Information processing systems, information processing methods, and programs

Abstract

We provide information processing systems and other tools that can effectively support the recruitment activities of employers. [Solution] According to one aspect of the present invention, an information processing system is provided, comprising at least one processor, the processor configured to perform the following steps by reading a program: in the acquisition step, job-related information including information about job postings from employers is acquired; in the target creation step, a plurality of target pieces of information are created based on the job-related information and first reference information, each representing a different person profile sought by the employer in the job posting, the first reference information being information relating to the correlation between the job-related information and the target information; in the search condition creation step, for each of the plurality of target pieces of information, search conditions are created based on the target information and second reference information to search for job seekers who match the profile from among the job seekers registered in the job seeker database, the second reference information being information relating to the correlation between the target information and the search conditions; and in the search result display control step, the search results for candidate job seekers, who are job seekers searched using the search conditions for each of the plurality of target pieces of information, are displayed, and the search results include at least one of the number of candidate job seekers whose registered information has not been viewed by the employer and the number of candidate job seekers to whom the employer has not sent a scouting document.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a technique for searching job seekers.

Prior Art Document

Patent Document

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a need for a technique that can effectively support the recruitment activities of employers.

[0005] In view of the above circumstances, the present invention aims to provide an information processing system and the like that can effectively support the recruitment activities of employers.

Means for Solving the Problems

[0006] According to one aspect of the present invention, an information processing system is provided, comprising at least one processor, the processor configured to perform the following steps by reading a program: an acquisition step acquires job-related information including information about job postings from employers; a target creation step creates a plurality of target pieces of information, each representing a different person profile sought by an employer in a job posting, based on the job-related information and first reference information, the first reference information being information relating to the correlation between the job-related information and the target information; a search condition creation step creates search conditions for each of the plurality of target pieces of information, based on the target information and second reference information, to search for job seekers who match the profile from among job seekers registered in a job seeker database, the second reference information being information relating to the correlation between the target information and the search conditions; and a search result display control step displays search results for candidate job seekers, each of the search conditions for each of the plurality of target pieces of information, the search results including at least one of the number of candidate job seekers whose registered information has not been viewed by the employer and the number of candidate job seekers to whom the employer has not sent a scouting document.

[0007] This approach can effectively support the recruitment activities of employers. [Brief explanation of the drawing]

[0008] [Figure 1] This is a diagram showing the configuration of Information Processing System 1. [Figure 2] This is a block diagram showing the hardware configuration of server device 10. [Figure 3] This block diagram shows the hardware configuration of the job seeker terminal 20 and the job applicant terminal 30. [Figure 4] This is a block diagram showing the functions realized by the server device 10 (control unit 11), the job seeker terminal 20 (control unit 21), and the job seeker terminal 30 (control unit 31). [Figure 5] This figure shows an example of the search criteria display screen SD that appears on the job seeker terminal 20. [Figure 6]This figure shows an example of the search results display screen RD shown on the job seeker terminal 20. [Figure 7] This is an activity diagram showing an example of the flow of information processing (job seeker search processing) performed by Information Processing System 1. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. The various features shown in the embodiments below can be combined with each other.

[0010] Incidentally, the program or program product for implementing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or it may be provided so that the program or program product is launched on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0011] Furthermore, in various information processing according to one embodiment, an input and an output corresponding to the input can be realized. Here, as long as an output is obtained as a result of the input, the form of the information referenced in such information processing (hereinafter referred to as "reference information") is not limited. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a decision formula such as a regression equation constructed by a statistical method), or a trained model that has been pre-trained to learn the correlation between input and output, or a generative AI such as a large-scale language model that can output a desired result by inputting a prompt (these models include parameters that construct the correlation relationship between input and output) or a visual language model.

[0012] Furthermore, in one embodiment, "part" may include, for example, hardware resources implemented by a circuit in a broad sense, and the information processing of software that can be specifically realized by these hardware resources. Also, in one embodiment, various types of information are handled, and this information can be represented, for example, by the physical values ​​of signal values ​​representing voltage and current, the high or low values ​​of signal values ​​as a set of binary bits composed of 0s or 1s, or by quantum superposition (so-called qubits), and communication and calculations can be performed on a circuit in a broad sense.

[0013] Furthermore, a circuit in a broad sense is a circuit realized by combining at least a suitable combination of circuits, circuits, processors, and memory. The processor may be a general-purpose processor or a dedicated circuit. In other words, it includes application-specific integrated circuits (ASICs), programmable logic devices (for example, simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)), etc.

[0014] 1. Hardware Configuration This section describes the hardware configuration.

[0015] <Information Processing System 1> FIG. 1 is a configuration diagram showing an information processing system 1. The information processing system 1 includes a communication line 2, a server device 10, a plurality of employer terminals 20, and a plurality of applicant terminals 30. The server device 10, the employer terminals 20, and the applicant terminals 30 are configured to be communicable with each other through the communication line 2. The connections of the server device 10, the employer terminals 20, and the applicant terminals 30 may be wired or wireless. Also, the server device 10, the employer terminals 20, and the applicant terminals 30 are each an example of an "information processing device".

[0016] The information processing system 1 constitutes at least a part of a recruitment and job application system used by, for example, a plurality of employers (the first employer U1 and the second employer U2) and a plurality of job applicants (the first applicant U3 and the second applicant U4). The information processing system 1 mainly performs searches for job applicants by employers, searches for job openings by job applicants, mediation of communication between employers and job applicants, and the like. For example, the information processing system 1 provides and manages a talent matching platform, a talent matching service, etc. used by employers and job applicants. In one embodiment, the information processing system 1 consists of one or more devices or components. Hereinafter, these components will be described.

[0017] <Server device 10> FIG. 2 is a block diagram showing the hardware configuration of the server device 10. As shown in FIG. 2, the server device 10 includes a control unit 11, a storage unit 12, a communication unit 13, and a communication bus 14. The control unit 11, the storage unit 12, and the communication unit 13 are electrically connected inside the server device 10 via the communication bus 14.

[0018] <Control unit 11> The control unit 11 performs processing and control of the overall operation related to the server device 10. The control unit 11 is, for example, a Central Processing Unit (CPU), which is an example of a processor. The control unit 11 realizes various functions related to the server device 10 by reading a predetermined program stored in the storage unit 12. That is, the information processing by software stored in the storage unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be executed as each functional unit included in the control unit 11. These will be described in more detail in the next section. Note that the control unit 11 is not limited to being single, and the server device 10 may have a plurality of control units 11 for each function. Also, the server device 10 may be configured by a combination of these.

[0019] <Storage unit 12> The storage unit 12 stores various information defined by the foregoing description. This can be implemented, for example, as a storage device such as a Solid State Drive (SSD) that stores various programs and the like related to the server device 10 executed by the control unit 11, or as a memory such as a Random Access Memory (RAM) that stores temporarily necessary information (arguments, arrays, etc.) related to the calculation of the program. The storage unit 12 stores various programs, variables, etc. related to the server device 10 executed by the control unit 11.

[0020] <Communication unit 13> The communication unit 13 preferably uses wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), and wired LAN network communication, but may include wireless LAN network communication, mobile communication such as LTE / 5G, and BLUETOOTH (registered trademark) communication as necessary. That is, the communication unit 13 may be implemented as a collection of these plural communication means. Also, the server device 10 may communicate various information with the outside via the communication unit 13 and the network.

[0021] The server device 10 may be on-premises or in a cloud environment. A cloud-based server device 10 may provide the above-mentioned functions and processing in the form of, for example, SaaS (Software as a Service) or cloud computing.

[0022] <Job seeker terminal 20> Figure 3 is a block diagram showing the hardware configuration of the employer terminal 20 and the job seeker terminal 30. The employer terminal 20 is an information processing terminal used by employers and can access the server device 10.

[0023] "Employers" include organizations such as for-profit corporations (e.g., companies), non-profit organizations (e.g., cooperatives, foundations), and public corporations (e.g., local governments), or their representatives. Representatives within employers may also be called hiring managers, and may include personnel from the organization's human resources department or the department responsible for hiring. Furthermore, employers may also include headhunters. A headhunter is an organization or its representative that acts as an intermediary between job seekers and employers (organizations) on behalf of the organization (employer). Headhunters are also known as recruitment agencies, hiring agents, or recruitment agencies.

[0024] Furthermore, "organization" includes for-profit corporations (e.g., companies), non-profit corporations (e.g., cooperatives, foundations, etc.), and public corporations (e.g., local governments, etc.). In addition, "organization" is not limited to a single legal entity, but may also include a group composed of multiple legal entities with capital relationships or partnerships (e.g., a group consisting of a parent company, subsidiaries, affiliated companies, etc.).

[0025] As shown in Figure 3A, the job seeker terminal 20 comprises a control unit 21, a storage unit 22, a communication unit 23, an input unit 24, an output unit 25, and a communication bus 26. The control unit 21, storage unit 22, communication unit 23, input unit 24, and output unit 25 are electrically connected within the job seeker terminal 20 via the communication bus 26. The descriptions of the control unit 21, storage unit 22, and communication unit 23 are the same as the descriptions of each part in the server device 10 and are therefore omitted.

[0026] <Input section 24> The input unit 24 receives operation inputs made by the user. The operation inputs are transmitted as command signals to the control unit 21 via the communication bus 26. The control unit 21 can perform predetermined controls or calculations based on the transmitted command signals as needed. The input unit 24 may be included in the housing of the job seeker terminal 20 or it may be an external component. For example, the input unit 24 may be implemented as a touch panel integrated with the output unit 25. When the input unit 24 is implemented as a touch panel, the user can input tap operations, swipe operations, etc. to the input unit 24. Instead of a touch panel, the input unit 24 can be a switch button, mouse, trackpad, QWERTY keyboard, etc.

[0027] <Output section 25> The output unit 25 displays a graphical user interface (GUI) screen that can be operated by the user. The output unit 25 may be included in the housing of the job seeker terminal 20 or it may be an external device. Specifically, the output unit 25 can be implemented as a display device such as a CRT display, liquid crystal display, organic EL display, or plasma display. It is preferable that these display devices be used according to the type of job seeker terminal 20.

[0028] <Job seeker terminal 30> The job seeker terminal 30 is an information processing terminal used by job seekers and is capable of accessing the server device 10. "Job seekers" include various types of people seeking employment, such as those who are looking to change jobs or find employment (e.g., currently employed people (those seeking a job change), prospective graduates (job seekers), students, etc.), and those who are interested in changing jobs or finding employment.

[0029] As shown in Figure 3B, the job seeker terminal 30 comprises a control unit 31, a storage unit 32, a communication unit 33, an input unit 34, an output unit 35, and a communication bus 36. The control unit 31, storage unit 32, communication unit 33, input unit 34, and output unit 35 are electrically connected within the job seeker terminal 30 via the communication bus 36. The descriptions of the control unit 31, storage unit 32, communication unit 33, input unit 34, and output unit 35 are the same as the descriptions of each part in the employer terminal 20 and are therefore omitted.

[0030] 2. Functional Configuration This section describes the functional configuration of this embodiment. Information processing by software stored in the memory unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be executed as each functional unit included in the control unit 11 (at least one processor provided by the information processing system 1).

[0031] Figure 4 is a block diagram showing the functions realized by the server device 10 (control unit 11), the job seeker terminal 20 (control unit 21), and the job seeker terminal 30 (control unit 31).

[0032] As shown in Figure 4A, the server device 10 (control unit 11) comprises a basic display control unit 111, an acquisition unit 112, a target creation unit 113, a query reception unit 114, a search condition creation unit 115, a search result display control unit 116, and an artificial intelligence unit 120.

[0033] As shown in Figure 4B, the job seeker terminal 20 (control unit 21) includes a display unit 211 and an operation acquisition unit 212. As shown in Figure 4C, the job seeker terminal 30 (control unit 31) includes a display unit 311 and an operation acquisition unit 312.

[0034] <Basic display control unit 111> The basic display control unit 111 is configured to display various information on the employer terminal 20 or the job seeker terminal 30. For example, in response to requests from each user (employers U1, U2 or job seekers U3, U4), the basic display control unit 111 displays the registration information of job seekers registered in the database on the display unit 211 of the employer terminal 20 or the display unit 311 of the job seeker terminal 30.

[0035] <Acquisition part 112> The acquisition unit 112 is configured to acquire job-related information, including information about job postings (jobs advertised by job postings). "Job-related information" includes, for example, job requirements, job description text, candidate search criteria, etc.

[0036] "Job requirements" define the conditions and qualities that job seekers are expected to have for a given position. Job requirements may include, for example, necessary skills, experience, qualifications, desired personality, character, values, and attitude. They may also include mandatory requirements (conditions that are always required) and desirable requirements (conditions that are not mandatory but are desirable).

[0037] A "job description document" is a document that explains at least one of the following: the organization, industry, department, job title, duties, position, annual salary, and work arrangements of the applicant. For example, a job description document may include descriptions of the organization's history, business environment, characteristics, specific job titles or duties, and working conditions.

[0038] "Candidate search criteria" are search conditions used to find job seekers who are candidates for a job opening in the database. Candidate search criteria include search keywords and search categories (job seeker attributes) based on the registered information of job seekers.

[0039] The registration information of job seekers may include, for example, a resume, which is a document detailing the job seeker's work history (work history document) that conveys their past work experience, skills, qualifications, etc. to employers. The work history document may include the job seeker's resume, other profile information, and conditions such as the industry or job type the job seeker desires. A "resume" is a document that mainly describes the job seeker's profile, current situation, educational background, work history, and desired working conditions. The work history document may be automatically generated by artificial intelligence such as generation AI, or it may be created by the job seeker themselves. In addition, the registration information of job seekers may include portfolio information that proves the job seeker's skills and achievements, account information for various SNS (Social Networking Services), and reference check information that shows evaluations of the job seeker by third parties, etc.

[0040] Job-related information should at least include the job requirements. This improves the accuracy of target information creation by the target creation unit 113, which will be described later. Job-related information is typically a job posting, but it does not necessarily have to be formatted like a job posting; it may be an unstructured document such as a memo with the job requirements listed as items.

[0041] The acquisition unit 112 may, for example, accept the upload of job-related information from the recruiter terminal 20 and acquire the uploaded job-related information. Alternatively, the acquisition unit 112 may accept input from the recruiter terminal 20 such as information indicating the target job (e.g., the title and ID of the target job), the storage location of the job-related information (network address, URL, path, etc.), and acquire the corresponding job-related information from a database or the like. For example, the acquisition unit 112 may accept input of a job ID that uniquely identifies the job posting and acquire the corresponding job posting as job-related information from the job posting database. Furthermore, the acquisition unit 112 may accept input of job-related information from the recruiter terminal 20 (e.g., keywords or sentences describing the job, search keywords, etc.).

[0042] <Target Creation Section 113> The target creation unit 113 is configured to create multiple target information sets, each representing a different profile of a person sought by the employer in the job for which the job-related information has been acquired, based on the job-related information acquired by the acquisition unit 112 and the first reference information.

[0043] "Target information" includes, for example, the requirements for job seekers (candidates for employment) (skills, experience, qualifications, age group, work history, values, career aspirations, etc.). Target information may also include, for example, a label name (a phrase that represents the person's profile) and a description of the person's profile.

[0044] The target information label name is a combination of keywords such as job title, duties, products handled, related organizations, and career. Specific examples of label names include "LLM App Development Lead," "Platform Engineering Advocate," and "Full-Stack Proactive DX Engineer." The profile description is a text that explains the abilities, experience, and role of the person represented by the label name.

[0045] The number of target information entries created by the target creation unit 113 is determined based on the content of the job-related information, and is, for example, a maximum of 3. The number of target information entries may also be determined, for example, according to the range of personnel targeted by the job (broadness or narrowness of job requirements) represented by the job-related information. For example, the more lenient the job requirements (the fewer the number of mandatory requirements) and the wider the range of personnel targeted, the more target information entries the target creation unit 113 may create.

[0046] The first reference information is information relating to the correlation between job-related information and target information. The first reference information is stored, for example, in the memory unit 12. The first reference information may include, for example, tables, functions, simple algorithms, etc., that show the correlation between job-related information and target information. The correlations included in the first reference information can be constructed, for example, by statistically analyzing data that records job-related information and corresponding target information.

[0047] The first reference information may include a set of parameters for generating target information from job-related information. For example, the first reference information may be various pre-trained models. For example, the first reference information may include a target information creation model which is a dedicated learning model or a general-purpose learning model that has been machine-trained to take job-related information as input and output target information. In this case, the target creation unit 113 inputs the job-related information into the target information creation model and causes the target information creation model to output target information.

[0048] The target information creation model is included in the artificial intelligence unit 120. The target information creation model, which is a dedicated learning model, may be constructed, for example, by learning using job-related information data and corresponding target information data as training data. In such a target information creation model, parameters calculated and tuned through learning construct a correlation between job-related information and target information. The dedicated learning model may also include a generative AI capable of generating answers not included in the training data. The generative AI of the dedicated learning model is a limited-use generative AI that does not require input of instructions such as the content of the output information to be generated or the content of the task to be executed.

[0049] If the target information creation model is a general-purpose learning model (for example, a language model such as a large-scale language model), the target creation unit 113 inputs a prompt to the target information creation model that includes job-related information and an instruction to output target information corresponding to the job-related information as input, causing the target information creation model to output the target information. The target creation unit 113 may also generate a prompt that gives the target information creation model an instruction to create target information and input this prompt to the target information creation model. In addition to the job-related information and the instruction to create and output target information, the target creation unit 113 may also input a prompt to the target information creation model that includes, for example, one or more samples of job-related information and one or more samples of corresponding target information as examples, samples, or training data of input and output pairs. Here, the parameters that construct the target information creation model and the prompt that includes an instruction to output target information corresponding to the job-related information construct the correlation between the job-related information and the target information. The general-purpose learning model may include a generative AI capable of generating arbitrary output information based on the input information. Generative AI for general-purpose learning models is a general-purpose generative AI that requires input such as instructions on the content of the output information to be generated and the content of the task to be performed.

[0050] <Query Reception Unit 114> The query reception unit 114 is configured to receive input from job seekers (job seeker terminal 20) for required queries in the search conditions created by the search condition creation unit 115, which will be described later.

[0051] The required query received by the query reception unit 114 is used as part of the search criteria. The required query may be a keyword, a numerical range, a search field, or an activity status.

[0052] A "search field" is an item used to specify the search scope (search category). Examples of search fields include "address," "industry," "position," "department," "job description," "educational background," "language skills," "skills," "qualifications," "awards," and "company name." For example, in a search targeting "address" as the search field (search scope), only information categorized as "address" (i.e., information assigned an attribute corresponding to the "address" search field) from the job seeker's registration information will be included in the search, and other information will not be included.

[0053] "Activity status" includes, for example, the last login date and time to the services provided by Information Processing System 1, the number or frequency of actions taken regarding job postings (e.g., viewing, adding to bookmark list, applying, receiving scout documents, replying to scout documents), and the last update date and time of registered information. The "bookmark list" (also called the "favorites list," "interesting list," etc.) is a list prepared for each job seeker where they can register any job posting they wish. A "scout document" is a document sent from an employer to a job seeker with the aim of encouraging them to apply for a job or proposing an interview, and may also be called a scout email.

[0054] Note that it is not necessary to enter required queries, and the acceptance of required query input may be skipped.

[0055] <Search Criteria Creation Section 115> The search condition creation unit 115 is configured to create search conditions for each of the multiple target information created by the target creation unit 113, based on the target information and the second reference information, to search for job seekers registered in the job seeker database who match the profile represented by the target information.

[0056] The second reference information is information regarding the correlation between target information and search conditions. The second reference information is stored, for example, in the memory unit 12. The second reference information may include, for example, tables, functions, simple algorithms, etc., that show the correlation between target information and search conditions. The correlations included in the second reference information can be constructed, for example, by statistically analyzing data that records target information and corresponding search conditions.

[0057] The second reference information may include a set of parameters for generating search conditions from target information. For example, the second reference information may be various pre-trained models. For example, the second reference information may include a search condition creation model which is a dedicated or general-purpose learning model that has been machine-trained to take target information as input and output search conditions. In this case, the search condition creation unit 115 inputs the target information into the search condition creation model and causes the search condition creation model to output search conditions.

[0058] The search condition creation model is included in the artificial intelligence unit 120. The search condition creation model, which is a dedicated learning model, may be constructed, for example, by learning using target information data and corresponding search condition data as training data. In such a search condition creation model, parameters calculated and tuned through learning construct a correlation between the target information and the search conditions.

[0059] If the search condition creation model is a general-purpose learning model (for example, a language model such as a large-scale language model), the search condition creation unit 115 inputs a prompt to the search condition creation model that includes target information and an instruction to output a search condition corresponding to the target information, causing the search condition creation model to output the search condition. The search condition creation unit 115 may also generate a prompt that gives the search condition creation model an instruction to create a search condition, and input this prompt to the search condition creation model. In addition to the target information and the instruction to create and output the search condition, the search condition creation unit 115 may also input a prompt to the search condition creation model that includes, for example, one or more samples of target information and one or more samples of corresponding search conditions as examples, samples, or training data of input and output pairs. Here, the parameters that construct the search condition creation model and the prompt that includes an instruction to output a search condition corresponding to the target information construct the correlation between the target information and the search condition.

[0060] The search criteria created by the search criteria creation unit 115 are derived from the requirements expressed in the target information, translated into search criteria elements (keywords, numerical ranges, search fields, etc.). The search criteria may also include auxiliary elements that are not expressed in the target information but are preferable as search criteria (e.g., annual income, current address, etc.). These auxiliary elements may be pre-set, for example, according to the occupation, industry, etc., of the target information.

[0061] For example, for target information with the label name "LLM App Development Lead," search conditions are created that include keywords such as "LLM" and "Application Development," a numerical range such as "7.5 to 10 million yen" (most recent income), search fields such as "SE" (job title), "Internet" (industry), and "Tokyo" (current address), and activity status such as "Last login within the last month."

[0062] If the query reception unit 114 has received input of required queries, the search condition creation unit 115 may create search conditions that include the required queries based on the target information, the required queries, and the second reference information. This prevents elements that the job seeker considers essential from being omitted from the search conditions created by the search condition creation unit 115.

[0063] In this case, the second reference information is information regarding the correlation between the combination of target information and required queries and the search conditions. For example, the search condition creation unit 115 inputs the combination of target information and required queries into the search condition creation model included in the second reference information and causes the search condition creation model to output the search conditions.

[0064] When search criteria are created from target information and required queries, the required queries may be incorporated into the search criteria as they are (what the job seeker entered), or they may be incorporated after minor modifications (for example, conversion of keywords to synonyms).

[0065] The search condition creation unit 115 may create a number of search conditions corresponding to each of the multiple target information items. This allows job seekers who match the target information to be searched from multiple perspectives (search axes), thereby increasing the significance of the search results displayed by the search result display control unit 116.

[0066] The number of search conditions created by the search condition creation unit 115 for a single target information is determined based on the content of the target information, and is, for example, a maximum of 3. The number of search conditions may also be determined, for example, according to the level of abstraction of the person profile represented by the target information. For example, the fewer the keywords included in the target information, or the wider the range of attributes indicated by the keywords, and the higher the level of abstraction of the person profile, the more search conditions the search condition creation unit 115 may create.

[0067] For example, if the target information does not specify an age, the search condition creation unit 115 may create multiple search conditions targeting different age groups such as young people, middle-aged people, and senior people. The multiple search conditions created by the search condition creation unit 115 for a single piece of target information may have some elements in common (for example, the search fields may be the same, but the keywords may be different).

[0068] The search condition creation unit 115 may further create explanatory information for each search condition. The "explanatory information" may include, for example, the search condition name and the search strategy. The "search condition name" is, for example, a keyword that represents the personnel targeted by the search condition, and is a more specific representation of the target information label name. The "search strategy" indicates the purpose of the search condition and may include, for example, a detailed description of the personnel represented by the search condition name (skills, experience, etc.) and the search axis of the search condition (for example, the job type axis, skill axis, etc., which are the main search fields in the search).

[0069] The search condition creation unit 115 may, for example, create search conditions and their explanatory information based on target information and second reference information. In this case, the second reference information is information regarding the correlation between target information and combinations of search conditions and explanatory information. The search condition creation unit 115 may, for example, input target information into a search condition creation model included in the second reference information and cause the search condition creation model to output combinations of search conditions and explanatory information.

[0070] Here, the first reference information referenced in the target creation unit 113 and the second reference information referenced in the search condition creation unit 115 may be implemented integrally as a single (common) reference information. Similarly, the target information creation model and the search condition creation model may be implemented by a single (common) artificial intelligence model (trained model, generative AI, large-scale language model, etc.).

[0071] When the first reference information and the second reference information are implemented as a single reference information, for example, this reference information may be information relating to the correlation between job-related information and combinations of multiple target information and search conditions for each of those multiple target information.

[0072] Furthermore, this reference information may be various pre-trained models, and may include, for example, a dedicated learning model trained to take job-related information as input and output a combination of multiple target information and search conditions for each of those multiple target information, or a target / search condition creation model which is a general-purpose learning model. In this case, the control unit 11 inputs the job-related information into the target / search condition creation model and causes the target / search condition creation model to output a combination of multiple target information and search conditions for each of those multiple target information. The control unit 11 may take the job-related information as input to the target / search condition model and output multiple target information and multiple search conditions by simultaneously or sequentially executing a process to create multiple target information from the job-related information and a process to create search conditions for each of the created target information, using a series of inference processes (one-step text generation process, multitasking process, etc.) to output multiple target information and multiple search conditions. Specifically, the control unit 11 inputs the acquired job-related information into the target / search condition model and first causes the target / search condition model to generate multiple target information based on the job-related information. Next, the control unit 11 inputs (feeds back) each (or a combination thereof) of the generated target information to the same target-search condition model, along with additional instruction information including instructions for creating search conditions as needed, to further generate search conditions corresponding to each target information.

[0073] Figure 5 shows an example of the search criteria display screen SD displayed on the recruiter terminal 20. The search criteria display screen SD displays multiple search criteria display areas SA. Each search criteria display area SA is provided for each search criterion. In the example in Figure 5, multiple search criteria display areas SA corresponding to the target information labeled "LLM App Development Lead" are displayed. The search criteria display areas SA are grouped by target information and displayed on the recruiter terminal 20. Each search criteria display area SA includes the search criterion name SN, search strategy ST, search criterion SC, etc.

[0074] The search condition name SN represents the image of the personnel being searched for by the search condition SC. The search strategy ST is a description of the skills, experience, etc., of the personnel being searched for by the search condition SC, and the search criteria of the search condition SC.

[0075] The search criteria (SC) include keywords as a search query (AND keywords and OR keywords), search fields (job title, industry, current address), numerical ranges (most recent income), and activity status (last login).

[0076] <Search Result Display Control Unit 116> The search result display control unit 116 is configured to search for job seekers registered in the job seeker database using the search conditions created by the search condition creation unit 115, and to display the results. The search performed here may be a preliminary search (which may also be called a preliminary search, simulation search, or pre-search) performed automatically or by an arbitrary trigger before the employer confirms the search conditions and actually executes the (production) search process to output a list of candidates, etc. Furthermore, the database to be searched is not limited to the actual (production environment) job seeker database itself, but may be a database for preliminary searches that is different from the job seeker database (for example, a subset of production data, a lightweight replica database, cache data, a database indexed for searching, etc.).

[0077] Specifically, the search result display control unit 116 displays the search results for candidate job seekers, who are job seekers, on the recruiter terminal 20, using the search conditions for each of the multiple target information items.

[0078] The "search results" include at least one of the following: the number of job seekers whose registration information the employer has not viewed (hereinafter, "number of first candidates"), and the number of job seekers to whom the employer has not sent a scouting document (hereinafter, "number of second candidates"). The search results display control unit 116 may display only one of the number of first candidates or the number of second candidates, or it may display both the number of first candidates and the number of second candidates. In addition, each numerical value included in the search results may be displayed in a format other than numbers (including rounded numbers (for example, numbers that have been rounded, truncated, rounded up, etc., to the ones place, tens place, hundreds place, etc. (approximate numbers))), such as graphs and labels (grades, ranks, etc., according to the magnitude of the numerical value).

[0079] Furthermore, "job seekers who have not viewed their registration information" refers to job seekers whose registration information has never been displayed on the employer's terminal 20 at the employer's request (input of a display instruction) to display the search results (job seekers for whom no request to view their registration information has been made).

[0080] Furthermore, the conditions "the employer has not viewed the registration information" and "the employer has not sent a recruitment letter" are merely examples, and the conditions that make up the information included in the search results (number of first candidates, number of second candidates, or other numerical values) may be the employer's activity history, the job seeker's registration information, or other conditions based on the job seeker's activity history.

[0081] Specifically, the search results may include at least one of the candidate counts shown in (a) through (d) below. (a) The number of job seekers found in the search results who have not been added to any list chosen by the employer (favorites list, bookmarks list, etc.) (number of unfavorited candidates). (b) The number of job seekers found who the employer has never contacted in the past selection process (including selection processes for other job postings) (number of candidates with no prior contact). (c) The number of job seekers who have been found and have not yet responded to messages such as recruitment letters sent by employers (number of unresponded candidates). (d) The number of job seekers found who have not followed (registered to track) the employer's organization (unfollowed number).

[0082] The search results may also include the number of candidates found (hereinafter referred to as the "baseline candidate count"). This allows employers to compare the total number of candidates with the number of first-choice candidates, second-choice candidates, etc., and to understand the proportion of candidates who have not been approached.

[0083] The search results may further include an expected response rate, calculated based on the number of scouting messages received and the number of replies to those messages within the searched set of candidate job seekers. This allows employers to evaluate search criteria created using the expected response rate. The search criteria creation unit 115 displays the expected response rate, along with the number of first and / or second candidates, on the employer terminal 20, for example.

[0084] For example, the search result display control unit 116 may calculate the expected response rate by dividing the total number of responses to scouting documents from all searched candidates by the total number of scouting documents received by all searched candidates (for example, if 100 candidates are searched, the sum of the number of scouting documents received by each of the 100 candidates, including those who have not received any scouting documents).

[0085] Furthermore, the search result display control unit 116 may calculate the individual response rate (the response rate to scouting documents for each candidate) for each found candidate by dividing the number of replies to scouting documents by the number of scouting documents received, and calculate the average, median, etc. of the individual response rates for all found candidates as the expected response rate. Candidates who have not received any scouting documents (zero received documents) may be excluded from the calculation of the expected response rate, or they may be treated as candidates with an individual response rate of zero.

[0086] The search result display control unit 116 may, for example, display the expected response rate using labels such as "High+", "High", "Medium", "Low+", "Low", or "Low-" depending on the magnitude of the expected response rate. Alternatively, the search result display control unit 116 may display the expected response rate using a numerical value (including negative values), graph, label, etc., representing the difference from the average response rate of job seekers to scouting documents in the industry (sector) of the job posting for which the target information was created.

[0087] If there is target information for which multiple search conditions have been created, the search result display control unit 116 searches for candidate job seekers for each of the search conditions belonging to each of the multiple target information.

[0088] In this case, the search result display control unit 116 may also display search results for each of the multiple target information items, based on the set of candidate job seekers found using all the search criteria belonging to the target information. This allows employers to check the search results, including the number of first candidates, second candidates, etc., for each target information item, making it easier to evaluate the target information.

[0089] Here, "all search conditions belonging to the target information" means all search conditions created by the search condition creation unit 115 based on the target information. For example, if three search conditions are created from one target information, the search result display control unit 116 will display the combined search results of the three search conditions as the search results for that target information on the job seeker terminal 20.

[0090] The search result display control unit 116 may calculate and display the number of candidates described in (a) to (d) above for each target information or for each search condition. This makes it possible for recruiters to understand, for example, how many new groups (those not yet favorited) exist that they have not yet identified, on a per-target information or per-search condition basis.

[0091] Furthermore, the search result display control unit 116 may display, along with the target information, a recommendation message to the recruiter prompting them to change the profile settings or relax the search conditions for target information in the search results where the expected response rate is below a predetermined threshold (for example, "Low-").

[0092] The list of potential job seekers may be a collection of candidates who have been found through multiple search criteria belonging to a single target information. This allows the search results presented to employers to be more relevant to the actual situation.

[0093] In this context, "organizing candidate applicants" means ensuring that candidates who have been searched for more than once (i.e., those who have been found using two or more different search criteria) are not counted multiple times within a single target information entry. This organization prevents duplicate entries representing the same candidate applicant within a single target information entry, and avoids duplicate counting of candidates in search results.

[0094] If there is target information for which multiple search conditions have been created, the search result display control unit 116 may display only one of the search results per target information unit (such as the number of first candidates, second candidates, standard candidates, and expected response rate, calculated from the set of candidate job seekers searched by all search conditions) or the search results per multiple search conditions unit (such as the number of first candidates, second candidates, standard candidates, and expected response rate, calculated from the candidate job seekers searched by each individual search condition), or it may display both the search results per target information unit and the search results per search condition unit on the recruiter terminal 20.

[0095] Furthermore, the search result display control unit 116 may display a comprehensive search result (search result per job-related information unit) which integrates the search results of multiple target information created from one job-related information. The comprehensive search result may include, for example, the sum of the number of first candidates, second candidates, and standard candidates for each target information, as well as the average expected response rate.

[0096] Figure 6 shows an example of the search results display screen RD displayed on the job seeker terminal 20. The search results display screen RD includes a results list RL that displays the search results for each target information.

[0097] The Results List RL displays, for each target information, the target information label name ("Label"), the description of the person ("Description"), the number of target candidates ("Number of Candidates"), the expected response rate, the number of first candidates ("Number of Unread Messages"), the number of second candidates ("Number of Unsent Messages"), etc. In addition, the bottom column of the Results List RL displays the number of target candidates, first candidates, and second candidates for all target information combined.

[0098] The search result display control unit 116 may accept edits to the search conditions from the employer, re-search the job seeker database for job seekers using the edited search conditions, and display the search results for the re-searched candidate job seekers on the employer terminal 20. This allows the employer to optimize the search conditions by adjusting the search conditions created from the target information and checking the changes in the search results.

[0099] The search result display control unit 116 may, for example, display the search conditions and corresponding search results on the recruiter terminal 20 and accept editing of the search conditions (deletion, addition, modification, etc.) from the recruiter terminal 20. Alternatively, after accepting the editing of the search conditions, the search result display control unit 116 may immediately perform a new search for job seekers and update the search results displayed on the recruiter terminal 20 with the results of the new search using the edited search conditions.

[0100] <Artificial Intelligence Department 120> The artificial intelligence unit 120 is configured to receive input from each functional unit and return the instructed output. The artificial intelligence used by each functional unit of the server device 10 may be common to all units, or it may be prepared individually for each functional unit.

[0101] The artificial intelligence unit 120 may be an AI (Artificial Intelligence) equipped with trained models such as transformers including GPT (Generative Pretrained Transformer, including GPT-1 to GPT-5), BERT (Bidirectional Encoder Representations from Transformers), BART (Bidirectional and Auto-regressive Transformer), and language models such as recurrent neural networks (RNN). The artificial intelligence unit 120 may be, for example, a general-purpose learning model including various language models, large-scale language models, and generative AI, or an AI agent, and may include specific models such as OpenAI's GPT (registered trademark), Google's Gemini (registered trademark), and models provided through services and platforms such as Microsoft's Azure (registered trademark) AI Studio. Generative AI may be, for example, text generation AI, image generation AI, multimodal generation AI, etc. The trained model may be called an artificial intelligence model, machine learning model, or deep learning model. In addition, the artificial intelligence unit 120 can include any pre-trained model.

[0102] Specific machine learning algorithms used to build trained models include nearest neighbors, naive Bayes, decision trees, support vector machines, and deep learning using neural networks. The artificial intelligence unit 120 can apply these algorithms as appropriate.

[0103] The artificial intelligence unit 120 may have a trained model constructed by a learning method such as supervised learning, unsupervised learning, or self-supervised learning. In supervised learning, machine learning is performed using training data. Training data consists of pairs of input data and output data (correct answer data) for training. Furthermore, the trained model may not only be one trained for a specific task, but also a general-purpose learning model that can be used universally for a wide range of tasks.

[0104] The artificial intelligence unit 120 may include a natural language model as artificial intelligence, or it may be a general-purpose learning model such as a Large Language Model (LLM). An LLM is a learning model that has been pre-trained on a large amount of large data consisting of text data, etc. (for example, (i) web content on the internet, or (ii) data stored in a predetermined database), and can perform various language processing tasks by being given a task. According to the given prompt, it can perform a wide range of natural language processing tasks, such as understanding sentence patterns and context, responding to questions, and generating sentences. Such a general-purpose learning model may include a pre-trained model that can handle various tasks without fine-tuning by One-shot Learning or Few-shot Learning. Furthermore, the general-purpose learning model may also be configured to handle various tasks by Zero-shot Learning. The artificial intelligence used in each functional unit of the control unit 11 may be a separate pre-trained model, or it may be a common general-purpose pre-trained model. In addition, the artificial intelligence unit 120 may include a small-scale language model or a medium-scale language model that is smaller in scale than a large-scale language model as a pre-trained model. Small-scale and medium-scale language models are natural language processing models that are trained on less data (and constructed with fewer parameters) compared to large-scale language models.

[0105] The pre-trained models included in the artificial intelligence unit 120 (pre-trained models used in each functional unit) can undergo additional training using methods such as transfer learning and fine-tuning. For example, whenever new data is registered, the artificial intelligence unit 120 may perform additional training and fine-tuning using this new data as training data. This improves the accuracy of the information output from the pre-trained models.

[0106] The trained model included in the artificial intelligence unit 120 may be a trained model (distilled model) obtained by knowledge distillation using the original trained model. In knowledge distillation, a trained model such as a large-scale language model is used as the teacher model, and the student model is trained by adjusting the parameters of the student model so that the loss of the student model's output (soft target loss) relative to the teacher model's output (soft target) is small, and that student model becomes the distilled model. Alternatively, the student model may be trained so that the loss of the student model's output (hard target loss) relative to the correct labels (hard target) of the teacher data (combination of input data and output data of the trained model) is small. Compared to the original trained model (teacher model), the distilled model has performance close to that of the trained model, but with fewer parameters and a lower processing load. Therefore, by using the distilled model, the cost of the information processing system 1 can be reduced.

[0107] For example, the trained model used in each functional unit may be a distilled model trained using combinations of input and output data from a large-scale language model as training data. Alternatively, when the information processing system 1 is introduced, a large-scale language model may be used as the trained model in each functional unit, and once training data from the large-scale language model has been accumulated, the distilled model obtained by knowledge distillation using that training data may be used as the trained model in each functional unit.

[0108] An AI agent (also called an autonomous agent) may, in response to a goal (objective, purpose, etc.) or task (output of XX) input by a user, break down the task into subtasks, actions, etc., in order to reach the goal or accomplish the task, and may perform at least one of the following actions: collecting and analyzing necessary data, using external tools, generating and executing programs, etc. The AI ​​agent takes the information and instructions input by the user as its goal, autonomously selects and executes tasks, actions, etc. according to the goal, and outputs information according to the goal, and does not require user intervention (operation input). However, the AI ​​agent may, if necessary, request confirmation from the user or feedback from the user. Furthermore, the AI ​​agent may autonomously plan and execute, evaluate the execution results itself, and autonomously perform learning (including in-context learning, etc.) to aim at achieving the goal or improving the accuracy of achievement. For example, the AI ​​agent may autonomously update itself based on the execution results of subtasks (e.g., collected information, results of information analysis, etc.).

[0109] Furthermore, the AI ​​agent may be a multi-agent system composed of multiple AI agents. In this case, the multiple AI agents may have different roles, capabilities, access rights, etc. Multiple AI agents may cooperate to solve tasks by communicating (dialogue) with each other using natural language, a predetermined protocol, etc. The cooperation between each AI agent is not limited to a hierarchical structure (superior-subordinate relationship). For example, in a multi-agent system, multiple AI agents may autonomously engage in discussions, voting, etc., and the final output may be decided by consensus.

[0110] <Display section> The display unit 211 of the job seeker terminal 20 shown in Figure 4B, and the display unit 311 of the job seeker terminal 30 shown in Figure 4C, respectively, display the screen (information) indicated by the data transmitted from the server device 10.

[0111] <Operation acquisition section> The operation acquisition unit 212 of the employer terminal 20 receives operations from the employer using the employer terminal 20. The operation acquisition unit 312 of the job seeker terminal 30 receives operations from the job seeker using the job seeker terminal 30.

[0112] 3. Information Processing Methods This section describes the information processing method of the server device 10. In this information processing method, each part of the server device 10 is executed by a computer as a step.

[0113] The information processing method described above comprises an acquisition step, a target creation step, a search condition creation step, and a search result display control step. In the acquisition step, job-related information, including information about job postings from employers, is acquired. In the target creation step, multiple target information pieces are created based on the job-related information and first reference information, each representing a different profile of a person sought by the employer in the job posting. In the search condition creation step, for each of the multiple target information pieces, search conditions are created based on the target information and second reference information to search for job seekers registered in the job seeker database who match the profile. In the search result display control step, search results for candidate job seekers, who are those found using the search conditions for each of the multiple target information pieces, are displayed.

[0114] Figure 7 is an activity diagram showing an example of the flow of information processing (job seeker search processing) performed by information processing system 1. The information processing will be explained below in accordance with each activity in this activity diagram.

[0115] The job seeker search process begins with the employer's terminal 20 inputting (including uploading, etc.) job-related information (Activity A101). The server device 10 acquires the job-related information entered on the employer terminal 20 (Activity A102). After acquiring the job-related information, the server device 10 creates target information based on the job-related information (Activity A103). Furthermore, the server device 10 creates search conditions based on the target information (Activity A104).

[0116] After creating the search criteria, the server device 10 searches for job seekers using the created search criteria (Activity A105). Next, the server device 10 creates search results for the found candidate job seekers (Activity A106). Furthermore, the server device 10 outputs the created search results to the recruiter terminal 20 (Activity A107). As a result, the search results are displayed on the recruiter terminal 20 (Activity A108).

[0117] 4. Effect The function of this embodiment can be summarized as follows: In other words, it can effectively support the recruitment activities of employers. In particular, by displaying at least one of the first number of candidates (the number of job seekers who have not viewed their registration information) and the second number of candidates (the number of job seekers to whom no recruitment documents have been sent) as search results based on search criteria created based on target information, employers can evaluate their search criteria.

[0118] Furthermore, by displaying the number of unread messages (number of first-choice candidates) and unsent messages (number of second-choice candidates) for each target group, employers can easily identify target groups they have not yet approached. This not only provides search criteria for finding job seekers, but also supports decision-making in recruitment activities, such as strengthening scouting efforts and reconsidering target settings.

[0119] Although embodiments of the present invention have been described above, the present invention is not limited thereto and can be modified as appropriate without departing from the technical spirit of the invention.

[0120] 5. Others In the above embodiment, the server device 10 performed various storage and control functions, but instead of the server device 10, multiple external devices may be used. That is, various information and programs may be stored in a distributed manner across multiple external devices using blockchain technology or the like. In particular, the artificial intelligence unit 120 may be an external component of the server device 10. In that case, the external artificial intelligence unit 120 may be provided by, for example, an artificial intelligence service server, and is configured to receive input from each functional unit of the server device 10, receive requests to execute artificial intelligence services, and return the instructed output as a processing result to the server device 10. The artificial intelligence service server may be a server that provides services using a learning model, or a server that performs language processing tasks using a language model. In particular, the artificial intelligence service server may be constructed using an LLM. The artificial intelligence service server receives prompt input in the form of text, images, audio, etc., and generates and responds with answers to the prompts.

[0121] At least one of the devices included in the information processing system 1 may be located outside the country in which the functions of the information processing system 1 are performed.

[0122] The embodiments of this model are not limited to the information processing system 1, but may also be an information processing method or a program. In the information processing method, the information processing device executes each step of the information processing system 1. In the program, the computer causes the computer to execute each step of the information processing system 1.

[0123] The product may be provided in any of the following embodiments.

[0124] (1) An information processing system comprising at least one processor, wherein the processor is configured to perform the following steps by reading a program, the acquisition step involves acquiring job-related information including information about a job posting by an employer, the target creation step involves creating a plurality of target information, each representing a different person profile sought by the employer in the job posting, based on the job-related information and first reference information, where the first reference information is information about the correlation between the job-related information and the target information, and the search condition creation step involves creating a search condition for each of the plurality of target information, where the target information An information processing system that, based on the report and second reference information, creates search conditions for searching for job seekers who match the profile from among the job seekers registered in the job seeker database, where the second reference information is information relating to the correlation between the target information and the search conditions, and in the search result display control step, displays the search results for candidate job seekers who have been searched using the search conditions for each of the multiple target information, where the search results include at least one of the number of candidate job seekers whose registration information has not been viewed by the employer, and the number of candidate job seekers to whom the employer has not sent a scouting document.

[0125] (2) An information processing system as described in (1) above, wherein the job-related information includes at least the requirements for the job.

[0126] (3) An information processing system according to (1) or (2) above, wherein the search results further include an expected response rate calculated based on the number of scouting documents received and the number of replies to the scouting documents in the set of candidate job seekers that have been searched.

[0127] (4) An information processing system according to any one of (1) to (3) above, wherein the search results further include the number of candidate job seekers that have been searched.

[0128] (5) An information processing system according to any one of (1) to (4) above, wherein in the search condition creation step, a number of search conditions corresponding to the target information are created for each of the multiple target information, and in the search result display control step, the candidate job seeker is searched for each of the search conditions belonging to each of the multiple target information.

[0129] (6) An information processing system as described in (5) above, wherein in the search result display control step, the system displays the search results for each of the multiple target information, based on the set of candidate job seekers searched by all the search conditions belonging to the target information.

[0130] (7) An information processing system as described in (6) above, wherein the set is a set of candidate job seekers who have been searched multiple times in multiple search conditions belonging to one of the target information.

[0131] (8) Information processing system as described in (1) to (7) above, wherein the processor is configured to further perform the following steps: in the query reception step, it receives input of required queries in the search conditions from the job seeker; in the search condition creation step, it creates the search conditions that include the required queries based on the target information and the required queries and the second reference information, wherein the second reference information is information relating to the correlation between the combination of the target information and the required queries and the search conditions.

[0132] (9) An information processing system according to any one of (1) to (8) above, wherein in the search result display control step, the system receives an edit of the search conditions from the employer, uses the edited search conditions to search for job seekers again from the job seeker database, and displays the search results for the re-searched candidate job seekers.

[0133] (10) An information processing system according to any one of (1) to (9) above, comprising a server device having the processor and a terminal that can access the server device.

[0134] (11) An information processing method wherein an information processing device performs each step of the information processing system described in any one of (1) to (9) above.

[0135] (12) A program that causes a computer to perform each step of the information processing system described in any one of (1) to (9) above. Of course, this is not always the case.

[0136] Finally, while various embodiments relating to this disclosure have been described, these are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be implemented in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0137] 1: Information Processing System 2: Communication lines 10: Server device 11: Control Unit 111: Basic Display Control Unit 112: Acquisition Department 113: Target Creation Department 114: Query Reception Department 115: Search Criteria Creation Section 116: Search Result Display Control Unit 120: Artificial Intelligence Department 12: Storage section 13: Communications Department 14: Communications bus 20: Job seeker terminal 21: Control Unit 211:Display section 212: Operation acquisition section 22: Storage section 23: Communications Department 24: Input section 25: Output section 26: Communications bus 30: Job seeker terminal 31: Control Unit 311: Display section 312: Operation acquisition section 32: Storage section 33: Communications Department 34: Input section 35: Output section 36: Communications bus RD:Search result display screen RL: Results List SA: Search criteria display area SC: Search Criteria SD: Search criteria display screen SN: Search condition name ST: Search Strategy

Claims

1. An information processing system, Equipped with at least one processor, The aforementioned processor is configured to perform the following steps by reading a program: In the acquisition step, job-related information, including information about the employer's job postings, is acquired. In the target creation step, based on the job-related information and the first reference information, multiple target information sets are created, each representing a different candidate profile sought by the employer in the job posting. Here, the first reference information is information relating to the correlation between the job-related information and the target information. In the search condition creation step, for each of the multiple target information items, search conditions are created to search for job seekers who match the profile from among the job seekers registered in the job seeker database, based on the target information and the second reference information, where the second reference information is information regarding the correlation between the target information and the search conditions. The search result display control step displays search results for candidate job seekers who have been searched using the search conditions for each of the multiple target information items, wherein the search results include at least one of the number of candidate job seekers whose registration information has not been viewed by the employer, and the number of candidate job seekers to whom the employer has not sent a scouting document.

2. In the information processing system described in claim 1, The aforementioned job-related information is an information processing system that includes at least the requirements for the aforementioned job.

3. In the information processing system described in claim 1, The search results further include an information processing system that calculates an expected response rate based on the number of recruitment letters received and the number of replies to recruitment letters in the searched set of candidate job seekers.

4. In the information processing system described in claim 1, The search results further include the number of the candidate job seekers found in the search, in an information processing system.

5. In the information processing system described in claim 1, In the search condition creation step, for each of the multiple target information items, a number of search conditions corresponding to the target information are created. The search result display control step involves an information processing system that searches for candidate job seekers according to the search conditions belonging to each of the multiple target information items.

6. In the information processing system described in claim 5, An information processing system that, in the search result display control step, displays the search results for each of the multiple target information, based on the set of candidate job seekers found by all the search conditions belonging to the target information.

7. In the information processing system described in claim 6, The aforementioned set is an information processing system in which candidate job seekers who have been searched multiple times in multiple search conditions belonging to one of the target information are organized.

8. In the information processing system described in claim 1, The aforementioned processor is configured to perform the following steps: In the query reception step, the employer inputs the required queries for the search conditions. In the search condition creation step, the information processing system creates the search condition that includes the required query based on the target information, the required query, and the second reference information, wherein the second reference information is information relating to the correlation between the combination of the target information and the required query and the search condition.

9. In the information processing system described in claim 1, The information processing system, in the search result display control step, receives an edit of the search conditions from the employer, uses the edited search conditions to search for job seekers again from the job seeker database, and displays the search results for the candidate job seekers found through the search.

10. In the information processing system described in claim 1, A server device having the aforementioned processor, A terminal that can access the aforementioned server device, An information processing system equipped with the following features.

11. Information processing method, An information processing method comprising an information processing device performing each step of the information processing system described in any one of claims 1 to 9.

12. It is a program, A program for causing a computer to perform each step of the information processing system described in any one of claims 1 to 9.

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