Job posting optimization system, job posting optimization server, program, and job posting optimization method

Abstract

Job posting optimization allows you to efficiently create job postings that can improve your hiring rate. This system provides a job posting optimization server, a program, and a job posting optimization method. [Solution] An information acquisition unit 131 that acquires information from job seekers, and the information from the job posting source A requirements extraction unit 132 extracts job requirements based on the above, and analyzes and optimizes the extracted job requirements. A requirements optimization unit 133 generates recommended job requirements, and the job requirements and the recommended job requirements A job posting editing department 134 presents the job posting to the aforementioned job seeker and accepts the editing of the job requirements, and El.

Description

Technical Field

[0001] The present invention relates to a job offer optimization system, a job offer optimization server, a program, and a job offer optimization method.

Background Art

[0002] In recent years, job matching services have played a role in efficiently connecting the needs of companies (job offerers) and job seekers. Job site operating companies are strengthening comprehensive matching support by utilizing AI (Artificial Intelligence) and digital technologies, or by expanding supplementary services such as intensive support by agents and direct scouting.

[0003] The functions required for job matching services can be broadly classified into those for the job offer side and those for the job seeker side. Among them, for the job offer side, a function to improve the efficiency of creating job offers is required. For example, in Patent Document 1, a technology is described in which a job offerer's input of the conditions of the human resources they seek is received as an input of human resource conditions, related information related to the input human resource conditions is acquired, the acquired related information is input into a first artificial intelligence, and a job offer corresponding to the human resources indicated by the related information is output.

[0004]

Prior Art Documents

Patent Documents

Patent Document 1

[0005]

Summary of the Invention

Problems to be Solved by the Invention

[0006] Furthermore, large companies tend to have accumulated know-how and achievements in recruitment activities, and The gap in the difficulty of hiring is widening between small and medium-sized enterprises (SMEs) that tend not to have such resources and those that do. There are no efficient support functions available for creating or modifying job postings for companies.

[0007] Furthermore, recruitment agencies other than the operators of job matching services possess their own unique job seeker data. By linking to databases, it is possible to expand the pool of job seekers, but this is not being utilized very often. This is not being done, resulting in lost recruitment opportunities not only for employers but also for job seekers.

[0008] Therefore, this disclosure describes a job posting optimization system that can efficiently create high-quality and uniform job postings. The objective is to provide a job posting optimization server, program, and job posting optimization method. Let's assume that. [Means for solving the problem]

[0009] The job posting optimization system according to the present invention includes an information acquisition unit that acquires job posting source information from employers. The requirements extraction unit extracts job requirements based on the aforementioned job posting source information, and the extracted job requirements A requirements optimization unit analyzes the job requirements and generates optimized recommended job requirements, and the requirements and the recommended A job posting editing department presents the job requirements to the aforementioned employers and accepts the editing of the aforementioned job requirements, It is equipped with.

[0010] The job posting optimization server according to the present invention includes an information acquisition unit that acquires job posting source information from employers, and A requirements extraction unit extracts job requirements based on the aforementioned job posting source information, and the extracted job requirements A requirements optimization unit analyzes the job requirements and generates optimized recommended job requirements, and the recommended A job posting editing department presents the job requirements to the aforementioned employer and accepts editing of the aforementioned job requirements, Prepare.

[0011] Furthermore, the program according to the present invention includes an information acquisition step that acquires job posting source information from employers. The process involves a requirements extraction step that extracts job requirements based on the aforementioned job posting source information, and the extracted pre A requirements optimization step that analyzes the job requirements and generates optimized recommended job requirements, and the said The recruiter is presented with the personnel requirements and the aforementioned recommended job requirements, and is accepted to edit the aforementioned job requirements. The computer will perform the personnel record editing step.

[0012] The job posting optimization method according to the present invention involves an information acquisition step that obtains job posting source information from the employer. The process involves a requirements extraction step that extracts job requirements based on the aforementioned job posting source information, and the extracted pre A requirements optimization step that analyzes the job requirements and generates optimized recommended job requirements, and the said The recruiter is presented with the personnel requirements and the aforementioned recommended job requirements, and is accepted to edit the aforementioned job requirements. It includes a personnel ticket editing step.

Advantages of the Invention

[0013] According to the present disclosure, a job offer optimization system capable of efficiently creating high-quality and homogeneous job offers a job offer optimization server, a program, and a job offer optimization method can be provided .

Brief Description of the Drawings

[0014] [Figure 1] It is a schematic diagram showing a job offer optimization system according to an embodiment of the present invention. [Figure 2] It is a functional block diagram of a job offer optimization server according to an embodiment of the present invention. [Figure 3] It is a diagram showing an example of information stored in a storage unit of a job offer optimization server according to an embodiment of the present invention. [Figure 4] It shows an example of an instruction sentence according to an embodiment of the present invention. [Figure 5] It is a functional block diagram of a user terminal according to an embodiment of the present invention. [Figure 6] It is a diagram showing a specific example of a screen of a job offer optimization service displayed on a user terminal according to an embodiment of the present invention. [Figure 7] It is a diagram showing a specific example of a screen of a job offer optimization service displayed on a user terminal according to an embodiment of the present invention. [Figure 8] It is a diagram showing a specific example of a screen of a job offer optimization service displayed on a user terminal according to an embodiment of the present invention. [Figure 9] It is a flowchart showing a job offer creation process by a job offer optimization system according to an embodiment of the present invention. [Figure 10] It is a flowchart showing a job offer review process by a job offer optimization system according to an embodiment of the present invention. [Figure 11] It is a block diagram showing the basic configuration of a computer.

Modes for Carrying Out the Invention

[0015] The following describes the job posting optimization system 1 according to an embodiment of the present invention, with reference to the drawings. Let me explain. In all the figures illustrating the embodiments, common components are denoted by the same reference numerals, and repeating this will be done. I will omit the explanation of the repetition.

[0016] <System Configuration> Figure 1 is a schematic diagram showing a job posting optimization system 1 according to an embodiment of the present invention.

[0017] The job posting optimization system 1 includes a job posting optimization server 100 (hereinafter simply referred to as server 100). ) and user terminal 200, generation AI 300, external database 400, internal system It includes Mu 500 and, in the example system configuration shown in Figure 1, user terminal 200, generation AI3 Only one instance each of 00, external database 400, and internal system 500 is displayed. However, multiple instances are acceptable. Server 100, User terminals 200, Generating AI 300, External data The base 400 and the internal system 500 are connected to the network NW. They can communicate with each other via a network (NW). The network (NW) is the internet and This includes intranets. Networks include LANs (Local Area Networks) and / Alternatively, it may include a WAN (Wide Area Network).

[0018] Server 100, User terminal 200, Generation AI 300, External database 400, Internal system Each STEM 500 consists of one or more Computer 900 units. The basic configuration of the Ta900 will be described later.

[0019] Server 100 is used by multiple users (job seekers) who access it via the network NW. Information provides a job posting optimization service to optimize job postings for the user terminal 200 used by the user. It is a notification processing device. Users of the job posting optimization service are employers who post job openings, for example. This includes companies, corporations, legal entities, government agencies, etc.

[0020] User terminal 200 is a terminal device used by job seekers. Functional configuration of user terminal 200. This will be explained later.

[0021] The generated AI300 is provided by an external provider different from the operator of server 100. I is involved in, for example, conversation, writing, summarizing, translation, information retrieval and collection, and programming. Large Language Models (LLMs) capable of generating text such as The generating AI learns from a vast amount of existing information when given instructions (prompts). This technology uses artificial intelligence to output responses that are in line with the context of the given instructions. I accepts input in real time and interactively in a conversational format and generates output. It can output data. In this embodiment, the server 100 uses the API (Appl) of the generating AI 300. The AI300 is used in conjunction with the ication Programming Interface, but server 10 It is also possible to use a generator AI that has been independently built within 0.

[0022] External database 400 is accessed outside of server 100 by anyone other than the operator of server 100, for example. For example, a recruitment agency (also known as an external agent) independently manages and operates Server 100. This is a database of job seekers that is provided. Server 100 is connected to an external database 400. By sharing (exchanging) the job postings described later with an external database, external database 4 00 can receive recommendations for job seeker candidates. Server 100 indirectly receives, Connect to external database 400 by / or directly. (The job postings are stored in external database 400.) By linking with this system, the pool of job seekers can be expanded.

[0023] Internal system 500 is one or more job seeker databases managed by the operator of server 100. This includes, for example, the form, type, and / or the matching service. The internal system 500 includes, for example, the form, type, and / or the matching service. It can include multiple job seeker databases corresponding to the associated services. The forms, types, and associated services of a service include, for example, offer services and agency services. These include recruitment services, direct scouting, etc. Job postings are handled by the internal system by default. It will be configured to automatically connect with at least one of the 500 job seeker databases. 500 internal systems that are not linked due to faults, such as a job seeker database, for example, a separate fee Regarding the job seeker database that will be generated, based on the proposal of server 100, or by the user The settings can be changed at the user's discretion. This allows for expansion of the target population.

[0024] Figure 2 is a functional block diagram of server 100 according to an embodiment of the present invention. Server 100 It comprises a communication unit 110, a storage unit 120, and a processing unit 130.

[0025] The communication unit 110 is a network interface, and via the network NW, users The system communicates with terminal 200, generation AI 300, external database 400, and internal system 500. The communication unit 110 includes a user terminal 200, a generating AI 300, and an external database 400. The data received from the internal system 500 is passed to the processing unit 130, and the processing unit 130 The generated data is stored in the user terminal 200, the generating AI 300, the external database 400, and the internal system. Send to Stem 500.

[0026] The memory unit 120 is configured using a storage device such as a magnetic hard disk or a semiconductor storage device. The memory unit 120 contains the application program 121 and the internal database 12 Remember 2 and mathematical models 123.

[0027] The application program 121 is executed by the processing unit 130, and mainly by processing unit 1 This is a program for implementing 30 different functional units.

[0028] Internal database 122 is the job posting database (hereinafter referred to as the job posting DB) described later. ) and the recruitment information database (hereinafter referred to as the recruitment information DB) are included. It stores recruitment activity information, including recruitment results information that links past job postings with past job seekers. It is the database that is managed.

[0029] Mathematical model 123 is a model that has learned from recruitment activity information. Specifically, for example, A model that has learned the correlation between multiple past job postings from a number of job seekers and the results of those job postings. This is the case. More specifically, for example, mathematical model 123 uses past job posting information and those This is a model that has learned the relationship between the characteristics of applicants included in the job posting results information. This includes the applicant's job requirements, basic information about the applicant, the applicant's profile, and the applicant's selection process. Includes information. Job requirements are the conditions on the job seeker's side that correspond to the job requirements. Applicant selection The process includes information on the applicant's selection history, acceptance / rejection, withdrawal, or joining the company. Learning further encompasses the industry and This may be done for each job category, or it may be done for those who have been selected among the applicants. "Applicants" refers to job seekers who have applied for the job posting, including those who have received a job offer and those who have been hired. This includes the decision-maker. Mathematical model 123 is designed when job requirements are given as input, specifying (connected). Referencing the job seeker database (which is provided), we will optimize the job requirements and target population as described below. Output at least one of the following: group size or hiring rate. The specified job seeker database is: Includes 400 external databases and 500 internal systems.

[0030] Figure 3 shows the data stored in the internal database 122 of the server 100 according to an embodiment of the present invention. This figure shows an example of the information.

[0031] As shown in Figure 3, the internal database 122 includes at least a job posting database and recruitment information Includes DB.

[0032] The job posting database manages job posting information for each employer using the job posting optimization service. It is the database that is managed.

[0033] The job posting information includes the job posting ID, the employer, the publication status, the source information of the job posting, and the job posting itself. Includes the original information analysis results.

[0034] The job posting ID is an identifier used to uniquely identify a job posting, and each job posting is assigned a unique ID to Server 10 0 is automatically assigned.

[0035] The "Employer" field is where the employer ID of the person creating the job posting is stored.

[0036] The publication status is that the job posting is on server 100 external (mainly external database 400 and This item indicates whether or not it is made public to the internal system (or internal system 500), and is not public or private. This item stores one of two states. Immediately after generating a job posting, server 10 0 means it is set to private. After that, the employer who created the job posting can switch the public / private setting. It is replaceable.

[0037] The job posting source information is the information that the employer provides to server 100 in order to create the job posting. .

[0038] The results of the job posting source information analysis include job requirements, potential collaborators, and hiring success rates. The results of the information analysis are information that is managed in history for each analysis run. Figure 3 shows, as an example, the most The first analysis result is labeled as ver1, and the second analysis result is labeled as ver2.

[0039] The job requirements include multiple requirement items. Each requirement item has an initial version, an optimized version, and a variable version. Includes settings. The initial content consists of the job requirements immediately after analysis, extracted from the source information of the job posting. Initially, the content is information that the job seeker can edit on user terminal 200. The optimized content is tailored to the specific job requirements. Note that the original content is appropriate. In this case, the optimization content does not need to be generated. The variable setting is an item that stores the degree to which changes in content are acceptable for each job requirement. In terms of form, the recruiter can change, not change, or semi-changeable options on the user terminal 200. You can select and set one of the following. The tolerance for content changes is that this job requirement is... This could mean something that is absolutely non-negotiable, or something that allows for some flexibility. For example, the job requirements might be about the assets held. If it is a specific category and the Class B Hazardous Materials Handler (Category 4) qualification is required, select "Not changeable". I would like to have the Grade 1 Eiken (Practical English Proficiency Test) as a qualification, but depending on other equivalent qualifications I hold... If a pre-1st grade level is acceptable, select "Changeable". The variable setting is initially set to "Changeable". It's fine if you do that.

[0040] The collaboration candidates include the initial candidate, the initial population, the optimized candidate, and the optimized population. The initial candidates are a list of potential partners immediately after analysis, obtained by analyzing the source information of the job postings, and are optimal. The list of potential partners is a list of potential partners obtained based on the optimization of the job requirements. Each linked candidate included in the supplementary and optimization candidates contains selected / deselected status information, and initially it is selected The selection status is set, but the recruiter can change the selection status on user terminal 200 (see below). (See list D233 in Figure 6). Initially, the population was obtained through analysis of the source information of job postings. The target population immediately following the job requirements is the optimized population. This is the target population. The target population will be discussed later.

[0041] The hiring rate includes the initial hiring rate and the optimized hiring rate. The initial hiring rate is: Calculated based on the initial content of all job requirements immediately after analysis, obtained by analyzing the source information of the job posting. The hiring rate is calculated based on the optimization of all job requirements. This is the calculated hiring success rate.

[0042] The recruitment information database contains information on multiple current and past users (employers) of the job posting optimization service. Therefore, a system manages information that links past job postings with the results of those job postings. It is a data base.

[0043] Returning to Figure 2, we will continue the explanation of the processing unit 130 of the server 100. The processing unit 130 is a functional unit The system consists of an information acquisition unit 131, a requirements extraction unit 132, a requirements optimization unit 133, and a job posting form. It comprises an editorial department 134, a collaboration department 135, and an improvement proposal department 136. The processing unit 130 is described By executing the application program 121 stored in memory unit 120, These functional units are implemented, and each step of the job posting creation process and job posting review process is carried out. The process will be carried out. Details of the job posting creation and review processes will be described later.

[0044] The information acquisition unit 131 acquires job posting source information used to create job postings from the user terminal 200. The source information for job postings is available in text, electronic file, and U format accessible via the network. Reference information such as RL (Uniform Resource Locator), etc., can be in any format. Combinations are also acceptable.

[0045] The information acquisition unit 131 provides the user terminal 200 with the source information of the job posting as a user interface. This document provides a job posting creation screen for obtaining the necessary information. An example of the job posting creation screen will be provided later.

[0046] Furthermore, if the acquired job posting source information is not in text format, the information acquisition unit 131 will... Convert the ba100 and / or job seeker-editable text.

[0047] The requirements extraction unit 132 extracts job requirements based on the job posting source information. Specifically, the requirements The extraction unit 132 analyzes the job posting source information acquired by the information acquisition unit 131 and determines the predetermined job posting. Extract the initial job requirements for each requirement item. The specified requirement items are, for example, job duties, Contract period, probationary period, place of work, working hours, break time, holidays, overtime work, wages, insurance coverage Information required: name or title of employer, employment type, status of passive smoking prevention measures, job title, number of hires. This includes job description, qualifications / application requirements, annual salary, working hours, job title / position, etc. It is pre-stored in 120. The requirements extraction unit 132 records the initial content of the extracted job requirements. Stored in a database of 120 job postings. Initial job requirements obtained by analyzing the source job posting information. The contents are stored as the result of the first analysis (ver1).

[0048] The requirements extraction unit 132 may use the generation AI 300 to extract job requirements. The requirements extraction unit 132 extracts job requirements corresponding to pre-set requirement items from the job posting source information. Generates a job requirements extraction instruction, which is an instruction (prompt) for extraction, and generates AI30 Enter the job requirements extraction instruction text and job posting source information into field 0, and then select the initial content of the job requirements for each requirement item. You can also extract them into two categories. Figure 4 shows a portion of an example of a job requirements extraction instruction. The job information extraction instruction is for job postings. The content may be generated according to the method of obtaining the vote source information (text, file, URL, etc.). .

[0049] The requirements extraction unit 132 identifies the job requirements that could not be extracted from the job posting source information, and the employer... You may conduct interviews to obtain information. The interviews will be conducted in a chat format (question and answer format). The interface may also be used. Furthermore, the requirements extraction unit 132 determines that the extracted job requirements are relevant to the recruitment activities. Determine whether the content is effective, and if not, you may conduct a hearing. If the job requirement "place of employment" is extracted as "head office or branch office", then You may also ask, "Does the term 'branch office' include foreign branches?" Similarly, in the requirements extraction unit 132... For the first job requirement that was extracted, a second job requirement related to the first job requirement was extracted. Even if such information is available, if it is not useful for recruitment activities, you may still conduct an interview. If so, the job requirements "Job Description" can be extracted as "Web Engineer", and the job requirements Even if "programming language" is extracted as an "application requirement," The job description for "Web Engineer" is "Programming Languages." If this is not effective for recruiters' hiring activities, then specify the web programming language. You can conduct a hearing where you ask, "Please determine this." The questions for the hearing should be related to past job postings. The job requirements on the application form are effective (more likely to lead to hiring) in recruitment activities based on that application form. It may also be generated using a learning model that has learned the correlation with the job requirements.

[0050] The requirements optimization unit 133 applies a mathematical model to the initial content of the job requirements extracted by the requirements extraction unit 132. Using 123, the optimized content, which is optimized for the initial content, is used as the recommended job requirements. The requirements optimization unit 133 generates the recommended job requirements (optimization content) and stores them in the storage unit 120. Store it in the job posting database.

[0051] The requirements optimization unit 133 will process the initial content of the job requirements if they have been edited by the employer. The initial job requirements may be re-analyzed and updated to optimize them as recommended job requirements.

[0052] The requirements optimization unit 133, based on the improvement proposal unit 136 described later, analyzes the selection status of job postings (recruitment activities). If it is determined that a revision of the job posting is necessary based on the progress of the project, the initial job requirements at that time will be revised. Even if we reanalyze the content and update the recommended job requirements, collaborating candidates, and / or hiring success rates good.

[0053] The requirements optimization unit 133 may analyze the job requirements based on variable settings of the job requirements. Example For example, weighting can be applied to the analysis according to the variable settings.

[0054] The job posting editing department 134 processes the initial content of multiple job requirements extracted by the requirements extraction department 132 into a job posting. The form is presented to the user terminal 200 used by the job seeker, and the initial content of the job requirements is edited. Attach. The job posting editorial department 134 stores the edited content in the memory unit 120 under version control. Furthermore, the job posting editorial department 134 combined the initial content of the job requirements with the optimized content of the recommended job requirements. The match is presented to the user terminal 200 used by the job seeker. The optimization details are then generated. For requirements that were not met, the display of optimization details will be omitted.

[0055] The job posting editorial department 134 formed a target population based on the initial content of the job requirements and The combination of the target population formed based on the optimized content of the recommended job requirements is as described above. You may present this to job applicants.

[0056] The job posting editorial department 134 receives the job requirements from the user terminal 200 used by the employer. For each variable setting, select one of the following options: changeable, not changeable, or semi-changeable. You may obtain it. Also, the job posting editorial department 134 can change whether it is unchangeable or semi-changeable. Changes in the effectiveness of recruitment when this is changed, specifically the target population and / or recruitment decision You may also present a constant rate of change.

[0057] The collaboration unit 135 selects one or more collaboration candidates from multiple job seeker databases based on the job requirements. Supplementary information is extracted. Specifically, the collaboration unit 135 uses the mathematical model 123 to extract the initial job requirements. We analyze the content and optimization requirements, and initially extract potential collaboration candidates. Furthermore, the collaboration unit 135 uses the mathematical model 123 to select candidates based on the initial content of the job requirements. The target population for when a partnership is established with the proposed partnership candidates is initially generated as the population, and optimization is performed within Based on the content, the target population when collaborating with the selected collaboration candidates is used as the optimized population. It is generated and stored in the memory unit 120. The target population is defined in the job seeker database. This is the target population of job seekers who meet the job requirements in a specified proportion or higher. The target populations are interconnected. It also varies depending on the job seeker database. Furthermore, the collaboration unit 135 uses the mathematical model 123 to determine the hiring rate based on the job requirements. This calculates the initial hiring rate based on the initial job requirements, and the optimization process. Based on this, the optimized hiring rate is calculated for each. In addition, the collaboration unit 135 calculates the job requirements. The initial hiring rate is calculated based on the initial content, the initial population, and / or the initial candidates. It may also be used. Similarly, the linking unit 135 receives the optimization content and the optimization population and / or optimization The optimal adoption rate and other parameters may be calculated based on the candidates.

[0058] The collaboration unit 135 may automatically connect with the collaboration candidates extracted based on the job requirements.

[0059] The collaboration unit 135, when the original content of the job requirements is edited, will update the edited job requirements. Based on the content, update at least one of the following: target population, collaborating candidates, or hiring rate. This information may be displayed to job seekers. The display may be updated in real time, from user terminal 200. It's also acceptable to do this when a request for a display update is received.

[0060] The Improvement Proposal Department 136 is responsible for the selection events related to job postings using user terminals 20 used by employers. We start from scratch and determine whether or not to revise the job posting based on the selection status (progress of recruitment activities). The selection process involves, for example, receiving applications from job seekers, interacting with applicants, and the applicants' responses. This includes hiring decisions, applicant withdrawals, etc. The determination of whether a review is necessary arises when the selection event is completed. Measurements are taken each time and / or at pre-set intervals. The decision may be reset when a review event occurs. Whether or not a review is necessary depends on the individual selection event. The decision may be made based on, or based on multiple selection events, or pre-set The number of times a decision on whether or not a review is necessary is made based on the period may also be used. The server 100 may manage the settings, or the recruiter may change them.

[0061] Figure 5 is a functional block diagram of a user terminal 200 according to an embodiment of the present invention. The end 200 consists of a communication unit 210, a storage unit 220, a control unit 230, a display unit 240, and an operation unit. It comprises a unit 250, a communication unit 210, a storage unit 220, a control unit 230, a display unit 240, and The operating unit 250 is electrically connected to each other via the communication bus 260. User terminal 200 refers to devices such as smartphones, tablet devices, and PCs.

[0062] <Screen example> Next, we will explain an example of the screen for the job posting optimization service provided by server 100.

[0063] Figures 6, 7, and 8 show the server 100 according to an embodiment of the present invention displayed on the user terminal 200. Screens D100, D200, and D300 are examples of the job posting optimization service screens. This is a diagram illustrating each of these.

[0064] The screen D100 shown in Figure 6 is an example of a job posting creation screen, where the employer enters the job posting source information. It is a user interface.

[0065] Screen D100 includes a title area D110 that shows the screen title, and a source information for the job posting. An input area D120 for easily inputting existing information, and a server 10 for confirming the input content. Button D130 for sending to 0, and the employer manually enters text as source information for the job posting. An input area D140 for applying power is located there.

[0066] The title area D110 contains the text "Job Posting Creation".

[0067] Input field D120 contains the string "Automatically create using existing information" and three input fields. Areas D121, D122, and D124 are located there. Above input field D121 is the text "Load other companies' media or your own website". Inside, the text "Please enter or copy and paste the URL" is placed. ru. Above input area D122 is the text "Load file", and inside it is the text "Load file Please drag and drop the file, or select it using the browse button. The strings are placed in that order. Also, to the right inside input area D122, the file A "Browse" button D123 is located here for selection. Above input field D124 is the text "Automatically generated by AI", and inside it is the text "Please enter... The string "uncool" is placed in each position.

[0068] Input field D140 contains the string "Create by yourself", and multiple input fields D141, D1 42, D143, D144, ... are arranged. Above the input fields D141, D142, D143, D144, ... are the item numbers and item names. The text "Please enter information" is placed inside each of the descriptions.

[0069] The screen D200 shown in Figure 7 is an example of a job posting editing screen, and the job posting entered on screen D100... Based on the source information, Server 100 extracts one or more job requirements for the user used by the employer. This is a user interface displayed on terminal 200 that accepts edits. Screen D200 is, After selecting (clicking or tapping) button D130 on screen D100, the user's terminal... It will be displayed at the end of page 200.

[0070] Screen D200 contains a title area D210 that shows the screen title, and each job description in the job posting. Display the items, the editing area D220, and the suggested services to link to the job posting. Area D230 accepts input indicating selection or non-selection, and the content is confirmed and sent to server 100. Button D240 is located for this purpose.

[0071] The title area D210 contains the text "Job Posting Editing".

[0072] Inside area D220, in the upper left corner, there is the text "There are items that we recommend reviewing" and , multiple input fields D222, D223, D225, ... and the job requirements are re-evaluated (re-resolved) all at once. A button D221 for analysis is located there. Above input areas D222, D223, D225, ... are input areas D141, D14 in Figure 5. 2, D143, D144, ... are each placed with the same item numbers and item descriptions. ru. Inside the input areas D222, D223, D225, ..., in the job application input screen shown in Figure 5... Based on the original job posting information entered by the employer, the initial content of the job requirements was extracted for each requirement item. The corresponding text is automatically entered and displayed in an editable format. Button D221 controls one or more input areas, especially multiple input areas D222, D223, D225, ... After the job posting is edited, you can select (click or tap) all of the edited content. This button is used to perform a batch re-analysis of the contents. Note that button D221 is on screen D It may be repositioned to the bottom of page 200.

[0073] Between input area D223 and input area D225, there is a message to present recommended job requirements. Message area D224 is located here. Message area D224 is the key to input area D225. An arrow pointing to input area D225 indicates that this is a recommended job requirement for the item. It is equipped with a warning icon and a message inside message area D224. A string of characters indicating a notification that reads, "It seems difficult to hire you under these conditions," and reference information regarding the notification. The report contains the string "Estimated number of applicants: 0" and the requirement item 3 in input field D225. In contrast, the optimized content (optimized content) is shown as "Recommended value (average annual salary of applicants) 500-6 The string "00 million yen" and are placed there. Also, message area D224 is within optimization. To the right of the string indicating the content is button D, which is used to apply the optimization details to input area D225. 226 is positioned there.

[0074] Furthermore, the input area D225, which is the target of message area D224, is re-evaluated (re-analyzed). Button D227 is located for this purpose. After the applicant edits input area D225... By selecting (clicking or tapping) button D227, input area D225 Analysis based on the edited content can be performed on a requirement item basis. In this way, re-evaluation can be performed. Button D227 is only temporarily displayed in the input area for the requirement items that are subject to the recommended job requirements. It may be displayed as such.

[0075] Inside area D230, in the upper left corner, it says "Our services and partner agent services" The string of text "By also collaborating (making public) this will lead to an increase in the pool of candidates and an increase in the hiring rate" and Area D231 shows the size of the target population, and area D232 shows the hiring rate. List D233, which displays a list of potential collaboration candidates, is located here. Area D231 contains the target calculated from the current job posting content (initial job requirements). The number of applicants (12 people) and the amount calculated when the content of the job posting is changed to an optimized version. The number of people in the target population (23) is shown. Area D232 contains the estimated recruitment calculated from the current job posting content (original job requirements). The conversion rate (35%) and the estimated minimum calculated when the content of the job posting is changed to an optimized version. The success rate is shown as 48%. List D233 contains the names of the candidate collaboration options and checkboxes indicating their selected / deselected status. The combination with Kus is displayed. In the example shown in Figure 6, the initial candidate (our service 1, Our services (Service 2, Agent 1, Agent 2, Agent 3) are available. In the Fort state, it is selected, and for the optimization candidate (Agent 4), it is an optimization candidate. The name is highlighted (e.g., underlined) so that it is clear that it is not selected by default. This is the case. By default, the unselected optimization candidates are edited by the employer based on the initial content of the job requirements. By gathering the data and increasing the match with recommended job requirements, server 100 automatically changes to a selected state. It may be changed. Job seekers can change the selection / deselection of potential collaborators using the checkboxes in list D233. can. Furthermore, when the selection status of a linking candidate in list D233 changes, area D231 will be updated. The estimated acceptance rate shown for the indicated target population and region D232 is updated and displayed. It will be done.

[0076] Button D240 displays the text "Confirm edits and publish". Button D211 has been repositioned above button D240.

[0077] The job seeker selects button D240 on screen D200 displayed on user terminal 200. (Click or tap) to confirm the edits made on screen D200 and the edited content It can be sent to server 100.

[0078] The screen D300 shown in Figure 8 is an example of a list screen of applicants who have applied for a job posting. This is a user interface that displays the details of the selected applicant in a pop-up window.

[0079] Screen D300 contains a title area D310 that shows the screen title, and a list of each applicant. The area D320 and the popup window area D330 are arranged. In area D320, each applicant's profile is displayed in a list format. Pop-up window area D330 displays the applicant's photo and basic information selected from the list. The following are located there: the selection status (results of the selection event), and button D331. Button D331 displays the text, "Why not review the job posting?" Job seekers can select (click or tap) button D331 on screen D300. You can transition to the job posting editing screen shown on screen D200 in Figure 6. In this case, on the job posting editing screen, , along with the original content of the job requirements for the current / latest version at the time of transition, and the original content Based on the results of the selection event for the job posting, the optimization content obtained by reanalyzing it is presented. Similarly, the target population and hiring rate will also be based on the initial selection criteria at this time. We present the results of the analysis, taking into account the venting results.

[0080] <System Operation> Next, the job posting creation process of the job posting optimization system 1 having the above configuration and functions and The process of reviewing job postings will be explained using a flowchart. The job posting creation process involves the steps of acquiring source job posting information, extracting job requirements, and optimizing job requirements. This is a series of processes including the collaboration process, the job posting presentation process, the editing content acquisition process, and the job posting finalization process. ru.

[0081] Figure 9 shows the job posting creation process by the job posting optimization system 1 according to an embodiment of the present invention. This is a flowchart.

[0082] In step S101, the user terminal 200 displays, for example, the job posting creation screen shown in Figure 5. Using a user interface, the system accepts input of job posting source information from employers, and the job posting source information The information is sent to server 100. The information acquisition unit 131 of server 100 is from user terminal 200. The source information of the job posting is obtained and stored in the storage unit 120 (job posting source information acquisition process).

[0083] In step S102, the requirements extraction unit 132 of the server 100 performed in step S101. The acquired job posting information is analyzed to extract job requirements (job requirements extraction process). Requirements Extraction Department Unit 132 stores the extracted job requirements in the memory unit 120 as the initial content.

[0084] In step S103, the requirements optimization unit 133 of the server 100 performs the following in step S102 The extracted job requirements are analyzed, and optimized recommended job requirements are generated (job requirement optimization). process).

[0085] In step S104, the communication unit 135 of the server 100 is extracted in step S102. Based on the job requirements, potential partners are extracted, and based on the extracted partners, the target mother The process involves creating a group (collaboration process).

[0086] In step S105, the job posting editing department 134 of server 100, in step S102 The job requirements extracted in step S103, the recommended job requirements generated in step S104 The extracted potential partners and target population are edited into job postings for user terminal 200. To present (display) as possible (job posting presentation process). The job posting editorial department 134 is shown, for example, in Figure 6. The job posting is presented via the user interface of the job posting editing screen.

[0087] In step S106, the job posting presented to the user terminal 200 in step S105 Regarding this, employers can edit it if necessary. Note that only job postings can be edited. The initial requirements and the selection / deselection of the collaboration candidates. If a human edits the job posting, proceed to step S107. Meanwhile, the user terminal... If no editing input was made by the employer in step 200, proceed to step S111. .

[0088] In step S107, the user terminal 200 receives an input from the recruiter confirming the edited content. The system accepts the input and sends the edited content to server 100. Server 100 then sends the edited content to the user Retrieve from terminal 200 (process of retrieving edited content).

[0089] In step S108, the requirements optimization unit 133 and the cooperation unit 135 of the server 100 Then, the edited content obtained in step S107 is re-analyzed and the job posting is updated.

[0090] In step S109, the job posting editing department 134 of server 100, in step S108 The updated job posting is presented (displayed) in an editable format on the user terminal 200. (Job Posting Section) The collection unit 134 is updated, for example, by the user interface of the job posting editing screen shown in Figure 6. Present the completed job posting.

[0091] In step S110, the job posting presented to the user terminal 200 in step S109 Regarding this, the job seeker can edit it again if necessary. Note that only the following can be edited: The initial job requirements and the selection / deselection of potential collaborators are determined on user terminal 200. If a human makes edits to the job posting, return to step S107. Meanwhile, the user terminal... If no editing input was made by the employer in step 200, proceed to step S111. .

[0092] In step S111, the user terminal 200 confirms the job posting from the recruiter. The system accepts the input and notifies server 100 of its confirmation. Server 100 then confirms the notification. Received from user terminal 200 (job posting confirmation process).

[0093] In step S112, the server 100 stores the updated job postings in the storage unit 120. Confirm the status, change the job posting's publication status from private to public, and complete the process. do.

[0094] Figure 10 shows the job posting review process by the job posting optimization system 1 according to an embodiment of the present invention. The flowchart is shown below. The job posting review process is performed after the job posting has been finalized and published, according to the specified time. This is executed in the MING process. The job posting review process involves the selection event acquisition process, the selection analysis process, and review. This includes a judgment process, a review notification process, and an edit acceptance process.

[0095] In step S201, the user terminal 200 receives selection event information related to the job posting. The information is sent to server 100. Server 100 retrieves the selection event information from user terminal 200. It's advantageous (selection event acquisition process).

[0096] In step S202, the improvement suggestion unit 136 of the server 100 in step S201 The acquired selection event information is analyzed (selection analysis process).

[0097] In step S203, the improvement suggestion unit 136 of the server 100 performs the following in step S202 Based on the analysis results, we will determine whether or not it is necessary to revise the job postings linked to the selection event information. (Review and evaluation process). If the evaluation result is true (YES), i.e., the job posting needs to be reviewed. If so, proceed to step S204. On the other hand, if the result of the determination is false (NO), i.e., seek If a review of the personnel records is not required, terminate this process.

[0098] In step S204, the improvement suggestion unit 136 of the server 100 uses the job postings of the job seekers. A notification suggesting improvements is presented (displayed) on the user terminal 200 (review notification process). .

[0099] In step S205, in response to the notification proposing the improvement presented in step S204 The recruiter can choose to accept or reject the proposal. If the job seeker chooses to agree to the proposal, the process proceeds to step S206. Meanwhile, the user terminal... If you choose not to agree to the proposal in step 200, this flow will be terminated.

[0100] In step S206, that is, in step S205, the employer agrees to the proposal. If this option is selected, the user terminal 200 sends a notification to the server 100 requesting a review. Server 100 receives a notification from user terminal 200 requesting a review and creates the job posting. Proceed to processing step S105 (jump from number 1 in Figure 10 to number 1 in Figure 9), job posting This process accepts edits (edit acceptance process).

[0101] <Basic Computer Configuration> Figure 11 is a block diagram showing the basic hardware configuration of the computer 900. Computer 900 comprises a control unit 901, a storage unit 902, a communication unit 903, and an input unit 904. It has an output unit 905. Control unit 901, storage unit 902, communication unit 903, input unit 90 4 and the output unit 905 are electrically connected to each other via the communication bus 910.

[0102] The control unit 901 is a CPU (Central Processing Unit). It includes a processing unit (also called a processor) and controls the various parts of the computer 900. It is a device that reads and executes various programs stored in the memory unit 902.

[0103] The memory unit 902 is a DRAM (Dynamic Random Access Memory). Computer 90 includes main memory such as ry) and auxiliary storage such as hard disk Various programs for running the operating system and various applications RAM, and the device that stores the data used by these programs. The process shown in the flowchart described above involves Server 100, User Terminal 200, and Generating AI 300. Each computer that makes up the external database 400 and the internal system 500 controls Unit 901 executes the programs stored in each of the memory units 902. This is achieved by [method / method].

[0104] The communication unit 903 is a device for communicating with external devices, and operates according to the instructions of the control unit 901. Data is sent and received. Server 100, user terminal 200, generating AI 300, external data Each computer that makes up the Tababase 400 and Internal System 500 is this communication unit 903 is used to communicate with other devices, including the network NW shown in Figure 1.

[0105] The input unit 904 is a device that receives input from an external source and supplies it to the control unit 901, for example. For example, it consists of a keyboard, mouse, touch panel, and camera. The output unit 905 is This device outputs the processing results of the control unit 901 to an external device, such as a display or speaker. It is composed of including the following. <Program> Here, a program for realizing each functional unit of the server 100 according to this embodiment I will explain this.

[0106] Server 100 is implemented on computer 900. The various components of server 100 are then... The basic operation is stored in program form in the auxiliary storage device of the memory unit 902. Control unit 90 1 reads the program from the auxiliary storage device of the storage unit 902 and stores it in the main storage device of the storage unit 902. It is deployed to the location and the above process is executed according to the program. In addition, the control unit 901 is programme According to the Gram, the storage area corresponding to the storage unit 120 described above is stored in the main memory of the storage unit 902. Secure it.

[0107] Specifically, the program is used in computer 900, with a processor and a memory unit A program to be executed on a computer equipped with the following, the program is The computer has an information acquisition step in which it obtains information about the source of the job posting from the job seeker, and the source of the job posting A requirements extraction step to extract job requirements based on the report, and an analysis of the extracted job requirements to the best A requirements optimization step that generates optimized recommended job requirements, and the job requirements and the recommended job A job posting editing step that presents the requirements to the aforementioned job seeker and accepts editing of the job requirements, This is a program that executes [the command / action].

[0108] The auxiliary storage device of the memory unit 902 is an example of a tangible medium that is not temporary. Other examples of tangible media that are not tangible media include magnetic disks connected via the input unit 904, optical disks, etc. Examples include magnetic disks, CD-ROMs, DVD-ROMs, and semiconductor memory. If the program is distributed to computer 900 via the network NW, the distribution The receiving computer 900 then loads the program into the main memory of the storage unit 902, and the above You may proceed with the process.

[0109] Furthermore, the program may be intended to implement some of the functions described above. Furthermore, the program has already stored the aforementioned functions in the auxiliary storage device of the memory unit 902. These are things that are achieved by combining them with other programs, so-called differential files (differential programs) (Mu) is also acceptable.

[0110] According to the job posting optimization system 1 of this embodiment described above, high-quality and uniform job postings are produced. It can be created efficiently. Server 100 automatically extracts job requirements from the source job posting information using a generation AI. This is possible. Employers can use the URL of their website or existing job posting information as the source of the job posting. The use of electronic files for employee records reduces the burden on employers in creating job postings. This allows for quick and efficient creation / modification of job postings. . By presenting job seekers with content optimized for the job requirements extracted by Server 100, Even job seekers who lack know-how regarding recruitment can do so without relying on the agent's skills or experience. By referring to the optimized content, job requirements can be easily modified quickly. This will improve the quality of job postings, enable the formation of an appropriate target pool of candidates, and facilitate the hiring process. The fixed rate can be increased. Furthermore, the external database 400 and internal system 500 are suitable for job postings. By linking with databases and internal system 500 ancillary services, the target population This will allow for the expansion of the organization and strengthened support for job seekers.

[0111] Furthermore, the present invention is not limited to the embodiments described above, and various modifications can be adopted.

[0112] For example, in the above embodiment, the hiring rate is based on the initial content of all job requirements. It was calculated, but based on certain job requirements selected according to predetermined conditions. That is also fine. The specified conditions are, for example, variable settings for requirement items.

[0113] Furthermore, if multiple optimization criteria are generated as recommended job requirements, the system will apply the following algorithm. They are ranked and then the top ones are selected and presented (displayed) to job seekers, or the rankings are displayed. This is also acceptable. The given algorithm takes into account the impact on the size of the target population, variable settings, etc. This is worth considering. It allows for efficient optimization of job postings.

[0114] Furthermore, in the above embodiment, regarding the re-analysis of the edited content in step S108, The content to be edited by the recruiter in S107 needed to be finalized, but the selection of a collaborating candidate... Changes to non-selection will be processed in real time at the time the on / off status is accepted for the target population. You may also update the hiring success rate. This will allow you to immediately grasp any changes.

[0115] Furthermore, in the above embodiment, the storage unit 120 was version-controlled for the job requirements. However, for content that the applicant can edit, the editing history until it is finalized is temporarily stored. Alternatively, the memory unit 120 may be configured to store only the most recently confirmed information.

[0116] Furthermore, although the AI400 generated in the above embodiment uses a large-scale language model, image generation Non-text-based generative models such as video generation models, audio generation models, and this A multimodal generative model combining these elements may also be used.

[0117] (Note) The features of the above-described embodiment are noted below. (Note 1) Information acquisition unit that obtains job posting source information from job seekers, A requirements extraction unit extracts job requirements based on the aforementioned job posting source information, A requirements optimization unit analyzes the extracted job requirements and generates optimized recommended job requirements, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. The editorial department that attaches the job postings, A job posting optimization system equipped with the following features. This automatically extracts the job requirements needed to create a job posting, giving employers more freedom. It is possible to use job posting source information in any format. In addition, it provides recommended job postings optimized from the extracted job requirements. Since the number of candidates is presented, even job seekers with little know-how, experience, or track record in recruitment activities can find high-quality candidates. Personnel records can be easily created. (Note 2) Based on the aforementioned job requirements, one or more job seeker databases are selected and linked. It further includes a coordinating unit that generates the target population for the combination, The aforementioned job posting editorial department has determined the target population and recommended job requirements based on the aforementioned job requirements. The combination of the target population based on the above is presented to the job seeker. The job posting optimization system described in Appendix 1. This allows for the formation of a target pool that meets the job requirements, as well as multiple job seekers. By linking with a database, the target population can be expanded, improving the hiring success rate. ru. (Note 3) The aforementioned linking unit automatically links to the job seeker database extracted based on the job requirements. do, The job posting optimization system described in Appendix 2. This allows access to a database of job seekers who meet the job requirements. (Note 4) The requirements optimization unit, when the job requirements are edited, re-analyzes the edited job requirements. Analyze and update the aforementioned recommended job requirements. The job posting optimization system described in Appendix 1. This allows you to check the impact of the edits. (Note 5) The aforementioned linkage unit, when the job requirements are edited, will perform the following based on the edited job requirements. Update each of the aforementioned target populations. The job posting optimization system described in Appendix 2. This allows us to check the impact of the edited content on the target population. (Note 6) The aforementioned job posting editorial department has received from the aforementioned employer the following variable settings for the job requirements: "changeable, changeable" Get a selection input to choose either "cannot be changed" or "can be changed". The requirements optimization unit analyzes the job requirements for each of the variable settings. The job posting optimization system described in Appendix 1. This allows for analysis that takes into account the specific preferences of job seekers. (Note 7) The aforementioned job posting editorial department determines whether the variable setting is unchangeable or semi-changeable. Present the benefits of adopting a change that makes it possible to modify the system. The job posting optimization system described in Appendix 1. This allows us to propose a compromise that addresses the specific requirements of the job seeker. (Note 8) The requirements extraction unit extracts the job requirements using a generation AI. The job posting optimization system described in Appendix 1. This makes the job posting creation process more efficient. (Note 9) The aforementioned linkage unit links to services associated with the job seeker database. The job offer ticket optimization system described in Supplementary Note 2. Thereby, support services matching the characteristics of the job offer ticket can be used. (Supplementary Note 10) The information acquisition unit provides a user interface that accepts a URL (Uniform Resource Locator) and / or an electronic file as the job offer ticket source information and converts it into editable text to the user terminal used by the job seeker. The job offer ticket optimization system described in Supplementary Note 1. Thereby, the job offer ticket creation work can be made more efficient. (Supplementary Note 11) The improvement proposal unit further includes obtaining a screening event of a job offer ticket created based on the job offer ticket source information and determining whether it is necessary to review the job offer ticket based on the screening event. The job offer ticket optimization system described in Supplementary Note 1. Thereby, it is possible to suggest the causal relationship between the screening situation and the job offer ticket and propose a review of the job offer ticket at an appropriate or necessary timing. (Supplementary Note 12) When it is determined that it is necessary to review the job offer ticket, the requirement optimization unit re-analyzes the job requirements. The job offer ticket optimization system described in Supplementary Note 11. Thereby, the content of the job offer ticket can be improved in response to the temporal changes in the balance between the job market and the job hunting market. (Supplementary Note 13) The requirement extraction unit identifies job requirements that could not be extracted from the job offer ticket source information and obtains the job requirements that could not be extracted from the job seeker. The job offer ticket optimization system described in Supplementary Note 1. Thereby, a job offer ticket without omission can be easily created. (Supplementary Note 14) An information acquisition unit that acquires job offer ticket source information from a job seeker, A requirements extraction unit extracts job requirements based on the aforementioned job posting source information, A requirements optimization unit analyzes the extracted job requirements and generates optimized recommended job requirements, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. The editorial department that attaches the job postings, A job posting optimization server equipped with the following features. (Note 15) The information acquisition step involves obtaining the source information of the job posting from the employer, A requirements extraction step that extracts job requirements based on the aforementioned job posting source information, The requirements optimization step analyzes the extracted job requirements and generates optimized recommended job requirements. P and, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. Steps for editing the job posting, A program that causes a computer to execute something. (Note 16) The information acquisition step involves obtaining the source information of the job posting from the employer, A requirements extraction step that extracts job requirements based on the aforementioned job posting source information, The requirements optimization step analyzes the extracted job requirements and generates optimized recommended job requirements. P and, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. Steps for editing the job posting, A method for optimizing job postings by having a computer perform the optimization. [Explanation of Symbols]

[0118] 1: Job posting optimization system 100: Job posting optimization server 110: Communications Department 120: Storage section 123: Mathematical Models 130: Processing Unit 131: Information acquisition department 132: Requirements extraction part 133: Requirements Optimization Department 134: Job Posting Editorial Department 135: Liaison Department 136: Improvement proposal department 200: User terminal 300: Generation AI 400: External database 500: Internal Systems D100, D200, D300: Screen NW: Network

Claims

1. Information acquisition unit that obtains job posting source information from job seekers, A requirements extraction unit extracts job requirements based on the aforementioned job posting source information, A requirements optimization unit analyzes the extracted job requirements and generates optimized recommended job requirements, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. The editorial department that attaches the job postings, A job posting optimization system equipped with the following features.

2. Based on the aforementioned job requirements, one or more job seeker databases are selected and linked. It further includes a coordinating unit that generates the target population for the combination, The aforementioned job posting editorial department has determined the target population and recommended job requirements based on the aforementioned job requirements. The target population based on the above is presented to the job seeker. The job posting optimization system according to claim 1.

3. The aforementioned linking unit automatically links to the job seeker database extracted based on the job requirements. do, The job posting optimization system according to claim 2.

4. The requirements optimization unit, when the job requirements are edited, re-analyzes the edited job requirements. Analyze and update the aforementioned recommended job requirements. The job posting optimization system according to claim 1.

5. The aforementioned linking unit, when the job requirements are edited, will perform the following based on the edited job requirements. Update the target population. The job posting optimization system according to claim 2.

6. The aforementioned job posting editorial department has received from the aforementioned employer the following variable settings for the job requirements: "changeable, changeable" Get a selection input to choose either "cannot be changed" or "can be changed". The requirements optimization unit analyzes the job requirements for each of the variable settings. The job posting optimization system according to claim 1.

7. The aforementioned job posting editorial department determines whether the variable setting is unchangeable or semi-changeable. Present the benefits of adopting a change that makes it possible to modify the system. The job posting optimization system according to claim 6.

8. The requirements extraction unit extracts the job requirements using generation AI. The job posting optimization system according to claim 1.

9. The aforementioned linkage unit links to services associated with the job seeker database. The job posting optimization system according to claim 2.

10. The aforementioned information acquisition unit uses the URL (Uniform Resource Locator) as the source information for the job posting. A user interface that accepts and / or electronic files and converts them into editable text. Provided to the user terminal used by the aforementioned recruiter, The job posting optimization system according to claim 1.

11. Based on the aforementioned job posting source information, the selection event of the job posting is obtained, and the selection event The system further includes an improvement suggestion unit that determines whether or not the job posting needs to be revised based on the results. The job posting optimization system according to claim 1.

12. If the requirements optimization unit determines that the job posting needs to be reviewed, it will revise the job requirements. Analyze, The job posting optimization system according to claim 11.

13. The requirements extraction unit identifies the job requirements that could not be extracted from the job posting source information, and the extraction unit Obtain the job requirements that could not be provided from the aforementioned employer. The job posting optimization system according to claim 1.

14. Information acquisition unit that obtains job posting source information from job seekers, A requirements extraction unit extracts job requirements based on the aforementioned job posting source information, A requirements optimization unit analyzes the extracted job requirements and generates optimized recommended job requirements, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. The editorial department that attaches the job postings, A job posting optimization server equipped with the following features.

15. The information acquisition step involves obtaining the source information of the job posting from the employer, A requirements extraction step that extracts job requirements based on the aforementioned job posting source information, The requirements optimization step analyzes the extracted job requirements and generates optimized recommended job requirements. P and, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. Steps for editing the job posting, A program that causes a computer to execute something.

16. The information acquisition step involves obtaining the source information of the job posting from the employer, A requirements extraction step that extracts job requirements based on the aforementioned job posting source information, The requirements optimization step analyzes the extracted job requirements and generates optimized recommended job requirements. P and, The aforementioned job requirements and the aforementioned recommended job requirements are presented to the employer, and the employer is asked to edit the aforementioned job requirements. Steps for editing the job posting, A method for optimizing job postings by having a computer perform the optimization.

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