Information processing systems, information processing methods, and programs

Abstract

We provide information processing systems and other tools that can create appropriate job postings. [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 job information acquisition step, it acquires job information that includes at least the requirements of the job; in the candidate extraction step, it extracts candidates suitable for the job from among job seekers registered in a database based on the job information and presents the extracted candidates; and in the job editing step, it accepts the selection of a citation range in the candidate's registration information and adds the content based on the citation range to the job information.

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 evaluating and improving documents.

Prior Art Documents

Patent Documents

[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 create appropriate job offer information.

[0005] In view of the above circumstances, the present invention aims to provide an information processing system or the like that can create appropriate job offer information.

Means for Solving the Problems

[0006] According to one aspect of the present invention, there is provided an information processing system including at least one processor configured to execute the following steps by reading a program. In a job offer information acquisition step, job offer information including at least the requirements of a job offer is acquired. In a candidate extraction step, candidates suitable for the job offer are extracted from job seekers registered in a database based on the job offer information, and the extracted candidates are presented. In a job offer editing step, a selection of a citation range in the registration information of the candidates is received, and the content based on the citation range is added to the job offer information.

[0007] According to such an aspect, a job offerer can create appropriate job offer information.

Brief Description of the Drawings

[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 an initial information input screen ID displayed on the job seeker terminal 20. [Figure 6] This figure shows an example of the job information editing screen ED displayed on the job seeker terminal 20. [Figure 7] This figure shows an example of how candidate information is displayed in the extraction result display area EA of the job posting editing screen ED. [Figure 8] This figure shows an example of how additional candidate information is displayed in the extraction result display area EA of the job posting editing screen ED. [Figure 9] This figure shows an example of the job information editing screen ED with the registration information display area RA displayed. [Figure 10] This figure shows an example of the state where the citation range CR is selected in the registration information display area RA. [Figure 11] This figure shows an example of the state in which editing of the additional content AC is performed in the additional content display field AF. [Figure 12] This figure shows an example of the state where the content of the quoted range CR (additional content AC) has been added to the job information display section JF. [Figure 13] This figure shows an example of how the search results SR are displayed in the job information display area JA. [Figure 14] This is an activity diagram showing an example of the flow of information processing (job posting creation process) 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 for implementing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or it may be provided as a downloadable medium from an external server, or it may be provided so that the program 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] In addition, in one embodiment, the "unit" may include, for example, hardware resources implemented by a circuit in a broad sense and information processing of software that can be specifically realized by these hardware resources. Also, in one embodiment, various types of information are handled, and these information are represented, for example, by physical values of signal values representing voltage and current, the high and low of signal values as a set of binary bits composed of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation can be executed on a circuit in a broad sense.

[0013] Furthermore, a circuit in a broad sense is a circuit realized by appropriately combining at least a circuit (Circuit), circuitry (Circuitry), a processor (Processor), and a memory (Memory), etc. Also, the processor may be a general-purpose processor or a dedicated circuit. That is, it includes an application specific integrated circuit (ASIC), programmable logic devices (for example, a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0014] 1. Hardware Configuration In this section, the hardware configuration will be described.

[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 job applicant terminals 20, and a plurality of job seeker terminals 30. The server device 10, the job applicant terminals 20, and the job seeker terminals 30 are configured to be mutually communicable through the communication line 2. The connections of the server device 10, the job applicant terminals 20, and the job seeker terminals 30 may be wired or wireless. Also, the server device 10, the job applicant terminals 20, and the job seeker terminals 30 are each an example of an information processing device.

[0016] The information processing system 1 constitutes at least a part of a job offer - job seeking system used by, for example, a plurality of job applicants (first job applicant U1 and second job applicant U2) and a plurality of job seekers (first job seeker U3 and second job seeker U4). The information processing system 1 mainly performs operations such as searching for job seekers by job applicants, searching for job offers by job seekers, and mediating communication between job applicants and job seekers. For example, the information processing system 1 provides and manages a talent matching platform, a talent matching service, etc. that are used by job applicants and job seekers. In one embodiment, the information processing system 1 is composed 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 predetermined programs stored in the memory unit 12. That is, information processing by software stored in the memory unit 12 is concretely 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 a single unit, and the server device 10 may have multiple control units 11 for each function. The server device 10 may also be composed of a combination of these.

[0019] <Storage section 12> The storage unit 12 stores various types of information as defined above. This can be done, for example, as a storage device such as a solid-state drive (SSD) that stores various programs related to the server device 10 executed by the control unit 11, or as memory such as random access memory (RAM) that stores temporarily necessary information (arguments, arrays, etc.) related to program calculations. The storage unit 12 stores various programs, variables, etc. related to the server device 10 executed by the control unit 11.

[0020] <Communications Department 13> The communication unit 13 preferably uses wired communication methods such as USB, IEEE1394, Thunderbolt®, and wired LAN network communication, but may also include wireless LAN network communication, mobile communication such as LTE / 5G, and Bluetooth® communication as needed. In other words, the communication unit 13 may be implemented as a collection of these multiple communication methods. Furthermore, the server device 10 may communicate various information with the outside world via the communication unit 13 and the network.

[0021] The server device 10 may be on-premises or in a cloud environment. The 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] 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.

[0025] <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.

[0026] <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.

[0027] <Job seeker terminal 30> The job seeker terminal 30 is an information processing terminal used by job seekers and can access the server device 10. "Job seekers" include, for example, those who are looking for a new job or a new job (e.g., currently employed people (those seeking a new job), prospective graduates (job seekers), students, etc.), and those who are interested in changing jobs or finding employment.

[0028] 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.

[0029] 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).

[0030] 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).

[0031] As shown in Figure 4A, the server device 10 (control unit 11) comprises a basic display control unit 111, a job information creation unit 112, a job information acquisition unit 113, a revision suggestion unit 114, a candidate extraction unit 115, a job editing unit 116, and an artificial intelligence unit 120.

[0032] 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.

[0033] <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.

[0034] <Job Posting Creation Department 112> The job posting creation unit 112 is configured to create job postings. "Job postings" are information that includes at least the requirements for the job. In addition to the requirements, the job postings may also include job descriptions. "Job descriptions" may include, for example, industry, job title, duties, department, position, annual salary, work location, work style, etc. "Job requirements" may include, for example, required skills, required experience, required qualifications, etc. Job descriptions and job requirements may be described using, for example, keywords, numbers, sentences, etc.

[0035] Job postings typically include multiple categories for classifying requirements (e.g., "Department / Job Title," "Job Description," "Annual Salary," "Job Type," "Industry," "Required Qualifications (Experience / Skills)," "Preferred Qualifications (Experience / Skills)," etc.), with each requirement described within its corresponding category. While job postings are typically in the form of a job application form, they do not necessarily need to be formatted like one; they can be in the form of a non-standard document such as a memo listing the job description and requirements.

[0036] Job postings may include multiple requirements with different priorities. For example, a job posting may include mandatory requirements that job seekers must meet and desirable requirements that job seekers may meet. Mandatory requirements have a higher priority than desirable requirements. Both mandatory and desirable requirements may have multiple sub-requirements. Furthermore, individual priorities may be set for each requirement within the mandatory and desirable requirements.

[0037] The job posting creation unit 112 may create job postings based on text indicating the requirements for the job posted, a file containing the requirements for the job posted, or other information that has been uploaded or stored in a location specified by the job posting terminal 20.

[0038] Furthermore, the job posting creation unit 112 may receive initial information from the recruiter terminal 20 that includes at least keywords related to the job posting, and create job postings based on this initial information and the first reference information. This makes it possible to seamlessly carry out the process from creating job postings based on materials prepared by the recruiter, to editing (refinement) of the job postings by the job posting editing unit 116, as described later, for job postings for which job postings have not yet been created.

[0039] "Initial information" includes, for example, a job posting document containing job keywords that represent the above-mentioned requirements for the job, comments containing keywords or sentences that represent the desired candidate profile (persona), the purpose of the job, etc. Initial information may also include, for example, a job posting document created by the recruiter (headhunter), a job posting document in progress (draft, memo, etc.), etc. Initial information may also include materials created by the headhunter for the organization they are representing. Furthermore, the job posting document may be a job posting used in an external service different from the service provided by Information Processing System 1 (i.e., a job posting in a format different from the format used in Information Processing System 1).

[0040] The job posting creation unit 112 may accept either the job posting document or a comment as initial information, or it may accept a combination of the job posting document and a comment as initial information. For example, the job posting creation unit 112 may accept the upload of the job posting document (or the specification of its storage location) and the input of a comment (such as the purpose of the job posting) associated with the job posting document from the job seeker terminal 20. Alternatively, the job posting creation unit 112 may accept input of both the job posting document and a comment, use only the job posting document as initial information, record the comment as an attribute of the job posting information created based on the job posting document (supplementary information linked to the job posting), and not use the recorded comment as initial information.

[0041] The first reference information is information relating to the correlation between initial information and job postings. 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 initial information and job postings. The correlations included in the first reference information can be constructed, for example, by statistically analyzing data that records initial information and corresponding job postings.

[0042] The first reference information may include a set of parameters for generating job information from initial information. For example, the first reference information may be various pre-trained models. For example, the first reference information may include a job information creation model, which is a machine learning model that has been trained to take initial information as input and output job information, or a general-purpose machine learning model. In this case, the job information creation unit 112 inputs the initial information into the job information creation model and causes the job information creation model to output job information.

[0043] The job posting creation model is included in the artificial intelligence unit 120. The job posting creation model, which is trained to output job postings, may be constructed, for example, by training with initial information data and corresponding job posting data as training data. In such a job posting creation model, parameters calculated and tuned through training construct a correlation between the initial information and the job postings.

[0044] If the job posting creation model is a general-purpose learning model (for example, a language model such as a large-scale language model, a generative AI, etc.), the job posting creation unit 112 inputs a prompt to the job posting creation model that includes initial information and an instruction to output job postings corresponding to the initial information, causing the job posting creation model to output job postings. The job posting creation unit 112 may also generate a prompt that gives the job posting creation model an instruction to create job postings and input this prompt to the job posting creation model. In addition to the initial information and the instructions to create and output job postings, the job posting creation unit 112 may also input a prompt to the job posting creation model that includes, for example, one or more samples of initial information and one or more samples of corresponding job postings as examples, samples, or training data of input and output pairs. Here, the parameters that construct the job posting creation model and the prompt that includes an instruction to output job postings corresponding to the initial information construct a correlation between the initial information and the job postings.

[0045] The job posting creation unit 112 may, for example, use the first reference information to replace keywords included in the initial information with keywords appropriate as job requirements. The job posting creation unit 112 may also create a range of requirements (e.g., salary range) based on numerical values ​​(e.g., annual salary) included in the initial information. Furthermore, the job posting creation unit 112 may convert the format of the initial information, including the job posting, into a format used by the information processing system 1 (i.e., a format corresponding to editing by the job posting editing unit 116 described later).

[0046] The job posting creation unit 112 may create job postings based on initial information, similar job postings that include at least the requirements of similar job postings, and first reference information. "Similar job postings" are other job postings registered in the job posting database that are similar to the job posting for which job postings are being created. This allows for the creation of job postings in which requirements of job postings not included in the initial information are supplemented based on the requirements of similar job postings, thereby reducing the effort required for employers to create job postings.

[0047] The number of similar job postings referenced by the job posting creation unit 112 may be one or multiple. Similar job postings are, for example, job postings registered in the job database. Furthermore, similar job postings may be from employers different from the employer creating the job posting for which the job posting is being created. In addition, similar job postings may include job postings that are no longer being advertised (job postings that have been filled, job postings whose application period has ended, etc.).

[0048] The similarity between two job postings is determined, for example, by the difference in the features of the job information (e.g., job requirements) of the two job postings (e.g., the distance between vectors obtained by vectorizing words or sentences). The job posting creation unit 112 determines that two job postings are similar if the difference in their features is small (e.g., the cosine similarity, which is the distance between the two vectors, is above a threshold). Vectorization is performed by quantification using known methods such as natural language processing using morphological analysis or encoding. Alternatively, features may be calculated by referring to a table in which features are defined for each keyword. Furthermore, the job posting creation unit 112 may input the two job postings into a similarity determination model, which is a learning model or a general-purpose learning model, and have the similarity determination model output a similarity or similarity determination result.

[0049] The job posting creation unit 112 may determine similarity between two job postings based on the agreement or disagreement of the content (requirements) for each corresponding item in the job postings of each job posting. For example, the job posting creation unit 112 may determine that two job postings that match in job title and / or industry are similar. In addition, when determining the similarity of job postings, agreement or disagreement of the content (requirements) of items such as work location and annual salary may be considered. Furthermore, the job posting creation unit 112 may determine that two job postings that match in annual salary range are similar. Also, the job posting creation unit 112 may determine that two job postings that match in the number of items (requirements) is above a certain threshold are similar.

[0050] When using similar job postings, the first reference information is information regarding the correlation between the combination of initial information and similar job postings, and the job postings themselves. The correlations included in this first reference information can be constructed, for example, by statistically analyzing data that records the combination of initial information and similar job postings and the corresponding job postings.

[0051] The first reference information may include a job information creation model, which is a machine learning model or a general-purpose machine learning model, that is capable of taking a combination of initial information and similar job information as input and outputting job information. In this case, the job information creation unit 112 inputs the combination of initial information and similar job information into the job information creation model and causes the job information creation model to output job information.

[0052] In this job posting creation model, parameters calculated and tuned through learning construct a correlation between the combination of initial information and similar job postings and the job postings. Alternatively, the parameters used to construct the job posting creation model, along with prompts containing instructions to output job postings corresponding to the combination of initial information and similar job postings, construct a correlation between the combination of initial information and similar job postings and the job postings.

[0053] The job posting creation unit 112 may, for example, input a prompt to the job posting creation model, which is a general-purpose learning model, that includes an instruction to extract job requirements that cannot be derived from the initial information from similar job postings and add them to the similar job postings. This allows, for example, if the initial information does not include information on annual salary, to add an annual salary, based on the annual salaries of similar job postings, as a requirement to the job posting.

[0054] The job posting creation unit 112 may register the created job postings in the job database as job postings to recruit job seekers.

[0055] Figure 5 shows an example of an initial information input screen ID displayed on the job seeker terminal 20. The initial information input screen ID includes a file upload field FF, file information FI, and supplementary information input field SF.

[0056] The file upload field FF accepts the upload of a file to be entered as initial information. When input is performed on the file selection button B11 within the file upload field FF, a file selection screen is displayed on the job seeker terminal 20. The file information FI displays the name of the file uploaded by the file upload field FF. Files may also be uploaded by dragging and dropping them into the file upload field FF.

[0057] The supplementary information input field SF accepts text input for supplementary information (comments) to be entered as initial information. When an input operation is performed on the send button B12 in the supplementary information input field SF, the uploaded file displayed as file information FI and the supplementary information entered in the supplementary information input field SF are sent to the server device 10 as initial information, and the job information creation unit 112 creates the job information. Note that even if the supplementary information input field SF is left blank, only the uploaded file may be sent to the server device 10 as initial information.

[0058] <Job Information Acquisition Department 113> The job information acquisition unit 113 is configured to acquire job information that includes at least the requirements for the job. The job information acquisition unit 113 may also acquire job information created based on initial information. In other words, the job information acquired by the job information acquisition unit 113 may be created by the job information creation unit 112, or it may be prepared by the employer (for example, a file uploaded from the employer terminal 20, a text document entered from an input screen displayed on the employer terminal 20, etc.).

[0059] <Revision proposal section 114> The revision proposal unit 114 is configured to create revision proposals for items included in the job information based on the job information acquisition unit 113 and the second reference information, and to display the created revision proposals on the job seeker terminal 20, linked to the items in question. This allows job seekers to work while referring to the revision proposals when editing the job information by the job editing unit 116, which will be described later, thereby improving the efficiency of editing the job information.

[0060] "Suggested revisions" include information to satisfy the recommended conditions set for each item. Examples of recommended conditions include the number of characters in the text explaining the requirements in one item (an example of a suggested revision is, "We recommend at least XX characters"), and the number of requirements to be included in one item (an example of a suggested revision is, "We recommend at least XX items").

[0061] The second reference information is information regarding the correlation between job postings and proposed revisions. 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 job postings and proposed revisions. The correlations included in the second reference information can be constructed, for example, by statistically analyzing data (e.g., number of characters, number of items, etc.) that records job postings and corresponding proposed revisions.

[0062] The second reference information may include a set of parameters for generating revision suggestions from job postings. For example, the second reference information may be various pre-trained models. For example, the second reference information may include a revision suggestion model, which is a machine learning model that has been trained to take initial job postings as input and output revision suggestions, or a general-purpose machine learning model. In this case, the revision suggestion unit 114 inputs the job postings into the revision suggestion model and causes the revision suggestion model to output revision suggestions.

[0063] The correction suggestion model is included in the artificial intelligence unit 120. The correction suggestion model, which is trained to output correction suggestions, may be constructed, for example, by training with job information data and corresponding correction suggestion data as training data. In such a correction suggestion model, parameters calculated and tuned through training establish a correlation between job information and correction suggestions.

[0064] If the proposed modification model is a general-purpose learning model (for example, a language model such as a large-scale language model, a generative AI, etc.), the proposed modification unit 114 inputs a prompt to the proposed modification model that includes job information and an instruction to output a proposed modification corresponding to the job information, causing the proposed modification model to output a proposed modification. The proposed modification unit 114 may also generate a prompt that gives the proposed modification model an instruction to create a proposed modification and input this prompt to the proposed modification model. In addition to the job information and the instruction to create and output a proposed modification, the proposed modification unit 114 may also input a prompt to the proposed modification model that includes, for example, one or more samples of job information and one or more samples of corresponding proposed modifications as examples, samples, or training data of input and output pairs. Here, the parameters for constructing the proposed modification model and the prompt that includes an instruction to output a proposed modification corresponding to the job information establish a correlation between the job information and the proposed modification.

[0065] The proposed revisions may include information indicating an evaluation (appropriateness) of the requirements compared to other job postings. Here, "other job postings" may refer to all job postings registered in the job database, or to job postings that meet specific conditions (for example, similar job postings). For example, the proposed revisions may include information such as "the requirements are stricter (or looser) compared to similar job postings."

[0066] The revision proposal unit 114 may create revision proposals based on the job information acquired by the job information acquisition unit 113, similar job information that includes at least the requirements of similar job postings, and second reference information. This allows employers to edit job information based on the results of comparison with similar job postings, thereby further improving the efficiency of editing job information.

[0067] In this case, the second reference information is information regarding the correlation between the combination of job postings and similar job postings and the proposed revisions. The correlations included in this second reference information can be constructed, for example, by statistically analyzing data that records the combination of job postings and similar job postings and the corresponding proposed revisions.

[0068] The second reference information may include a machine learning model, or a general-purpose machine learning model, which is capable of taking a combination of job postings and similar job postings as input and outputting a revision suggestion. In this case, the revision suggestion unit 114 inputs the combination of job postings and similar job postings into the revision suggestion model and causes the revision suggestion model to output a revision suggestion.

[0069] In the proposed modification model, parameters calculated and tuned through learning establish a correlation between the combination of job postings and similar job postings and the proposed modifications. Alternatively, parameters used to construct a general-purpose learning model, along with prompts containing instructions to output modification proposals corresponding to the combinations of job postings and similar job postings, establish a correlation between the combinations of job postings and similar job postings and the proposed modifications.

[0070] The revision suggestion unit 114 may input prompts to the revision suggestion model, which is a general-purpose learning model, that include instructions to compare the requirements of similar job postings (e.g., the mean) with the requirements of the job posting and suggest revisions based on the difference between the two. This will generate revision suggestions that, for example, suggest that the salary range of the job posting is lower (or higher) than the average salary range of similar job postings.

[0071] Figure 6 shows an example of the job information editing screen ED displayed on the recruiter terminal 20. The job information editing screen ED includes a job information display area JA and an extraction result display area EA.

[0072] The job posting display area JA shows file information FI, company information EI, job posting display area JF, cancel button B21, and confirm button B22.

[0073] The File Information FI displays the name of the file uploaded as initial information, similar to the Initial Information Input Screen ID in Figure 5. The Company Information EI displays the name of the employer (company) posting the job opening. If the employer is not a headhunter (i.e., the employer is an organization or its representative), the Company Information EI does not need to be displayed, and instead, the department name, group name, contact person's name, etc., may be displayed.

[0074] The job posting display area JF shows at least one item IM, at least one requirement RM, at least one proposed revision RS, and an edit acceptance object EO. ​​Each item IM contains at least one requirement RM from the job posting information that corresponds to that item IM, described (displayed) in the form of keywords, sentences, labels (tags), etc. In addition, for item IMs for which a proposed revision RS has been created, the corresponding proposed revision RS is displayed. The edit acceptance object EO accepts editing instructions for the requirement RM.

[0075] If an input operation is performed on the Cancel button B21, the edits made to the job information in the Job Information Display Field JF will be discarded. Conversely, if an input operation is performed on the Confirm button B22, the content of the job information edited in the Job Information Display Field JF will be registered in the job database.

[0076] The extraction result display area EA is located next to the job information display area JF (to the right of the job information display area JF in the example in Figure 6). The extraction result display area EA displays the filter setting area FA and the display reception object IO. The filter setting area FA accepts input for the display filter (narrowing conditions) of candidates extracted by the candidate extraction unit 115, which will be described later. The display reception object IO accepts the display of the list of extracted candidates.

[0077] <Candidate extraction section 115> The candidate extraction unit 115 extracts candidates suitable for the job posting from among the job seekers registered in the job seeker database based on the job posting information acquired by the job posting information acquisition unit 113, and presents the extracted candidates to the employer.

[0078] "Job seekers registered in the job seeker database" refers to job seekers whose registration information is recorded in the job seeker database. "Registration information" includes the job seeker's resume, work history, and other profile information. A "resume" is a document that mainly describes the job seeker's profile, current situation, educational background, work history, and desired working conditions. A "work history," also called a resume, is a document in which a job seeker communicates their past work experience, skills, qualifications, etc., to an employer. Registration information may also include conditions such as the industry and job type that the job seeker desires.

[0079] A "candidate" is, for example, a job seeker whose registration information meets at least some of the requirements included in the job posting. Typically, a candidate may be a job seeker who meets all of the requirements included in the job posting. Alternatively, a candidate may be a job seeker who meets at least the highest priority requirements (e.g., mandatory requirements).

[0080] The candidate extraction unit 115 may, for example, create search criteria for finding job seekers suitable for the job opening and extract job seekers found using those search criteria as candidates. "Search criteria" are conditions for searching for job seekers by referring to the registration information registered in the job seeker database. Search criteria may include, for example, keywords, attributes (tags, labels, etc.), and combinations thereof. Search criteria may also include search categories. "Search categories" are information that specifies the scope of registration information to be searched using keywords or attributes (for example, items such as work history, job type, industry, skills, qualifications, age, desired annual salary, etc.).

[0081] The candidate selection unit 115 may select one candidate or multiple candidates. In other words, the candidate selection unit 115 may select multiple candidates and present the selected multiple candidates to the job seeker.

[0082] The candidate extraction unit 115 displays, for example, some of the candidate's registration information (for example, items such as the name of the organization they currently work for, their job title, duties, position, age, current annual income, educational background, skills, and qualifications) on the recruiter terminal 20. The candidate extraction unit 115 may also display the candidate's information on the recruiter terminal 20 in a format that does not identify the candidate personally (for example, with information such as their name masked).

[0083] For example, the candidate extraction unit 115 may input candidate registration information and a prompt including instructions to create candidate information in which the candidate is not personally identified to a general-purpose learning model, causing the candidate information creation model to output candidate information in which the candidate is not personally identified, and then display the candidate information on the recruiter terminal 20.

[0084] The candidate extraction unit 115 may display the corresponding candidate information (list) on the employer terminal 20 alongside the job information acquired by the job information acquisition unit 113.

[0085] The candidate extraction unit 115 may extract candidates based on the degree of match between the job information and the registered information of job seekers. The candidate extraction unit 115 may also display the degree of match of the extracted candidates as candidate information on the employer terminal 20. This allows the employer to select candidate information to be used in the job editing unit 116, described later, based on the degree of match.

[0086] "Matching degree" is an index (numerical value) that indicates, for example, the proportion of job seekers who meet the requirements included in the job posting. The matching degree is calculated, for example, based on the difference in features between the job posting and the job seeker's registration information (for example, the distance between vectors obtained by vectorizing words or sentences). The candidate extraction unit 115 calculates the matching degree of job seekers to the job posting based, for example, on the difference in features between the job posting and the job seeker's registration information (for example, cosine similarity, which is the distance between two vectors). For example, the smaller the difference in features (the larger the cosine similarity), the higher the matching degree index. Alternatively, the features of the job posting, etc., may be calculated by referring to a table that defines features for each keyword.

[0087] The degree of match may be calculated by comparing specific requirements in the job posting with items in the job seeker's registration information that correspond to those requirements. For example, the candidate selection unit 115 may calculate the degree of match based on the difference between the job seeker's current or desired annual salary and the annual salary in the job posting (for example, the increase in current annual salary).

[0088] Furthermore, the candidate extraction unit 115 may input the combination of job information and job seeker registration information into a match degree calculation model and have the match degree calculation model output a match degree. The match degree calculation model is, for example, a machine learning model included in the artificial intelligence unit 120 that is capable of taking the combination of job information and job seeker registration information as input and outputting a match degree, or a general-purpose machine learning model.

[0089] The candidate selection unit 115 may, for example, select job seekers as candidates whose match rate is above a predetermined threshold (e.g., 80% or higher). Alternatively, the candidate selection unit 115 may, for example, select job seekers as candidates whose rank is above a predetermined level (e.g., 10th place or higher) when multiple job seekers are ranked in descending order of their match rate.

[0090] The degree of match may be displayed on the recruiter terminal 20 as a numerical value (for example, "XX%"), or it may be displayed on the recruiter terminal 20 in the form of a graph showing the magnitude of the degree of match, or a rank corresponding to the degree of match (for example, "Match Level A").

[0091] The candidate extraction unit 115 may extract candidates by combining a search based on search criteria with a degree of match. For example, the candidate extraction unit 115 may extract as candidates job seekers whose degree of match is equal to or greater than a predetermined threshold from among the job seekers found using the search criteria.

[0092] The candidate extraction unit 115 may display a candidate list on the recruiter terminal 20, sorted by the degree of match (candidates with a higher degree of match appear higher in the list).

[0093] The candidate extraction unit 115 may, after presenting candidates, accept input of filtering conditions for the presented candidates or changes to the candidate extraction conditions from the recruiter terminal 20. This allows recruiters to filter or re-extract candidates whose registered information is used for editing job postings based on arbitrary conditions.

[0094] "Refinement criteria" are conditions used to narrow down the candidates displayed on the recruiter terminal 20 from the extracted candidates. Refinement criteria include, for example, keywords included in the registration information, candidate IDs, and conditions for each item (e.g., age, annual income, address, industry, job type, skills, qualifications, etc.).

[0095] The "candidate extraction criteria" are the conditions for extracting job seekers registered in the job seeker database as candidates. Candidate extraction criteria include, for example, the threshold for the degree of match used to extract candidates, and the range of requirements (items) used to calculate the degree of match. If, for example, the candidates displayed on the recruiter terminal 20 are not suitable, or if the number of candidates presented is small, the recruiter will input a change to the extraction criteria (for example, an instruction to "expand the search range") from the recruiter terminal 20. When the recruiter terminal 20 receives a change to the candidate extraction criteria, the candidate extraction unit 115 re-extracts candidates based on the changed extraction criteria and displays them on the recruiter terminal 20.

[0096] The candidate extraction unit 115 receives input of evaluations for the extracted candidates from the recruiter terminal 20 and may further present to the recruiter as candidates who are similar to candidates with evaluations above a certain level. This allows the recruiter to present additional candidates who are useful for editing the job information according to their own evaluation, thereby improving the efficiency of editing the job information and the quality of the job information.

[0097] The "evaluation" of a candidate received by the candidate selection unit 115 may be a numerical value, or it may be selected from a set of options including, for example, "good" (high evaluation) or "bad" (low evaluation). For example, the candidate selection unit 115 may consider a candidate who has been given a "good" evaluation as a "candidate whose evaluation is above a predetermined level."

[0098] "Job seekers similar to candidates" are determined, for example, by the difference in feature quantities between the registered information, similar to the degree of match described above. The candidate extraction unit 115 calculates the similarity between the two based on the difference in feature quantities (for example, cosine similarity, which is the distance between two vectors) between the registered information of a candidate highly rated by the employer and the registered information of other job seekers in the job seeker database, and determines that job seekers whose similarity is above a threshold are additional candidates.

[0099] The candidate extraction unit 115 accepts input of evaluations for the extracted candidates from the recruiter terminal 20 and may exclude job seekers who are similar to candidates with evaluations below a predetermined level. For example, the candidate extraction unit 115 may consider a candidate with a "bad" evaluation as a "candidate with an evaluation below a predetermined level" and may not display candidates similar to such candidates on the recruiter terminal 20. Furthermore, the candidate extraction unit 115 may re-extract candidates based on a first similarity with candidates with an evaluation above a predetermined level (for example, candidates with a "good" evaluation) and a second similarity with candidates with an evaluation below a predetermined level (for example, candidates with a "bad" evaluation). For example, the candidate extraction unit 115 may not extract job seekers who have a high first similarity (similar to highly-rated candidates) but also a high second similarity (similar to low-rated candidates).

[0100] Figure 7 shows an example of how candidate information is displayed in the extraction results display area EA of the job posting editing screen ED. The extraction results display area EA in Figure 7 is displayed, for example, when an input operation is performed on the display reception object IO in the extraction results display area EA of Figure 6. In the extraction results display area EA of Figure 7, the filter setting area FA and multiple candidate information CIs are displayed.

[0101] The Candidate Information CI includes some of the candidate's registration information (in the example in Figure 7, current organization, job title, age, current annual salary, education level, and skills). The Candidate Information CI also includes the Match MD, the first evaluation submission object VO1, and the second evaluation submission object VO2.

[0102] The first evaluation receiving object VO1 is an object that accepts input for high ratings ("good"). The second evaluation receiving object VO2 is an object that accepts input for low ratings ("bad"). When an input operation is performed on either the first evaluation receiving object VO1 or the second evaluation receiving object VO2, the display of the first evaluation receiving object VO1 or the second evaluation receiving object VO2 changes to a form indicating that input has been completed, and the evaluation for the corresponding candidate is accepted.

[0103] In the filter setting area FA, when filtering conditions (age and free word in the example in Figure 7) are entered, only candidate information CI that meets those filtering conditions will be displayed in the extraction result display area EA.

[0104] Figure 8 shows an example of the state in which additional candidate information is displayed in the extraction result display area EA of the job information editing screen ED. The extraction result display area EA in Figure 8 is displayed, for example, when a predetermined number of candidate information CIs are entered into the first evaluation reception object VO1 in the extraction result display area EA of Figure 7.

[0105] In the extraction results display area EA of Figure 8, candidate information CIs that have been input to the first evaluation reception object VO1 (i.e., those that have received a high evaluation) and additional candidate information ACIs that are similar to these candidate information CIs are displayed. Note that in the example of Figure 8, the display form of the first evaluation reception object VO1 that received the input has changed from a white symbol to a black symbol.

[0106] <Recruitment Editorial Department 116> The job posting editing unit 116 is configured to accept the selection of citation ranges in the candidate's registration information from the job posting terminal 20 and add the content based on the citation ranges to the job posting information.

[0107] Specifically, first, the job posting editing unit 116 accepts the candidate selection from the employer for the candidate presented by the candidate selection unit 115, and displays the registration information of the selected candidate on the employer terminal 20. At this time, the job posting editing unit 116 may also display the candidate's registration information on the employer terminal 20 alongside the job information acquired by the job information acquisition unit 113. In addition, the job posting editing unit 116 may display on the employer terminal 20 only the information included in the registration information that the employer has permission to view (for example, all information except information that can identify an individual).

[0108] The job posting editor 116 may provide employers with sections of a candidate's registration information that are suitable for addition to the job posting (hereinafter referred to as "recommended sections for addition"). This will improve the efficiency of the employer's job posting editing work and the quality of the edited job posting.

[0109] The job posting editorial department 116 may, for example, display the recommended additional sections (keywords or sentences) in a different manner from other text in the candidate's registration information on the job seeker terminal 20 by highlighting them (for example, by coloring, adding decorations, changing the font, or enclosing them in a frame).

[0110] The job posting editing department 116 may determine recommended additions based on the differences between the candidate registration information (the registration information displayed on the employer terminal 20) and the job posting information. For example, the job posting editing department 116 may determine keywords or sentences that are not included in the job posting information but are included in the registration information as recommended additions. The job posting editing department 116 may also determine keywords or sentences that are common to the registration information of multiple candidates as recommended additions. Furthermore, the job posting editing department 116 may determine recommended additions (locations that contain content that can be modified as included in the modification proposal) based on the modification proposal created by the modification proposal department 114.

[0111] After displaying the candidate's registration information, the job posting editing department 116 accepts requests from the job seeker's terminal 20 to select the scope of the citation to be added to the job posting based on the displayed registration information.

[0112] The "quoted area" is defined as a keyword or a sentence. The unit for selecting the quoted area can be set as, for example, a keyword, a sentence, a paragraph, or an item.

[0113] The recruitment editorial department 116 may use a general-purpose learning model to determine which items in the recruitment information to which content based on the quoted scope should be added, or which items to which content based on the quoted scope should be added, based on the content of the quoted scope (for example, specific keywords included in the quoted scope) or the location (item, etc.) in the registration information where the quoted scope has been selected, and may add the content based on the quoted scope to the applicable item. For example, the recruitment editorial department 116 may add a quoted scope containing text related to work experience, or a quoted scope selected from the work experience item in the registration information, to the work experience item (requirement) in the recruitment information.

[0114] The job posting editing department 116 may further accept selections of applicable items in the job posting information from the job seeker terminal 20 and add content based on the quoted range to the selected applicable items. This allows job seekers to edit the job posting information by combining any quoted range with any item, thereby increasing the degree of freedom in editing the job posting information.

[0115] The job posting editor 116 may, for example, accept the selection of applicable items in response to input operations into a selection acceptance object provided for each applicable item. Alternatively, the job posting editor 116 may accept the selection of applicable items by moving an object that indicates the content of the quoted range to be added. In this case, the item at the destination of the object (for example, the destination of drag and drop) will be selected as the applicable item. Note that the selection of applicable items is not mandatory, and the job posting editor 116 may determine the applicable items (items or locations to which content based on the quoted range will be added, etc.) as described above.

[0116] The job posting editing department 116 may accept multiple citation range selections from the job seeker terminal 20 for a single selected application item, and add content based on multiple citation ranges to that application item. This allows multiple citation ranges to be combined and applied to any item in the job posting information, further increasing the editing flexibility of the job posting information.

[0117] When accepting the selection of applicable items from the recruiter terminal 20, the job posting editorial department 116 may accept the selection of applicable items and then accept the selection of the citation range that contains the content to be added to said applicable items, or it may accept the selection of the citation range and then accept the selection of applicable items to which the content of said citation range will be added, or it may accept these selections in any order.

[0118] The job posting editing unit 116 may accept the selection of multiple citation ranges from the job seeker terminal 20, and further accept the selection of application items to which each of the multiple citation ranges should be added from the job seeker terminal 20, and add the content based on the corresponding citation range to the selected application items. This allows, for example, multiple citation ranges to be extracted and then the job posting information items to which each citation range should be applied, so that job seekers can edit job posting information in any procedure they choose.

[0119] The job posting editing department 116 may, for example, sequentially add the quoted ranges selected in the candidate's registration information to the stock area of ​​quoted ranges displayed on the recruiter's terminal 20, and add the content of the quoted ranges to the job posting information based on the addition operation of the quoted ranges stocked in the stock area (for example, input operation to the add acceptance object prepared for each quoted range, drag operation to the application item of the object that indicates the content of the quoted range, etc.). The stock area is a display area prepared separately from the display area of ​​the candidate's registration information and the display area of ​​the job posting information, and for example, multiple quoted ranges selected by the recruiter are displayed in the stock area. The job posting editing department 116 may accept changes to the display order of multiple quoted ranges, selection of quoted ranges to add to one application item, deletion of quoted ranges (deselection), etc., in the stock area.

[0120] Furthermore, the job posting editorial department 116 may accept an operation (for example, a drag-and-drop operation) to directly move the quoted range from the registration information displayed on the job seeker terminal 20 to the applicable item of the job information displayed on the job seeker terminal 20, and add the contents of the quoted range to the applicable item.

[0121] If the candidate selection unit 115 presents multiple candidates to the employer, the job editing unit 116 may accept the selection of any candidate from among the multiple candidates and the selection of citation ranges in the registration information of the selected candidates, and add content based on the multiple citation ranges selected in the registration information of the multiple candidates to the job information. This makes it possible to extract arbitrary content from the registration information of multiple candidates and combine them to add to the job information.

[0122] The job posting editing department 116 may, for example, display the registration information of each candidate on the recruiter terminal 20 one by one and sequentially add the selected citation range in the registration information to the stock area, or it may display the registration information of multiple candidates on the recruiter terminal 20 simultaneously and accept the selection of citation ranges for each registration information.

[0123] The job posting editor 116 may input the text included in the quoted range (hereinafter referred to as "quoted text") into a text editing model, have the text editing model output insertable text that has been modified to suit the job posting, and then add the insertable text to the job posting. This reduces the effort required of the job seeker to modify the content of the quoted range to match the job posting, thereby improving the efficiency of editing the job posting.

[0124] The text correction model is a machine learning model or general-purpose machine learning model that takes quoted text as input and outputs insert text. The text correction model is included in the artificial intelligence unit 120. A text correction model trained to output insert text is trained, for example, using data of quoted text and data of corresponding insert text as training data.

[0125] If the text editing model is a general-purpose learning model (for example, a language model such as a large-scale language model, a generative AI, etc.), the job editing department 116 inputs a prompt to the text editing model that includes a quoted text and an instruction to output an insert text corresponding to the quoted text as input, causing the text editing model to output the insert text. The job editing department 116 may also generate a prompt that gives the text editing model an instruction to create an insert text and input this prompt to the text editing model. In addition to the instructions to create and output the quoted text and the insert text, the job editing department 116 may also input a prompt to the text editing model that includes, for example, one or more sample quoted texts and one or more sample insert texts corresponding to them, as examples, samples, or training data of input and output pairs.

[0126] The job posting editor 116 may, for example, create insert text from quoted text when a quoted range is selected, create insert text when a quoted range is added to the stock area, create insert text when instructions (input operation of instructions to create insert text) are received from the job seeker while a quoted range is stocked in the stock area, create insert text when a quoted range and applicable items are selected, or create insert text when adding the content contained in the quoted range to the job posting information.

[0127] When insert text is created when a quoted range is added to the stock area, the insert text is displayed in the stock area. Alternatively, when insert text is created with a quoted range and applicable items selected, the job posting editing department 116 may, for example, input the combination of the quoted text and applicable items into the text modification model, and have the text modification model output the insert text modified to suit the applicable items.

[0128] The recruitment editorial department 116 may decide whether or not to create insert text depending on the content of the quoted text. For example, if the recruitment editorial department 116 determines that the quoted text can be inserted directly into the job information (is appropriate as job information content), it may not create insert text. On the other hand, if it determines that the quoted text cannot be inserted directly into the job information (is inappropriate as job information content), it may create insert text.

[0129] The job posting editor 116 may display the text to be inserted on the job seeker terminal 20 before adding it to the job posting information. For example, the job posting editor 116 may display the text to be inserted in the stock area where the quoted range is stored. The job posting editor 116 may also display information (such as a symbol) for each quoted range displayed in the stock area indicating whether or not the text to be inserted has been created (i.e., whether the original quoted text has been modified).

[0130] The job posting editing department 116 may accept edits of text or keywords included in the selected quoted range from the job seeker terminal 20 and add the edited text or keywords from the quoted range to the job posting. This allows for the addition of content requested by the job seeker to the job posting while making use of text or keywords included in the candidate's registration information.

[0131] "Editing" includes, for example, adding, replacing, and deleting. The job posting editing department 116 may, for example, accept edits to text or keywords when a quoted range is selected, when a quoted range is added to the stock area, when a quoted range and applicable items are selected, or after the text or keywords contained in the quoted range have been inserted into the job posting information.

[0132] The recruitment editorial department 116 may accept edits to the inserted text that has been modified from the quoted text. Furthermore, if the recruitment editorial department 116 accepts edits to the inserted text, it may remove the display of information indicating that the inserted text has been created, which is displayed for the quoted range in which the inserted text has been edited.

[0133] Figure 9 shows an example of the job posting editing screen ED with the registration information display area RA displayed. The registration information display area RA in Figure 9 is displayed, for example, when an input operation is performed on any of the candidate information CIs in the extraction result display area EA in Figure 7. The job posting editing screen ED in Figure 9 includes the job posting display area JA and the registration information display area RA. The job posting display area JA is the same as the job posting display area JA in Figure 6. However, in the job posting display area JA in Figure 9, the edit acceptance object EO is displayed for each requirement RM.

[0134] The registration information display area RA is located next to the job information display area JF (to the right of the job information display area JF in the example of Figure 9). Specifically, the registration information display area RA is displayed in the area where the extraction result display area EA in Figures 6 and 7 was displayed. The registration information display area RA displays the registration information of the candidate selected by the employer, item by item. The registration information display area RA also includes the close object CO, the first evaluation acceptance object VO1, and the second evaluation acceptance object VO2. When an input operation is performed on the close object CO, the registration information display area RA is closed, and the extraction result display area EA in Figure 7 is displayed again on the job information editing screen ED. The first evaluation acceptance object VO1 and the second evaluation acceptance object VO2 have the same functions as the first evaluation acceptance object VO1 and the second evaluation acceptance object VO2 in Figure 7.

[0135] Figure 10 shows an example of a state where the citation range CR is selected in the registration information display area RA. In the example in Figure 10, three sentences included in the "Work History" section of the candidate's registration information displayed in the registration information display area RA have been selected as the citation range CR by the recruiter's selection operation (for example, text selection by dragging). In the registration information display area RA, the citation range CR is highlighted (framed and shaded in Figure 10) compared to the rest of the registration information.

[0136] In the job posting editing screen ED of Figure 10, the job posting display area JA shows the additional content display area AF and the reflect button B31 below the job posting display area JF. In the job posting display area JF, "Job Description" is selected as the item to be edited (applicable item) in the job posting, and the content of this item is displayed in edit mode (enclosed in a frame). The selection of applicable items is performed by inputting an operation into the editable object EO assigned to each item.

[0137] The Additional Content Display Area AF is a stock area for citation ranges CR, where the Additional Content AC, which is the content of the citation range CR selected in the registration information display area RA, is displayed. In the Additional Content Display Area AF, the Additional Content AC (text or keywords) is displayed for each citation range CR, and furthermore, the Move Acceptance Object MO, the Citation Range Edit Acceptance Object CEO, and the Citation Range Deletion Object CCO are displayed for each Additional Content AC. In addition, in the Additional Content Display Area AF, the text included in the citation range CR has been modified by the text modification model (i.e., the inserted text displayed in the Additional Content Display Area AF is different from the original text included in the registration information display area RA) is marked with a modified mark FM.

[0138] The movement acceptance object MO accepts the movement of additional content AC within the additional content display area AF by a combination of selection, drag, and drop operations performed by the recruiter. By moving additional content AC within the additional content display area AF, the display order (position) of additional content AC within the additional content display area AF can be changed. The movement acceptance object MO may also accept the movement of additional content AC to the job information display area JF. For example, additional content AC may be inserted into the job information display area JF by a drag-and-drop operation.

[0139] The Citation Range Editing Acceptance Object CEO accepts edits to the Additional Content AC. When an input operation is performed on the Citation Range Editing Acceptance Object CEO, the corresponding Additional Content AC switches to edit mode. The Citation Range Deletion Object CCO accepts deletions of Additional Content AC (cancellation of Citation Range CR). When an input operation is performed on the Citation Range Deletion Object CCO, the corresponding Additional Content AC is removed from the Additional Content Display Field AF. In addition, the display of the corresponding Citation Range CR in the Registration Information Display Area RA is canceled.

[0140] When an input operation is performed on the Reflect button B31, one or more additional content ACs included in the additional content display field AF (i.e., all additional content ACs displayed in the additional content display field AF) are added to the selection item (in the example in Figure 10, "Job Description") (details will be described later).

[0141] Figure 11 shows an example of the state in which editing of additional content AC is performed in the additional content display field AF. In the additional content display field AF of Figure 11, for example, when an input operation is performed on the citation range editing acceptance object CEO of the top additional content AC in the additional content display field AF of Figure 10, the additional content AC is shown to have entered editing mode (a state in which it accepts editing by text input from job seekers). In addition, in the additional content AC that is in editing mode, the citation range editing decision object CDO is displayed instead of the citation range editing acceptance object CEO.

[0142] When an input operation is performed on the Citation Range Editing Determination Object CDO, the edited content for the Additional Content AC is finalized, and the edited Additional Content AC is displayed in the Additional Content Display Field AF. Furthermore, if the edited Additional Content AC had a modified mark FM (i.e., if the Additional Content AC was an insertable text created by the text modification model), the modified mark FM will no longer be displayed after the edit is finalized.

[0143] Figure 12 shows an example of the state in the job information display area JF where the content of the quoted range CR (additional content AC) has been added. The job information display area JF in Figure 12 is displayed, for example, after input is made to the reflect button B31 in Figure 10 or Figure 11.

[0144] In the example in Figure 12, the additional content AC, which was displayed in the additional content display field AF in Figure 10 or Figure 11, has been inserted into the "Job Description" field, which is the applicable item (and is in edit mode). The additional content AC is displayed in a format that is distinguishable from the content originally written in the applicable item (in italics in Figure 12).

[0145] If the additional content display field AF contains multiple additional content ACs, all additional content ACs will be inserted in the order they appear in the additional content display field AF (i.e., from top to bottom). The additional content display field AF may also allow employers to select additional content ACs to add to the applicable items.

[0146] In the job posting display area JF, the Edit Confirmation Object DO is displayed for applicable items that have been edited (addition of additional content AC). When an input operation is performed on the Edit Confirmation Object DO, the edited content for the applicable item is confirmed, and the edited content is displayed in the job posting display area JF. Note that for applicable items, text or sentences can be edited both before and after the addition of additional content AC.

[0147] The job posting editing unit 116 may display the number of job seekers who meet the requirements of the current job posting on the job seeker terminal 20 while editing the job posting. This allows the job seeker to edit the job posting while confirming its effectiveness (the range of job seekers that can be reached).

[0148] The job posting editorial department 116, for example, searches the job seeker database using the requirements of the job posting as search criteria, and presents the number of job seekers found (hits) along with the content of the current job posting to the employer. The job posting editorial department 116 may also perform a job seeker search when, for example, the employer updates at least part of the job posting, or when content based on the scope of citations in the candidate's registration information is added to (reflected) in the job posting, or it may perform a job seeker search upon instruction from the employer.

[0149] If a job posting contains multiple requirements of different priorities, the job posting editor 116 may display the number of job seekers who meet each priority requirement on the employer terminal 20. This allows for modifications to the job posting requirements according to priority, thereby improving the efficiency of job posting modifications.

[0150] For example, the job posting editor 116 displays the number of job seekers who meet the mandatory requirements (or both mandatory and preferred requirements) and the number of job seekers who meet the preferred requirements (requirements with a higher priority than the mandatory requirements). Alternatively, the job posting editor 116 may display the number of job seekers who meet the comprehensive requirements, which include all the requirements of the job posting.

[0151] Figure 13 shows an example of the state in which the search results SR are displayed in the job information display area JA. In the job information display area JA of Figure 13, the search results SR are displayed below the additional content display area AF of Figure 10.

[0152] The search results SR includes the number of job seekers who meet the requirements of the current job posting (the requirements displayed in the job posting display section JF). In the example in Figure 13, the search results SR displays the number of job seekers who meet all the requirements of the job posting, the number of job seekers who meet the preferred requirements ("WANT Job Seekers"), and the number of job seekers who meet the mandatory requirements ("MUST Job Seekers").

[0153] <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.

[0154] The artificial intelligence unit 120 may be an AI (Artificial Intelligence) equipped with pre-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 (RNNs). 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 models provided by services such as OpenAI's GPT, Google's Gemini, and Microsoft's Azure AI Studio. Generative AI may be, for example, text generation AI, image generation AI, or multimodal generation AI. The pre-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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] The pre-trained models included in the artificial intelligence unit 120 (such as the job posting creation model, which are 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.

[0159] 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 relative to the teacher model's output (Soft Target Loss) 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 relative to the correct labels (Hard Target) of the teacher data (combinations of input and output data of the training model) is small. Compared to the original training 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.

[0160] 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.

[0161] An AI agent (also called an autonomous agent) is a model that, upon input of a goal (objective, purpose, etc.) such as "Teach me about XX" or a task such as "Output XX," breaks down the processes necessary to reach the goal or accomplish the task into subtasks, actions, etc., and performs necessary data collection and analysis, program generation and execution, etc. The AI ​​agent takes the information and instructions input by the user as its goal, autonomously selects and executes tasks and actions according to the goal, outputs information according to the goal, and does not require user intervention (operation input). Furthermore, the AI ​​agent may autonomously plan and execute, evaluate the execution results itself, and autonomously learn in order to aim for the achievement of the goal. 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.).

[0162] <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.

[0163] <Operation acquisition part> 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.

[0164] 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.

[0165] The above-described information processing method comprises a job posting creation step, a job posting acquisition step, a revision proposal step, a candidate extraction step, and a job posting editing step. In the job posting creation step, initial information containing at least keywords related to the job posting is accepted, and job postings are created based on this initial information and first reference information. In the job posting acquisition step, job postings containing at least the requirements for the job posting are acquired. In the revision proposal step, revision proposals for items included in the job posting are created based on the job posting and second reference information, and the created revision proposals are displayed in association with the items. In the candidate extraction step, suitable candidates for the job posting are extracted from job seekers registered in the database based on the job postings, and the extracted candidates are presented. In the job posting editing step, the selection of citation ranges in the candidate's registration information is accepted, and content based on the citation ranges is added to the job postings.

[0166] Figure 14 is an activity diagram showing an example of the flow of information processing (job posting creation process) performed by Information Processing System 1. The information processing will be explained below in accordance with each activity in this activity diagram.

[0167] The job posting creation process begins with the employer entering initial information. The employer enters the initial information that will serve as the source for the job posting on the employer terminal 20 (Activity A101). The server device 10 creates the job posting based on the initial information entered from the employer terminal 20 (Activity A102). Next, the server device 10 creates revision suggestions for the created job posting (Activity A103). Furthermore, the server device 10 extracts candidates from the job seeker database based on the job posting (Activity A104). Note that the order of creating revision suggestions and extracting candidates does not matter, and the candidate extraction process may be performed before the revision suggestion creation process.

[0168] Next, the server device 10 outputs the job information, proposed revisions, and candidate information to the employer terminal 20 (Activity A105). As a result, the job information and proposed revisions are displayed on the employer terminal 20, and candidates are presented (Activity A106). The employer selects a citation range for the presented candidate's registration information on the employer terminal 20 (Activity A107). The server device 10 adds the content based on the citation range selected on the employer terminal 20 to the job information (Activity A108).

[0169] 4. Effect The function of this embodiment can be summarized as follows: In other words, recruiters can create job postings using data tailored to their purpose. For example, when a headhunter is negotiating with a recruiting company, they can use the information processing system 1 to check the registration information of actual candidates and edit the job postings, thereby efficiently coordinating the job details and hiring requirements with the recruiting company.

[0170] 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.

[0171] 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 configuration 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 language model as a learning model, or a server that executes language processing tasks using a language model. 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.

[0172] 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.

[0173] 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.

[0174] The control unit 11 does not necessarily have to include a job information creation unit 112. In other words, the information processing system 1 does not have to have a job information creation function. Also, the control unit 11 does not necessarily have to include a revision suggestion unit 114. In other words, the information processing system 1 does not have to have a job information revision suggestion function.

[0175] The product may be provided in any of the following embodiments.

[0176] (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 information processing system comprising: a job information acquisition step, which acquires job information that includes at least the requirements of the job; a candidate extraction step, which extracts candidates suitable for the job from among job seekers registered in a database based on the job information, and presents the extracted candidates; and a job editing step, which accepts the selection of a citation range in the candidate's registration information, and adds the content based on the citation range to the job information.

[0177] (2) An information processing system as described in (1) above, wherein in the job editing step, the system further accepts the selection of applicable items in the job information and adds the content based on the citation scope to the applicable items.

[0178] (3) In the information processing system described in (2) above, the job posting editing step accepts the selection of multiple citation ranges for one selected application item and adds the content based on the multiple citation ranges to the application item.

[0179] (4) An information processing system as described in (2) or (3) above, wherein the job posting editing step accepts the selection of a plurality of citation ranges, further accepts the selection of an application item to which each of the plurality of citation ranges is to be added, and adds the content based on the corresponding citation range to the selected application item.

[0180] (5) An information processing system according to any one of (1) to (3) above, wherein in the candidate extraction step, a plurality of the above candidates are extracted, and the plurality of the extracted candidates are presented; in the job editing step, the selection of any of the plurality of the above candidates and the selection of the above citation range in the registration information of the selected candidate are accepted, and the content based on the plurality of above citation ranges selected in the registration information of the plurality of the above candidates is added to the job information.

[0181] (6) An information processing system according to any one of (1) to (5) above, wherein in the job information creation step, the system accepts input of initial information that includes at least keywords relating to the job, and creates the job information based on the initial information and first reference information, where the first reference information is information relating to the correlation between the initial information and the job information, and in the job information acquisition step, the system acquires the job information created based on the initial information.

[0182] (7) An information processing system as described in (6) above, wherein in the job information creation step, the job information is created based on the initial information, similar job information which includes at least the requirements of similar job postings, and the first reference information, wherein the similar job postings are other job postings similar to the job postings that are registered in the database, and the first reference information is information relating to the correlation between the combination of the initial information and the similar job information and the job information.

[0183] (8) An information processing system described in any one of (1) to (7) above, wherein in the revision proposal step, revision proposals are created for items included in the job information based on the job information and second reference information, and the created revision proposals are displayed in association with the items, and the second reference information is information relating to the correlation between the job information and the revision proposals.

[0184] (9) Information processing system as described in (8) above, wherein the modification proposal step creates the modification proposal based on the job information, similar job information which includes at least the requirements of similar job postings, and the second reference information, wherein the similar job postings are other job postings similar to the job postings registered in the database, and the second reference information is information relating to the correlation between the combination of the job information and the similar job information and the modification proposal.

[0185] (10) An information processing system according to any one of (1) to (9) above, wherein in the job posting editing step, the text included in the quoted range is input to a text editing model, the text editing model outputs an insertable text which is the text modified to be suitable for the job posting, the insertable text is added to the job posting, and the text editing model is a machine learning model or a general-purpose machine learning model which is capable of taking the text as input and outputting the insertable text.

[0186] (11) An information processing system according to any one of (1) to (10) above, wherein in the job editing step, the information processing system presents a suitable section in the candidate's registration information to be added to the job information.

[0187] (12) An information processing system according to any one of (1) to (11) above, wherein the job posting editing step accepts editing of the selected text or keywords contained in the quoted range, and adds the edited text or keywords of the quoted range to the job posting information.

[0188] (13) An information processing system according to any one of (1) to (12) above, wherein in the candidate extraction step, the system extracts candidates based on the degree of match between the job information and the registered information of the job seeker, and displays the degree of match of the extracted candidates.

[0189] (14) An information processing system according to any one of (1) to (13) above, wherein in the candidate extraction step, after the candidates are presented, the system accepts input of narrowing conditions for the presented candidates or changes to the candidate extraction conditions.

[0190] (15) An information processing system according to any one of (1) to (14) above, wherein in the candidate extraction step, the system accepts input of an evaluation for the extracted candidate and further presents as candidates the job seeker who is similar to the candidate and whose evaluation is above a predetermined level.

[0191] (16) An information processing system described in any one of (1) to (15) above, wherein the job posting editing step displays the number of job seekers who meet the requirements of the current job posting.

[0192] (17) An information processing system as described in (16) above, wherein the job information includes a plurality of requirements with different priorities, and the job editing step displays the number of job seekers who meet the requirements for each priority level.

[0193] (18) An information processing system according to any one of (1) to (17) above, comprising a server device having the processor and a terminal that can access the server device.

[0194] (19) An information processing method wherein an information processing device performs each step of the information processing system described in any one of (1) to (18) above.

[0195] (20) A program that causes a computer to perform each step of the information processing system described in any one of (1) to (18) above. Of course, this is not always the case.

[0196] 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]

[0197] 1: Information Processing System 10: Server device 11: Control Unit 111: Basic Display Control Unit 112: Job Information Creation Department 113: Recruitment information acquisition department 114: Revision proposal department 115: Candidate extraction department 116: Recruitment Editorial Department 120: Artificial Intelligence Department 12: Storage section 13: Communications Department 14: Communications bus 2: Communication lines 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 AC:Additional contents ACI: Additional Candidate Information AF: Additional content display field B11: File selection button B12: Send button B21: Cancel button B22: Confirm button B31: Apply button CCO: Object for removing quoted range CDO: Citation Range Editing Determination Object CEO: Quote editing accepted object CI: Candidate Information CO: Closed Object CR: Citation scope DO: Edit decision object EA: Extraction result display area ED: Job posting editing screen EI:Company information EO: Editable Object FA: Filter setting area FF: File upload section FI: File Information FM: Corrected mark ID: Initial Information Input Screen IM:Item IO: Display Reception Object JA:Job information display area JF: Job information display field MD: Matching degree MO: Movement acceptance object RA: Registration Information Display Area RM: Requirements RS: Revision suggestion SF: Additional Information Input Field SR: Search Results VO1: First evaluation submission object VO2: Second evaluation submission object

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 job information acquisition step, we acquire job information that includes at least the job requirements. In the candidate selection step, candidates suitable for the job are extracted from the job seekers registered in the database based on the job information, and the registration information of the extracted candidates is presented. An information processing system that, in the job posting editing step, accepts the selection of a citation range in the registration information, adds additional content based on the citation range to the job posting, wherein the additional content is text or keywords included in the citation range, or text or keywords created based on text or keywords included in the citation range.

2. In the information processing system described in claim 1, An information processing system that, in the job editing step, further accepts the selection of applicable items in the job information and adds the additional content to the applicable items.

3. In the information processing system described in claim 2, An information processing system that, in the job editing step, accepts the selection of multiple citation ranges for one selected application item and adds the additional content based on the multiple citation ranges to the application item.

4. In the information processing system described in claim 2, An information processing system that, in the job posting editing step, accepts the selection of multiple citation ranges, further accepts the selection of application items to which each of the multiple citation ranges will be added, and adds the additional content based on the corresponding citation range to the selected application items.

5. In the information processing system described in claim 1, In the candidate extraction step, a plurality of candidates are extracted, and the extracted plurality of candidates are presented. An information processing system that, in the job editing step, accepts the selection of any candidate from among multiple candidates and the selection of the citation range in the registration information of the selected candidate, and adds the additional content based on the multiple citation ranges selected in the registration information of the multiple candidates to the job information.

6. In the information processing system described in claim 1, The aforementioned processor is configured to perform the following steps: In the job posting creation step, initial information containing at least keywords related to the job posting is accepted as input, this initial information is input into the job posting creation model, and the job posting creation model is made to output the job posting. Here, the job posting creation model is a machine learning model or a general-purpose machine learning model that is capable of taking the initial information as input and outputting the job posting. The information processing system acquires the job information created based on the initial information in the job information acquisition step.

7. In the information processing system described in claim 6, In the job posting creation step, the initial information and similar job postings that include at least the requirements of similar job postings are input into the job posting creation model, and the job posting creation model is made to output the job posting, where the similar job postings are other job postings similar to the job posting that are registered in the database. The job posting creation model is an information processing system that is a machine learning model or a general-purpose machine learning model capable of taking a combination of the initial information and the similar job postings as input and outputting the job postings.

8. In the information processing system described in claim 1, The aforementioned processor is configured to perform the following steps: In the revision proposal step, the job information is input into the revision proposal model, the revision proposal model outputs revision proposals for the items included in the job information, and the revision proposals are displayed linked to the respective items. The aforementioned revision proposal model is an information processing system that is a machine learning model or a general-purpose machine learning model capable of taking the job information as input and outputting the revision proposal.

9. In the information processing system described in claim 8, In the aforementioned revision proposal step, the job information and similar job information that includes at least the requirements of similar job postings are input to the revision proposal model, and the revision proposal model is made to output the revision proposal, where the similar job postings are other job postings similar to the job postings that are registered in the database. The aforementioned modification suggestion model is an information processing system that is a machine learning model or a general-purpose machine learning model capable of taking a combination of the job information and the similar job information as input and outputting the modification suggestion.

10. In the information processing system described in claim 1, In the job posting editing step, the text included in the quoted range is input into the text editing model, the text editing model outputs insertable text modified to suit the job posting, and the insertable text is added to the job posting. The aforementioned text correction model is an information processing system that is a machine learning model or a general-purpose machine learning model capable of taking the aforementioned text as input and outputting the aforementioned text for insertion.

11. In the information processing system described in claim 1, An information processing system that, in the job posting editing step, determines the parts of the candidate's registration information that are suitable for addition to the job posting, based on the difference between the candidate's registration information and the job posting, or the content common to the registration information of multiple candidates, and presents the determined parts.

12. In the information processing system described in claim 1, An information processing system that, in the job posting editing step, accepts editing of text or keywords included in the selected citation range and adds the edited text or keywords from the citation range to the job posting information.

13. In the information processing system described in claim 1, An information processing system that, in the candidate extraction step, extracts candidates based on the degree of match between the job information and the registered information of the job seeker, and displays the degree of match for the extracted candidates.

14. In the information processing system described in claim 1, The candidate extraction step includes an information processing system that, after presenting the candidates, accepts input of filtering criteria for the presented candidates or changes to the candidate extraction criteria.

15. In the information processing system described in claim 1, An information processing system that, in the candidate extraction step, accepts input of an evaluation for the extracted candidate and further presents as candidates any job seeker who is similar to the candidate and whose evaluation is above a predetermined level.

16. In the information processing system described in claim 1, The information processing system, in the job posting editing step, displays the number of job seekers who meet the requirements of the current job posting.

17. In the information processing system described in claim 16, The aforementioned job posting includes multiple requirements with different priorities, The information processing system, in the job posting editing step, displays the number of job seekers who meet the requirements for each priority level.

18. 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.

19. Information processing method, An information processing method wherein an information processing device included in the information processing system performs each step of the information processing system described in any one of claims 1 to 17.

20. It is a program, A program for causing an information processing device included in the information processing system to perform each step of the information processing system described in any one of claims 1 to 17.

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