is associated with "business operator", "generation entity", "user ID", etc., and the group ID may be associated as the primary key.

[0096] "Operator" includes operators who can select groups. "Generator" includes the entity that generated the group. "User ID" includes the user IDs of the workers belonging to the group. For example, if it is a group of "AAA Japan Experience" generated by the "Operation Organization", the operator of "All AAA Japan Direct Stores" can select this group. Also, if it is a group of "AAA Experience" generated by the "Operation Organization", for example, the operator of "All Franchised and Direct Stores of AAA" can select this group. Also, if it is a group of "Morning Shift OK" generated by "AAA Shibuya Store", only the "AAA Shibuya Store" that generated this group can select this group. "AAA Japan Direct Store" represents a store operated under the umbrella of AAA Japan, and "AAA Franchised Store" represents a franchise store of AAA's franchise.

[0097] Also, the "Favorite" group is a general-purpose group name, but it is a group generated by the operation organization for each operator. Depending on the settings of the operation organization, for example, the "Favorite" group of "AAA Shibuya Store" can only be selected by the operator of "AAA Shibuya Store". If it is a group of "AAA Japan Experience (Minato Ward)" generated by "AAA Akasaka Store", in addition to the "AAA Akasaka Store" that generated this group, other "AAA Japan Direct Stores" located in the Minato Ward, such as Roppongi Store, can also select this group. In this case, when the group is generated by AAA Akasaka Store, the service control module 236 sets each store in the Minato Ward with the store name of "AAA" as the "operator" when the "Minato Ward" is selected as the regional information.

[0098] FIG. 6 is a diagram showing an example of the hierarchical structure of group data 234 according to the embodiment. For example, the structure shown in FIG. 6 is exemplified by AAA Japan, which concludes franchise (FC) contracts with a plurality of franchise stores. For example, it is assumed that AAA Japan Co., Ltd. is engaged in FC expansion and has concluded an FC contract with the "X Individual Store". At this time, conventionally, AAA Japan could grasp the workers who worked at the company-owned stores under its umbrella, but could not grasp the workers who worked at the franchise stores under the X Individual Store with a different operator. For example, AAA Japan can grasp the workers who worked at the AAA Shibuya store, but could not grasp the workers who worked at the AAA Ebisu store.

[0099] Therefore, the operation organization of the job information providing platform acquires information on each store using the same store name "AAA" including FC expansion from AAA Japan, and generates a hierarchical structure as shown in FIG. 6. For example, using the example shown in FIG. 5, in the case of the group of "AAA Japan's experience", since there are no restrictions other than the restrictions of AAA Japan, this group can be selected in all company-owned stores of AAA Japan (Shibuya store, Tokyo Station store, Roppongi store). On the other hand, for the group of "AAA experience", since both AAA Japan and the FC use the store name of AAA, this group can be selected in all stores of the AAA franchise (Ebisu store, Ebisu West Exit store, Shibuya store, Tokyo Station store, Roppongi store, etc.).

[0100] FIG. 7 is a diagram showing an example of job data for products according to the embodiment. The "job ID" includes identification information of the job information. The job information includes each information such as "job posting date", "working hours", "public / limited", "group", "hourly wage", etc. associated with the job ID. In the example shown in FIG. 7, the "hourly wage" is used, but the wage of hourly wage × working hours may be used.

[0101] The "Job Requirement Date" includes the date (which may be a specified period) when workers are needed by the business operator. The "Working Hours" includes the working hours of the worker on the Job Requirement Date. The "Public / Limited" indicates whether the job information is publicly available to the general public or limited to a selected predetermined group. The "Hourly Wage" includes the hourly wage for the job. Note that in the case of "Public / Limited", both may exist. In this case, the hourly wage corresponding to the predetermined group with "Limited" disclosure may be set higher than the hourly wage for general public disclosure (for example, refer to job IDs "J002" and "J003" in Figure 7).

[0102] Here, using the hierarchical structure of the groups shown in Figure 6, job information and priorities for each group may be set. For example, the setting module 238 may set the job information for a group with work experience in the lower layer (e.g., store) based on the job information for a group with work experience in the upper layer (e.g., business operator, store name). As a specific example, the condition information includes conditions such as not setting the hourly wage in the lower layer higher than that in the upper layer. Also, the setting module 238 may set the priority of a group with work experience in the upper layer higher than that of a group with work experience in the lower layer. The above is merely an example and is not limited to this example.

[0103] <Specific Example> Below, three main specific examples are given regarding the setting entities of each condition information in the recruitment conditions for job information. Figure 8 is Setting Example 1 where the business operator mainly sets the condition information, Figure 9 is Setting Example 2 where the business operator sets some condition information and the remaining condition information (e.g., publication date) is set by the system side, and Figure 10 is Setting Example 3 where the condition information other than the minimum condition information for the number of recruits, budget, and priority is set by the system side. Note that in Figure 10, the priority may also be set by the system side.

[0104] FIG. 8 is a diagram showing a first example of setting each condition information of job offer information according to the embodiment. FIG. 8(A) shows an example of basic condition information for a job offer, and FIG. 8(B) shows an example of detailed condition information for a job offer. In the example shown in FIG. 8(A), the basic hourly wage is set at 1,100 yen, and the total number of recruits is set at 7. The basic hourly wage is set by the system or the business operator, and the number of recruits is set by the business operator.

[0105] In the example shown in FIG. 8(B), for each group (A, B, Z, Y), condition information for priority (required), number of recruits (optional), hourly wage (optional), and publication date (required) is set. For example, each piece of information for the required priority and publication date is set by the business operator. For the optional number of recruits and hourly wage, if not set by the business operator, the setting module 238 sets them according to a predetermined standard. For example, the setting module 238 may set using machine learning or using rule-based conditions. Also, for the hourly wage, if not set by the business operator, the setting module 238 may set the hourly wage for each group based on the basic hourly wage. Note that for the publication date, if there is no time specified, the job offer information may be published at a predetermined time (e.g., 0:00 am) of the set publication date.

[0106] Also, for each group, for example, group A is a group to which workers with high evaluations belong, group B is a group to which workers who are okay with working at night and in the early morning belong, group Y is a group to which workers with work experience at the same store belong, and group Z is a group to which workers with work experience at other stores in the same series belong, but it is not limited to this example. The priority is in the order of groups A, B, Y, Z.

[0107] Also, if the desired number of applicants is not gathered by the set publication date, the publication module 239 publishes the job offer information to the next priority group. In this case, as described above, the proposal module 240 may present, for example, the number of views of the worker for this job offer, and propose whether it is better to change any conditional information of the recruitment conditions or to publish the job offer information to the next group. For example, the proposal module 240 estimates the matching degree of each of the two options and proposes the one with the higher matching degree to the business operator. The proposal also includes changes in hourly wage (e.g., from 1,100 yen to 1,200 yen) or working hours (recruitment hours) (e.g., from 6-hour work to 4-hour work).

[0108] FIG. 9 is a diagram showing a second example of setting each conditional information of job offer information according to an embodiment. FIG. 9(A) shows an example of basic conditional information for a job offer, and FIG. 9(B) shows an example of detailed conditional information for a job offer. FIG. 9(A) is the same as FIG. 8(A), but the difference between FIG. 9(B) and FIG. 8(B) is the presence or absence of setting of the publication date. In the example shown in FIG. 9(B), the setting of the publication date is not essential.

[0109] Here, regarding the publication date, the proposal module 240 may obtain the publication date using a learning model that has learned the relevance between each conditional information included in past recruitment conditions, the attribute information of each worker, and the number of days until application. Also, the proposal module 240 may obtain a matching rate using a learning model that has learned the employment matching degree between each conditional information included in past recruitment conditions and the attribute information of each worker. When the matching rate is obtained, if the matching rate is less than the threshold value, the job offer information is published to the next group, and if the matching rate is equal to or higher than the threshold value, the publication of the current group may be continued.

[0110] FIG. 10 is a diagram showing a third example of setting each condition information of recruitment information according to an embodiment. FIG. 10(A) shows an example of basic condition information for a job offer, and FIG. 10(B) shows an example of detailed condition information for a job offer. Compared with FIGS. 8(A) and 9(A), a budget is set in FIG. 10(A). Also, in the example shown in FIG. 10(B), a priority is set, and the number of recruits is not essential but is set.

[0111] In the case of the example shown in FIG. 10, using the budget, the number of recruits, and the priority, the proposal module 240 sets the hourly wage for each group. At this time, the proposal module 240 may set the hourly wage according to rule-based criteria, or may set the hourly wage using a learned learning model. In the case of rule-based, for example, the proposal module 240 may be based on the basic hourly wage and increase the additional amount as the priority within the budget is higher. When using machine learning, the proposal module 240 may set an hourly wage with a high matching probability while satisfying the budget based on past matched learning data.

[0112] Note that in the above Examples 1 to 3, the number of recruits for each group is set. If the number of recruits within the corresponding group is not filled, the disclosure module 239 may add the unfilled number in the corresponding group to the number of recruits in the next group and disclose the recruitment information. For example, if only 3 people are gathered by the deadline instead of 4 in Group A, the number of recruits in Group B will be 4 (the original number of recruits in Group B, 3 + the shortage number in Group A, 1).

[0113] Also, regarding the number of recruits, the reason why Group A with a high priority does not have to be the total number of recruits for the job offer is that if workers are gathered only from the group with a high priority, only experienced workers will be left, and the pool of workers will not expand. Also, since there are cases where the hourly wage is high in the group with a high priority, if only workers from the group with a high priority are gathered, there may be cases where the budget is exceeded. Therefore, the setting module 238 may allow the setting of the number of recruits to be distributed to each group.

[0114] Also, when the publication date of Group B with the second-highest priority arrives, if the number of applicants for Group A has not been reached, the publication module 239 continues to publish the job offers of Group A. Also, regarding the above Examples 1 to 3, if there are 3 applicants for Group A and the job offers are published in Group B, the publication module 239 may end the publication of the job offers for Group A when there are 4 applicants among the workers of Group B. That is, the publication module 239 may end the publication of the job offers for the higher-priority group when the number of applicants is reached in the lower-priority group, including the shortage of the number of applicants in the higher-priority group.

[0115] <Application Examples of Machine Learning> Next, application pattern examples of machine learning in the embodiment will be described. First, there are at least three patterns in which machine learning is applied. Pattern 1: Before Publication Pattern 2: During Publication (During Operation Start) Pattern 3: Before Publication + During Publication

[0116] In Pattern 1, machine learning is used when setting conditional information before the publication of job offers. In Pattern 2, when job offers are published without setting conditional information (e.g., publication date) that is not a problem at the time of publication, the information at that point during publication is input into the learning model and set each time. In Pattern 3, after using machine learning for setting arbitrary conditional information (e.g., hourly wage, working hours) before the publication of job offers, information that can be obtained during the publication of job offers (e.g., number of views) is included and input into the learning model, so that the set information is updated or information that has not been set (e.g., publication date) is set.

[0117] If it is before the public release, the proposal module 240 may set the condition information of the recruitment conditions not set by the operator using machine learning. If it is during the public release, the proposal module 240 may set the condition information such as the release date, hourly wage, and number of recruits using the information available at that time, for example, the number of views, the number of people gathered, the number of days of release, etc., using machine learning. The proposal module 240 may also estimate the possibility of whether the number of recruits will be gathered or not using the attribute information of the workers in the group during the public release and the condition information of the job offer information, using machine learning.

[0118] The following shows the data that can be used as the learning data of machine learning. (A) Condition information in the same area and category (job type) · The number of recruits for all job offers (Regarding this data, if the number of recruits is large, the matching probability with workers decreases) · The number of job seekers (workers) for all job offers, for example, the number of logged-in users to the system, MAU (Monthly Active User), DAU (Daily Active User) · Hourly wage (If the hourly wage is low, the matching probability with workers decreases) · Number of recruits (If the number of recruits is large, the probability of 100% gathering for the desired number of recruits decreases) · Age (attribute information of workers) · Gender (attribute information of workers) (B) Information in the corresponding group · Number of group members · Age, gender, previous hourly wage worked, tendency of previous working months or dates or days of the week or hours of individual workers belonging to the group (attribute information of workers) For example, if there is no work on the same month / date / day of the week / hour as the recruitment conditions, the matching probability decreases · Achievements of individual workers (organizations with work experience, qualifications, etc.) (C) Information of the relevant business operator · Matching probability for previous recruitments · Number of views · Number of favorites · Age, gender, etc. of individual workers with work experience in the relevant business operator · Number of days required to reach matching

[0119] Using the above learning data, the proposal module 240 appropriately combines data to generate learning data in order to obtain desired data, and learns the relevance with the desired data. For example, when the proposal module 240 wants to output the publication date of each group, it generates a learning model that learns the relevance between the job requirements information and worker attribute information of each group and the number of days required to reach matching. Also, when the proposal module 240 wants to output the matching probability, it may generate a learning model that learns the relevance between each piece of information included in (A) to (C) and the matching probability for each job offer information.

[0120] Also, when the proposal module 240 wants to output the hourly wage of each group, it generates a learning model that learns the relevance between the job requirements information (e.g., working hours, age, gender, occupation, etc.) in (A) to (C) and the hourly wage of the match. Also, when the proposal module 240 wants to output the working hours of each group, it generates a learning model that learns the relevance between the job requirements information (e.g., hourly wage, age, gender, occupation, etc.) in (A) to (C) and the recruitment time of the match. Thereby, the proposal module 240 can propose an hourly wage and working hours suitable for each group. The information required for the learning data may be appropriately selected according to the estimated data.

[0121] <Operation Explanation> Next, the operation of the information processing system 1 according to the embodiment will be described. FIG. 11 is a flowchart showing an example of the setting process of each condition information of the job offer information according to the embodiment. FIG. 11 is an example in which the server 20 performs the setting process of each condition information of the job offer information using each piece of information input, set, and selected regarding the job offer output from the information processing apparatus 10A of the business operator.

[0122] In step S101, the service control module 236 of the server 20 generates job information including the basic hourly wage and the total number of recruitment according to a request from an operator (see, for example, FIG. 15). Regarding the basic hourly wage, the service control module 236 may automatically set it considering the region and job type.

[0123] In step S103, the reception module 237 of the server 20 receives selection information output from the information processing device 10A on whether to publicly disclose the job information from the operator to the general public or to limit the disclosure to a predetermined group.

[0124] In step S105, when the job information is limitedly disclosed to each predetermined group, the reception module 237 of the server 20 receives the priority of each group output from the information processing device 10. Note that, as described above, the server 20 may automatically set the priority using machine learning.

[0125] In step S107, the reception module 237 of the server 20 receives a selection on whether to manually set or automatically set each condition information of the job information output from the information processing device 10A.

[0126] In step S109, the reception module 237 of the server 20 receives budget information input by the operator and output from the information processing device 10A. Note that the input timing of the budget information is not limited to this timing.

[0127] In step S111, the reception module 237 of the server 20 determines whether it has received the input of public information regarding the release date for each group output from the information processing device 10A and input by the operator. If the public information has been received (step S111 - YES), the process proceeds to step S115. If the public information has not been received (step S111 - NO), the process proceeds to step S113.

[0128] In step S113, the service control module 236 of the server 20 determines to set the publication date for each group using machine learning.

[0129] In step S115, the reception module 237 of the server 20 determines whether it has received the input of the hourly wage information for each group input by the business operator and output from the information processing device 10A. If the hourly wage information has been received (step S115 - YES), the process proceeds to step S119. If the hourly wage information has not been received (step S115 - NO), the process proceeds to step S117.

[0130] In step S117, the setting module 238 of the server 20 sets the hourly wage for each group based on the basic hourly wage. For example, when there are three groups, the setting module 238 may set the hourly wage for the group with the highest priority to 1.2 times → 1.1 times → 1.0 times the basic hourly wage, or set it to basic hourly wage + 200 yen → + 100 yen → + 0 yen.

[0131] In step S119, the reception module 237 of the server 20 determines whether it has received the input of the recruitment number information for each group input by the business operator and output from the information processing device 10A (see, for example, FIG. 16). If the recruitment number information has been received (step S119 - YES), the process proceeds to step S123. If the recruitment number information has not been received (step S119 - NO), the process proceeds to step S121.

[0132] In step S121, the setting module 238 of the server 20 sets the recruitment number for each group based on the total recruitment number. For example, the setting module 238 may divide the total recruitment number by the number of groups and set the number based on the quotient as the recruitment number.

[0133] In step S123, the setting module 238 of the server 20 sets the received items to each condition information of the recruitment conditions.

[0134] Note that the selection process in step S107 is not necessarily required. On the setting screen of the information processing apparatus 10A, the total number of job openings is set as an essential setting item, and the public release date, hourly wage, and number of job openings for each group are set as optional setting items. If all items are set by the business operator, the above-mentioned pattern 2 is used; if any item is not set, the above-mentioned pattern 1 or 3 may be executed. Also, the order of the processes in steps S111, S115, and S119 does not matter.

[0135] FIG. 12 is a flowchart showing an operation example in the case of setting example 1 according to the embodiment shown in FIG. 8. In the example shown in FIG. 12, the group with a priority of 1 (highest priority) is set as the "current group", and the group with a priority of 2 is set as the "next group". After the job information for the current group is publicly released, each process shown in FIG. 12 starts. Note that a pointer indicating the next group is prepared, and the initial value of this pointer is set to "2". The "current group" and "next group" will be described later.

[0136] In step S201 shown in FIG. 12, the service control module 236 of the server 20 determines whether the deadline for the job information has arrived. The deadline may be set by the business operator in FIG. 15 described later, or may be set based on the date and time based on the job posting date (for example, the same time on a predetermined day before the start time of work on the job posting date). If the deadline has arrived (step S201 - YES), the process ends; if the deadline has not arrived (step S201 - NO), after a predetermined period has elapsed, the process proceeds to step S203.

[0137] In step S203, the service control module 236 of the server 20 determines whether the number of job openings for the current group, which indicates the group for which the job information is currently being publicly released, has been filled. If the number of job openings has been filled (step S203 - YES), the process proceeds to step S215; if the number of job openings has not been filled (step S203 - NO), the process proceeds to step S205. The "current group" indicates the group for which the job information has been publicly released based on the priority. Each time job information is publicly released based on the priority, the newly publicly released group of job information is included in the "current group".

[0138] In step S205, the service control module 236 of the server 20 determines whether it is before a predetermined date of the publication date of the next group indicating the group in which the recruitment information will be published next or before a predetermined date of the general publication date. If the processing date corresponds to a date before these predetermined dates (step S205 - YES), the process proceeds to step S207. If the current day does not correspond to a date before these predetermined dates (step S205 - NO), the process proceeds to step S213. The "next group" is the group in which the recruitment information will be published next, based on the priority. Each time new recruitment information is published (S219), the value of the pointer indicating the next group is incremented (+1). When the value of the pointer is incremented, the group with the priority corresponding to the incremented pointer value becomes the "next group". Note that the object judged in step S205 may be whether it corresponds to a period before the predetermined date of the publication date or the general publication date, rather than before the predetermined date of the publication date or the general publication date.

[0139] In step S207, the proposal module 240 of the server 20 proposes changes to each condition information of the recruitment conditions of the current group (Pattern 2). At this time, the proposal module 240 of the server 20 outputs inquiry information including the change content and asking whether to approve it to the information processing device 10A. Here, when the current group includes a plurality of groups, the proposal module 240 proposes a change to the condition information for the recruitment conditions of the group where the number of recruits has not been gathered.

[0140] In step S209, the proposal module 240 of the server 20 determines whether the inquiry result output from the information processing device 10A of the business operator indicates approval or rejection of the proposal. If the proposal is approved (step S209 - YES), the process proceeds to step S211. If the proposal is rejected (step S209 - NO), the process proceeds to step S213.

[0141] In step S211, the proposal module 240 of the server 20 changes the condition information proposed for the recruitment conditions of the current group to the proposed content. Note that the operator may not approve the proposal as it is, but may re-modify the recruitment conditions.

[0142] In step S213, the service control module 236 of the server 20 determines whether the date is the same day as the release date of the next group or the same day as the general release date. If the processing date corresponds to these same days (step S213 - YES), the process proceeds to step S215. If the processing date does not correspond to these same days (step S213 - NO), the process returns to step S201. Note that the object judged in step S213 may not be whether it corresponds to the same day as the release date or the same day as the general release date, but whether it corresponds to a predetermined period before the release date or the general release date.

[0143] In step S215, the service control module 236 of the server 20 determines whether the total number of recruits for all job openings has been gathered. If the total number of recruits has been gathered (step S215 - YES), the process ends. If the total number of recruits has not been gathered (step S215 - NO), the process proceeds to step S217. Note that step S215, which is one of the end conditions of the process shown in FIG. 12, does not necessarily have to be at this timing. At the timing when a worker is hired, it may be determined whether the count value of the total number of hires has reached the total number of recruits for all job openings (whether the total number of recruits for all job openings has been gathered).

[0144] In step S217, the service control module 236 of the server 20 determines whether there is a next group. For example, the service control module 236 determines whether there is a group with a priority corresponding to the value of the pointer indicating the next group. If there is a next group (step S217 - YES), the process proceeds to step S219. If there is no next group (step S217 - NO), the process proceeds to step S221.

[0145] In step S219, the disclosure module 239 of the server 20 discloses the job information to each worker in the next group. After the disclosure, the service control module 236 increments the value of the pointer indicating the next group.

[0146] In step S221, the disclosure module 239 of the server 20 determines whether general disclosure is set. If general disclosure is set (step S221 - YES), the process proceeds to step S223. If there is no general disclosure (step S221 - NO), the process returns to step S201.

[0147] In step S223, the disclosure module 239 of the server 20 generally discloses the job information. "Generally disclose" includes making it viewable without restriction to the workers logged in to the job information providing platform.

[0148] FIG. 13 is a flowchart showing an operation example in the case of setting example 2 according to the embodiment shown in FIG. 9. In the example shown in FIG. 13, the group with a priority of 1 (highest priority) is set as the "current group", and the group with a priority of 2 is set as the "next group". After the job information for the current group is disclosed, each process shown in FIG. 13 starts. A pointer indicating the next group is prepared, and the initial value of this pointer is set to "2".

[0149] In step S301 shown in FIG. 13, the service control module 236 of the server 20 determines whether the deadline of the job information has arrived. The deadline may be set by the business operator in FIG. 15 described later, or may be set based on the date and time based on the job posting date (for example, the same time on a predetermined day before the start time of work on the job posting date). If the deadline has arrived (step S301 - YES), the process ends. If the deadline has not arrived (step S301 - NO), after a predetermined period has elapsed, the process proceeds to step S303.

[0150] In step S303, the service control module 236 of the server 20 determines whether the number of recruits for the current group has been collected. If the number of recruits has been collected (step S303 - YES), the process proceeds to step S307. If the number of recruits has not been collected (step S303 - NO), the process proceeds to step S305.

[0151] In step S305, as described above, the proposal module 240 of the server 20 determines, using machine learning, whether the number of recruits for the current group is likely to be collected before the deadline. If it is determined that the number of recruits will be collected (step S305 - YES), the process returns to step S301. If it is determined that the number of recruits will not be collected (step S305 - NO), the process proceeds to step S309.

[0152] In step S307, the service control module 236 of the server 20 determines whether the total number of recruits for all job openings has been collected. If the total number of recruits has been collected (step S307 - YES), the process ends. If the total number of recruits has not been collected (step S307 - NO), the process proceeds to step S309. Note that step S307 shown in FIG. 13 does not necessarily have to be at this timing, similar to step S215 shown in FIG. 12. At the timing when a worker is hired, it may be determined whether the count value of the total number of hires has reached the total number of recruits for all job openings (whether the total number of recruits for all job openings has been collected).

[0153] In step S309, the service control module 236 of the server 20 determines whether there is a next group. For example, the service control module 236 determines whether there is a group with a priority corresponding to the value of the pointer indicating the next group. If there is a next group (step S309 - YES), the process proceeds to step S311. If there is no next group (step S309 - NO), the process proceeds to step S313.

[0154] In step S311, the publishing module 239 of the server 20 publishes the job information to each worker in the next group. After the publication, the service control module 236 increments the value of the pointer indicating the next group.

[0155] In step S313, the publishing module 239 of the server 20 determines whether general publication is set. If general publication is set (step S313 - YES), the process proceeds to step S315. If there is no general publication (step S313 - NO), the process returns to step S301.

[0156] In step S315, the publishing module 239 of the server 20 generally publishes the job information.

[0157] The above - described process shown in Setting Example 2 is the process when the publication date among each condition information regarding the recruitment conditions is not set by the business operator. In this case, the information regarding the publication date may be set by machine learning as shown in the process of FIG. 13.

[0158] FIG. 14 is a flowchart showing an operation example in the case of Setting Example 3 according to the embodiment shown in FIG. 10. In the example shown in FIG. 14, the group with a priority of 1 (re - priority) is set as the "current group", and the group with a priority of 2 is set as the "next group". After the job information for the current group is published, each process shown in FIG. 14 starts. A pointer indicating the next group is prepared, and the initial value of this pointer is set to "2".

[0159] In step S401 shown in FIG. 14, the service control module 236 of the server 20 determines whether the deadline of the job information has arrived. The deadline may be set by the business operator in FIG. 15 described later, or may be set based on the date and time based on the job posting date (for example, the same time on a predetermined day before the start time of work on the job posting date). If the deadline has arrived (step S401 - YES), the process ends. If the deadline has not arrived (step S401 - NO), after a predetermined period has elapsed, the process proceeds to step S403.

[0160] In step S403, the service control module 236 of the server 20 determines whether the total number of recruitment for all job openings has been collected. If the total number of recruitment has been collected (step S403 - YES), the process ends. If the total number of recruitment has not been collected (step S403 - NO), the process proceeds to step S405. Note that step S403 shown in FIG. 14, similar to step S215 shown in FIG. 12, does not necessarily have to be at this timing. At the timing when a worker is hired, it may be determined whether the count value of the total number of hires has reached the total number of recruitment for all job openings (whether the total number of recruitment for all job openings has been collected).

[0161] In step S405, as described above, the proposal module 240 of the server 20 determines, using machine learning, whether it is likely that the total number of recruitment for all job openings will be collected under the recruitment conditions of the current group. If it is determined that the number of recruits will be collected (step S405 - YES), the process returns to step S401. If it is determined that the number of recruits will not be collected (step S405 - NO), the process proceeds to step S407.

[0162] In step S407, the proposal module 240 of the server 20 determines, using machine learning, whether it is better to change each condition information of the recruitment conditions of the current group or to conduct publicity to the next group. If changing the recruitment conditions is more likely to collect the total number of recruitment for all job openings (step S407 - YES), the process proceeds to step S409. If publicity to the next group is more likely to collect the total number of recruitment for all job openings (step S407 - NO), the process proceeds to step S411. Note that for the determination in step S407, the business operator may be asked to select which option is desired. Examples of changing each condition information by machine learning include increasing the hourly wage and reducing the working hours as described above.

[0163] In step S409, the proposal module 240 of the server 20 updates the condition information of the recruitment conditions of the current group to the proposed content.

[0164] In step S411, the service control module 236 of the server 20 determines whether there is a next group. For example, the service control module 236 determines whether there is a group with a priority corresponding to the value of the pointer indicating the next group. If there is a next group (step S411 - YES), the process proceeds to step S413. If there is no next group (step S411 - NO), the process proceeds to step S415.

[0165] In step S413, the publishing module 239 of the server 20 publishes the job information to each worker in the next group. After the publication, the service control module 236 increments the value of the pointer indicating the next group.

[0166] In step S415, the publishing module 239 of the server 20 determines whether general publication is set. If general publication is set (step S415 - YES), the process proceeds to step S417. If there is no general publication (step S415 - NO), the process returns to step S401.

[0167] In step S417, the publishing module 239 of the server 20 publishes the job information generally.

[0168] As described above, the process shown in setting example 3 is the process when the number of recruits and the budget for all job offers are set by the business operator and no other condition information is set. In this case, the other condition information may be set by machine learning as shown in the process of FIG. 14.

[0169] <Screen example> Next, each screen example displayed on the information processing device 10 on the user side will be described. FIG. 15 is a diagram showing an example of a job recruitment screen according to the embodiment. The screen shown in FIG. 15 is an example showing the content of a job offer that is limitedly published to workers belonging to three groups of "convenience store experience", "customer service", and "product delivery" by AAA Shibuya store.

[0170] In the job recruitment screen shown in FIG. 15, for example, the job posting date, working hours, deadline setting, total number of recruits for the entire job, basic hourly wage, public setting, etc. are set by the business operator. Note that in the job recruitment screen, a budget for the job may be set. The "basic hourly wage" may be set by the system based on the hourly wage in the same region or the same job type, etc. In the example shown in FIG. 15, the "deadline" indicates the end date and time of the public release of the job information, and the business operator can select it as appropriate. The total number of recruits for the entire job may be entered as shown in FIG. 15, or the number may be selected using a pull-down menu or the like. Here, assume that the business operator selects "Group Limited Public" G10, for example, selects the groups of "convenience store experience", "customer service", and "product delivery", and presses the "Next" button B10. In this case, the screen transitions from the screen shown in FIG. 15 to the screen shown in FIG. 16.

[0171] FIG. 16 is a diagram showing an example of a condition setting screen for each group according to the embodiment. According to the example shown in FIG. 16, an example of a screen for selecting groups in order of priority and setting each condition information is shown. Note that in the example shown in FIG. 16, it is an example of selecting groups for each priority, but it is also possible to set priorities for each group.

[0172] In the screen shown in FIG. 16, for each group, the hourly wage, public release date, and number of recruits can be arbitrarily set. If at least one item is not set, the setting module 238 or the proposal module 240 may set the hourly wage, public release date, or number of recruits for each group. If the business operator presses the "OK" button B20, the condition information set, selected, or input on the screen shown in FIG. 16 is set, and if the "Back" button B22 is pressed, the screen returns to the screen shown in FIG. 15. Note that in the case of only group limited public, if the total number of recruits for each group does not match the total number of recruits for the entire job, an error message may be displayed. Also, in the case of general public release of job information, it is sufficient that the total number of recruits for each group is less than or equal to the total number of recruits for the entire job. When the total number of recruits for each group is less than the total number of recruits for the entire job, the shortage number can be used as the number of recruits for general public release.

[0173] Note that the disclosed technology is not limited to the above-described embodiments, and can be implemented in various other forms without departing from the gist of the disclosed technology. Therefore, the above embodiments are merely illustrative in every respect and should not be construed in a limiting sense. For example, each of the above-described processing steps can be arbitrarily changed in order or executed in parallel as long as there is no contradiction in the processing content.

[0174] 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, by way of example and not limitation, software programs and computer programs.

Explanation of Reference Numerals

[0175] 1 Information processing system 10, 10A, 10B Information processing device 20 Information processing device (server) 110, 210 Processing device (CPU) 120, 220 Network communication interface 130, 230 Memory 131, 231 Operating system 132, 232 Network communication module 133 Application data 134 Service processing module 135 Acquisition module 136 Output module 137 Processing module 138 Display control module 150 User interface 170, 270 Communication bus 233 User data 234 Group data 235 Recruitment data 236 Service control module 237 Reception module 238 Setting module 239 Publication Module 240 Proposal Module

Claims

1. An information processing apparatus, receives a selection of a plurality of groups out of each group to which one or more users belong, from another information processing apparatus used by a business operator; sets a priority for each of the plurality of groups; publishes job information for each group based on the priority of each group; An information processing method for performing the above.

2. The receiving includes receiving, from the other information processing apparatus, setting of disclosure information regarding the disclosure timing of the job information for each group, The publishing includes publishing the job information to the next group to be published when the disclosure timing based on the disclosure information of the next group to be published arrives. The information processing method according to claim 1.

3. The publishing includes publishing the job information to the next group to be published before the disclosure timing of the next group to be published when the number of users equal to the number of recruits set for the group in which the job information is being published has gathered. The information processing method according to claim 2.

4. The information processing apparatus further proposes a change to the recruitment conditions set for the group in which the job information is being published when the number of users equal to the number of recruits for the group in which the job information is being published does not gather a predetermined number of days before the disclosure timing of the next group to be published. The information processing method according to claim 3.

5. The receiving includes receiving, from the other information processing apparatus, an approval operation of the business operator regarding the change of the recruitment conditions, The proposing includes changing the recruitment conditions of the current group according to the approval operation. The information processing method according to claim 4.

6. When disclosure information regarding the disclosure timing of the job information is not set for at least one group among the plurality of groups, obtaining disclosure information from a learning model that has learned the relationship between the condition information included in the recruitment conditions set for each group and the disclosure information; publishing the job information to the next group to be published based on the obtained disclosure information. The information processing method according to claim 1.

7. The receiving includes receiving, from the other information processing apparatus, setting of the number of recruits and budget for a job opening, The information processing apparatus Input the information on at least the recruitment number and the budget of the job opening into a learning model that has learned the relationship between each piece of information on the recruitment number and the budget of the job opening and each piece of conditional information including the recruitment number, public information, and salary of each group, and obtain each piece of conditional information including the recruitment number, the public information, and the hourly wage in each group. The information processing method according to claim 1, further comprising setting each piece of conditional information including the obtained recruitment number, the public information, and the hourly wage in a corresponding group.

8. Before the arrival of the publication time based on the public information of the group to be published next, determine whether to change the recruitment conditions of the group in which the job opening information is being published or to publish the job opening information in the group to be published next based on the update information of each piece of conditional information input into the learning model. The information processing method according to claim 6, further comprising performing this determination.

9. The setting specifies characteristic information based on the attribute information set for each group. The information processing method according to claim 1, further comprising determining the priority of each group using the specified characteristic information.

10. In an information processing device, receive a selection of a plurality of groups from among the groups to which one or more users belong from another information processing device used by the business operator. set a priority for each group within the plurality of groups. publish job opening information for each group based on the priority of each group. A program for causing the above to be executed.

11. An information processing device including a processor, wherein the processor receives a selection of a plurality of groups from among the groups to which one or more users belong from another information processing device used by the business operator. sets a priority for each group within the plurality of groups. publishes job opening information for each group based on the priority of each group. An information processing device that performs the above.

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