System

Abstract

A system is provided.SOLUTION: A system comprising: a generating AI for generating a skill profile of an applicant based on analyzed information; a server for receiving interview results and test results; a server for analyzing the received interview results and test results to make a comprehensive evaluation of the applicant; a server for collecting and analyzing job offer information of a company; a generating AI for generating an optimum matching candidate by collating the job offer information of the company with the skill profile of the applicant; and a server for proposing the generated matching candidate to the company.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When companies are recruiting or changing jobs, there is often a mismatch between the skills and aptitude of job seekers and the company's job postings, making it difficult to utilize human resources efficiently. This mismatch makes the recruitment process inefficient and increases the burden on recruiters. Subjective evaluations can also lead to a lack of transparency and fairness. Furthermore, while rapid response is required for large-scale recruitment projects, current systems have limitations. To solve these problems, a system is needed that objectively and comprehensively evaluates applicants' skills and aptitudes and achieves optimal matching. [Means for solving the problem]

[0005] The system includes a terminal for applicants to submit resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview and test results, a server for analyzing the imported interview and test results and conducting a comprehensive evaluation of the applicant, a server for collecting and analyzing company job information, a generation AI that compares company job information with the applicant's skill profile to generate optimal match candidates, and a terminal for proposing the generated match candidates to the company. This allows for an objective evaluation of applicants' skills and aptitude and matching them with the company's needs. The system uses the generation AI to evaluate learning ability and flexibility based on past project data and performance reviews, and also incorporates interview and test results, enabling a transparent comprehensive evaluation. It also quickly proposes optimal match candidates and can handle large-scale recruitment projects. This improves the efficiency and fairness of the recruitment process.

[0006] "Terminal" means a device used by a user to input and send information, and has the ability to communicate with a server.

[0007] A "server" is a mechanical device that receives information over a network and analyzes it, and is a central component of the system that works in conjunction with generative AI and databases.

[0008] "Generative AI" is a type of artificial intelligence (AI) that is a software system that learns and analyzes input data to generate a user's skill profile and matching results.

[0009] A "resume" is a document that a user submits by listing information such as their educational background, work history, and skills.

[0010] A "skill sheet" is a document submitted by a user detailing the techniques and skill sets that the user possesses.

[0011] "Analysis" is the process by which the server carefully examines and evaluates the information it receives and extracts useful data and features.

[0012] "Interview results" refers to the evaluation and scores given by the interviewer when the applicant was interviewed.

[0013] "Test results" refers collectively to the grades and scores obtained when an applicant takes a technical test or written test.

[0014] A "skill profile" is a detailed record of a user's skills and aptitudes, created based on information analyzed by the generation AI.

[0015] "Job information" is information that describes the qualifications, necessary skills, and job content of the employees that a company is looking for.

[0016] "Matching" is the process in which the generating AI compares the user's skill profile with company job listings and evaluates the degree of match and suitability.

[0017] A "matching candidate" is a candidate selected by the generation AI based on the matching results who best meets the needs of the user and the company.

[0018] "Proposal" is the process of notifying companies of the matching results calculated by the generation AI and providing them as reference material for recruitment. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention is a system that utilizes generative AI to effectively match job seekers with company job information. Below, we will explain the program processing of this system in natural language and provide specific examples.

[0041] Program processing

[0042] 1. The user uploads their resume and skill sheet from their device to the server.

[0043] A user uploads a file using a dedicated upload form.

[0044] The server receives the uploaded file and determines its format (e.g. PDF, DOCX, etc.).

[0045] 2. The server analyzes the uploaded resume and skill sheet.

[0046] The server uses a document analysis engine to extract information such as educational background, work history, and skill sets from resumes and skill sheets.

[0047] 3. The server uses the generation AI to generate a skill profile for the user.

[0048] Based on the extracted information, the generative AI generates a skill profile for the user.

[0049] At this time, past project data and performance reviews are also analyzed, and learning ability and flexibility are also evaluated.

[0050] 4. The user undergoes an interview and technical test, and the results are entered into the system.

[0051] The interviewer (user) enters the interview results and technical test results into the system through an input form.

[0052] The server receives these inputs and begins parsing them.

[0053] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[0054] The server analyzes interview results and technical test scores to evaluate communication skills and technical abilities.

[0055] Based on this, the user's skill profile is updated.

[0056] 6. Collect and analyze company job information.

[0057] Companies submit job information to the server using an input form.

[0058] The server receives the job information and analyzes the required skills and characteristics.

[0059] 7. The server matches the user's skill profile with company job listings.

[0060] The server uses generated AI to match the user's skill profile with job listings.

[0061] Based on the matching results, optimal matching candidates are generated.

[0062] 8. The server proposes the best matching candidates to the company.

[0063] The server creates a list of the generated matching candidates and presents them to the company's terminal.

[0064] The company's recruiter (user) reviews the provided candidate information and makes the final decision.

[0065] Specific examples

[0066] A job seeker, A, uploads his / her resume and skill sheet to the server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[0067] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[0068] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0069] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user uploads their resume and skill sheet from their terminal to the server.

[0073] The user uses the system's dedicated upload form, selects the resume or skill sheet file, and begins uploading.

[0074] The device sends the uploaded file to the server.

[0075] Step 2:

[0076] The server receives and stores the uploaded resumes and skill sheets.

[0077] The server automatically determines the file format (PDF, DOCX, etc.).

[0078] The server stores the file for passing to the analysis engine.

[0079] Step 3:

[0080] The server uses a document analysis engine to extract information from resumes and skill sheets.

[0081] The server analyzes the contents of the resume and skill sheet and extracts educational background, work history, and skill set as text data.

[0082] The server organizes the extracted data and extracts the necessary information.

[0083] Step 4:

[0084] The server uses a generation AI to generate a skill profile for the user.

[0085] The server inputs the extracted information into a generation AI, which creates a skill profile based on the user's educational background, work history, and skill set.

[0086] The generative AI performs additional analysis to assess the user's learning ability and flexibility.

[0087] Step 5:

[0088] Users take interviews and technical tests, and the results are entered into the system.

[0089] After the interview, the interviewer (user) sends the evaluation score and comments to the server using an input form.

[0090] The results of the technical tests are also entered and sent to the server.

[0091] Step 6:

[0092] The server analyzes the interview and test results and gives the user an overall evaluation.

[0093] The server analyzes the interview results received from the interviewer and evaluates the user's performance and aptitude.

[0094] Based on the scores of the technical test, the user's technical ability and expertise are evaluated.

[0095] Step 7:

[0096] The server uses the generated AI to update the user's skill profile.

[0097] The generative AI updates the user's skill profile based on interview results and technical test evaluations.

[0098] Generate an updated skills profile that reflects your overall assessment.

[0099] Step 8:

[0100] Companies enter job information.

[0101] A company's recruiter (user) submits job information to the server via an input form.

[0102] Company job postings include the required skill sets and job duties.

[0103] Step 9:

[0104] The server receives and analyzes the company's job information.

[0105] The server analyzes the job information using an analytical engine and extracts the required skills and characteristics.

[0106] The server stores the job listings in a database.

[0107] Step 10:

[0108] The server matches the user's skill profile with company job postings.

[0109] The server uses the generated AI to begin matching the user's skill profile with job listings.

[0110] Based on the matching results, the degree of skill matching and compatibility is evaluated.

[0111] Step 11:

[0112] The server generates optimal matching candidates and presents them to the company's terminal.

[0113] The server selects the best matching candidates from the matching results and generates a list.

[0114] The generated list is sent to the company's recruiter's device.

[0115] The recruiter (user) checks the proposed candidate information in the review form.

[0116] In this way, the system achieves efficient and fair talent matching.

[0117] Example 1

[0118] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0119] Conventional job change support systems have difficulty managing a wide range of information about applicants in one place and effectively matching them with companies' job openings. Furthermore, they lack the functionality to import interview and technical test results into the system and perform a comprehensive evaluation based on those results. As a result, there are cases where applicants are not properly matched with companies, which creates problems that prevent the job change process from proceeding smoothly.

[0120] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0121] In this invention, the server includes a terminal for applicants to submit resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and test results, a server that analyzes the imported interview results and test results to perform a comprehensive evaluation of the applicant, a server that collects and analyzes company job information, a generation AI that compares company job information with the applicant's skill profile and generates optimal matching candidates, a terminal for proposing the generated matching candidates to companies, a document analysis engine, a natural language processing tool, and a generation AI model for matching candidates with job information. This makes it possible to efficiently and accurately match applicants with company job information.

[0122] A resume is a document in which an applicant lists information such as their work history, educational background, and skills.

[0123] A "skills sheet" is a document in which an applicant details his or her technical skills and expertise.

[0124] A "terminal" is a device such as a computer or smartphone that is operated by a user.

[0125] A "server" is a computer system that stores and processes data on a network.

[0126] "Generative AI" is an artificial intelligence technology that generates new information and profiles based on given data.

[0127] "Interview results" refers to the evaluation and feedback of the applicant obtained through the interview.

[0128] "Test results" refer to the numerical results or evaluations of the technical tests or evaluation tests taken by the applicant.

[0129] A "skills profile" is a profile that summarizes an applicant's skills and characteristics based on analyzed information.

[0130] "Job information" refers to detailed information published by companies, such as job types, required skills, and compensation.

[0131] A "document analysis engine" is a software technology for analyzing uploaded documents and extracting necessary information.

[0132] A "natural language processing tool" is a software technology for analyzing text data and understanding human language.

[0133] A "generative AI model" is an artificial intelligence algorithm or framework that learns from massive amounts of data and generates new information and patterns.

[0134] This invention relates to a system that effectively matches job seekers with company job information. This system uses generative AI to create a skill profile of the applicant and compares it with the company's job information to achieve optimal matching.

[0135] The system consists of multiple components, including the following hardware and software:

[0136] 1. Terminal

[0137] A device such as a computer or smartphone that is operated by a user.

[0138] The terminal is used by users to upload resumes and skill sheets.

[0139] For example, a user can use a dedicated upload form to select a file, and the terminal will then send the file to the server.

[0140] 2. Server

[0141] A computer system for receiving and analyzing resumes and skill sheets.

[0142] The server uses the Python library PyMuPDF and the OCR tool Tesseract to parse the uploaded documents.

[0143] 3. Generation AI

[0144] It is an artificial intelligence technology for generating skill profiles of applicants.

[0145] For example, OpenAI's GPT-4 model is used to generate a skill profile based on the extracted information and store it in a database.

[0146] Specific examples of prompt sentences are as follows:

[0147] "Extract the following information from the job applicant's resume and skill sheet: educational background, work history, skill set, past project data, and performance review."

[0148] 4. Input Form and Analysis Tools

[0149] This is an input form for capturing interview and test results.

[0150] The server uses NLP tools (e.g., SpaCy or Gensim) to analyze the input data.

[0151] 5. Matching Engine

[0152] This is software for collecting and analyzing corporate job information.

[0153] Analyze job postings using text mining tools (e.g., NLTK).

[0154] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to assess the match between the applicant's skill profile and the company's job posting.

[0155] 6. Proposed System

[0156] This is a system that proposes the most suitable matching candidates to companies.

[0157] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiting staff reviews the candidate information provided and makes the final decision.

[0158] As a specific example, suppose a job seeker, A, uploads his / her resume and skill sheet to a server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[0159] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[0160] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0161] Finally, the server proposes information about Person A to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching. This invention makes it possible to achieve an ideal match for both job seekers and companies.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Step 1:

[0164] The user uploads their resume and skill sheet from their terminal to the server.

[0165] Specifically, the user selects a file using a dedicated upload form. The terminal then sends the selected file to the server. The server receives the uploaded file and determines its format (e.g., PDF, DOCX). The input is the uploaded file, and the output is the result of determining the file format.

[0166] Step 2:

[0167] The server analyzes the uploaded resume and skill sheet.

[0168] Specifically, the server launches a document analysis engine (for example, the Python library PyMuPDF or the OCR tool Tesseract). The server uses this analysis engine to automatically extract information such as educational background, work history, and skill set from resumes and skill sheets. The input is the received file, and the output is the extracted information.

[0169] Step 3:

[0170] The server uses a generation AI to generate a skill profile for the user.

[0171] Based on the extracted information, the server uses a generative AI (for example, OpenAI's GPT-4 model) to generate a skill profile for the user. Specifically, the server uses the following prompt for the generative AI: "Please extract the following information from the job seeker's resume and skill sheet: educational background, work history, skill set, past project data, and performance review." The input is the extracted information, and the output is the generated skill profile.

[0172] Step 4:

[0173] Users take interviews and technical tests, and the results are entered into the system.

[0174] The interviewer (user) enters the interview results and technical test results into the system through an input form. The terminal sends the entered data to the server. The server analyzes the received data. An NLP tool (e.g., SpaCy or Gensim) is used for the analysis. The input is the interview results and technical test results, and the output is the analyzed data.

[0175] Step 5:

[0176] The server analyzes the interview and test results and gives the user an overall evaluation.

[0177] Specifically, the server analyzes interview results and technical test scores to evaluate the applicant's communication and technical skills. This information is used to update the user's skill profile. The input is the analyzed interview and test results, and the output is the updated skill profile.

[0178] Step 6:

[0179] Companies enter job information and the server analyzes it.

[0180] Companies enter job information into the system using an input form. The terminal sends the entered job information to the server. The server receives the job information and analyzes it for required skills and characteristics. A text mining tool (e.g., NLTK) is used for the analysis. The input is the job information, and the output is the analyzed job information.

[0181] Step 7:

[0182] The server matches the user's skill profile with company job postings.

[0183] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to match the user's skill profile with job postings. The input is the skill profile and job posting, and the output is the match and candidate matches.

[0184] Step 8:

[0185] The server proposes the best matching candidates to the company.

[0186] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiter (user) reviews the provided candidate information and makes a final decision. The input is the list of matching candidates, and the output is the company's final decision.

[0187] (Application example 1)

[0188] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0189] The manual hiring process for brick-and-mortar stores is time-consuming and labor-intensive, and matching applicants with job listings is difficult to optimize. Furthermore, the difficulty of properly assessing applicants' skills and communication abilities can lead to reduced hiring efficiency and accuracy. Furthermore, there is a lack of methods to virtually recreate interviews in a real-world store environment and evaluate applicant suitability.

[0190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0191] In this invention, the server includes a terminal through which applicants submit their resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and technical evaluations, a server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant, a server that collects and analyzes job information from physical stores, a generation AI that compares the job information from physical stores with the applicant's skill profile and generates optimal matching candidates, and a terminal for proposing the generated matching candidates to physical stores.This makes it possible to improve the efficiency and accuracy of staff recruitment at physical stores and to increase the accuracy of applicant aptitude evaluations.

[0192] "Applicant" refers to an individual who applies for a job by submitting a resume or skill sheet.

[0193] A "resume" is a document that lists information such as an applicant's educational background, work history, and qualifications.

[0194] A "skills sheet" is a document that details an applicant's specialized skills and experience.

[0195] "Terminal" refers to the device used by applicants and companies to input, submit, and view information, specifically a smartphone or computer.

[0196] A "server" is a computer system that communicates with multiple terminals via a network and stores and processes data.

[0197] "Generative AI" refers to artificial intelligence that generates responses and actions based on input data. In particular, in this invention, it generates the applicant's skill profile and compares it with job information.

[0198] A "skills profile" is a detailed competency assessment document of an applicant that is generated based on the applicant's educational background, work history, skill set, etc.

[0199] "Interview results" refers to the evaluation results of the applicant when they were interviewed.

[0200] "Technical assessment" refers to the assessment of applicants when they are tested on specific technologies or skills.

[0201] A "comprehensive evaluation" is an overall assessment of an applicant based on a comprehensive analysis of various information such as resumes, skill sheets, interview results, and technical evaluations.

[0202] A "brick and mortar store" refers to a physical commercial establishment, such as a cafe or retail store.

[0203] "Job information" is information that describes the qualifications and job duties of the personnel that a company is looking for.

[0204] The present invention provides a system for improving the efficiency and accuracy of the staff recruitment process in brick-and-mortar stores. Specific embodiments of this system are described below.

[0205] System Configuration

[0206] The system consists of the following main components:

[0207] 1. A device for applicants to submit their resumes and skill sheets

[0208] 2. Server for analyzing submitted resumes and skill sheets

[0209] 3. Generative AI that generates skill profiles for applicants based on analyzed information

[0210] 4. Terminal for capturing interview results and technical evaluations

[0211] 5. A server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant.

[0212] 6. Server that collects and analyzes job information from brick-and-mortar stores

[0213] 7. Generative AI that matches job postings at brick-and-mortar stores with applicants' skill profiles to generate optimal matching candidates

[0214] 8. A device for proposing the generated matching candidates to the physical store

[0215] Hardware and software used

[0216] Hardware:

[0217] Smartphones and computers (devices used by applicants and brick-and-mortar stores)

[0218] Server (data analysis and storage)

[0219] Head-mounted displays (HMDs, used for virtual interviews, etc.)

[0220] software:

[0221] Generative AI models (GPT-4 and BERT)

[0222] Document analysis engine (e.g. Google Cloud Vision API)

[0223] Program processing

[0224] The server receives data from the device on which applicants submit their resumes and skill sheets. The document analysis engine on the server extracts information such as educational background, work history, and skill sets from the submitted data. The AI ​​then generates a skill profile based on the extracted data. At the same time, the server also imports interview results and technical evaluations, and performs a comprehensive evaluation.

[0225] When a brick-and-mortar store inputs job information, the server analyzes the information and identifies the required skills and characteristics. The generation AI matches the applicant's skill profile with the brick-and-mortar store's job information and generates the best matching candidates. This matching is performed by analyzing the data input into the generation AI using prompt sentences.

[0226] Finally, the generated candidates are presented to the store, where staff can review and select candidates. The store can then use touch and voice commands to check candidate information, contact them, schedule interviews, and more.

[0227] Specific examples

[0228] For example, if physical store A registers a job posting for a service staff member in the system, the generation AI will match applicant B's skill profile with store A's job posting. Applicant B had previously uploaded a resume and was evaluated for his excellent customer service skills in an online interview. The generation AI will determine that applicant B is highly suitable for store A's requirements and suggest applicant B to the store A staff member. The staff member can then check applicant B's details within the app and contact him, resulting in an efficient recruitment process.

[0229] Prompt Sentence Examples

[0230] An example of a prompt is:

[0231] "Evaluate this candidate's customer service skills and flexibility based on their resume and interview results to determine if they are an ideal match for the following job posting: (specific job posting details)"

[0232] By inputting these prompts into the generation AI, it is possible to analyze suitable candidates and propose optimal matching candidates.

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] The user uploads a resume or skill sheet from their device to the server. The user uploads a file in PDF or DOCX format using a dedicated upload form. The server receives the uploaded file and determines the file format. The input of this process is the resume or skill sheet, and the output is the file data stored on the server.

[0236] Step 2:

[0237] The server analyzes the uploaded resumes and skill sheets. The server's document analysis engine (e.g., Google Cloud Vision API) extracts information such as educational background, work history, and skill sets from the resumes and skill sheets. The input to this process is the file data saved in step 1, and the output is a dataset of the extracted information.

[0238] Step 3:

[0239] The server uses a generative AI to generate a skill profile for the user. The generative AI (e.g., GPT-4) generates the skill profile based on the extracted information. The input to this process is the dataset obtained in step 2, and the output is a skill profile. Specifically, past project data and performance reviews are also analyzed.

[0240] Step 4:

[0241] A user undergoes an interview or technical evaluation, and the results are imported into the system. The user's interview results and technical evaluation data are input from their terminal to the server. The input to this process is the interview results and technical evaluation entered by the interviewer via their terminal, and the output is the evaluation data stored on the server.

[0242] Step 5:

[0243] The server analyzes the interview results and technical evaluation and performs an overall evaluation of the user. The server evaluates communication and technical skills based on the interview results and technical evaluation. The input to this process is the evaluation data saved in step 4, and the output is an updated skill profile.

[0244] Step 6:

[0245] The server collects and analyzes job postings from brick-and-mortar stores. A brick-and-mortar store representative submits the job posting to the server using an input form. The server receives the job posting and analyzes the required skills and characteristics. The input to this process is the brick-and-mortar store's job postings, and the output is a dataset of analyzed job postings.

[0246] Step 7:

[0247] The server uses a generation AI to match the user's skill profile with job postings at brick-and-mortar stores. The generation AI uses a prompt to determine the degree of match between the skill profile and the job posting. The input to this process is the dataset obtained in steps 3 and 6, and the output is a list of the best matching candidates. An example of a specific prompt is, "Evaluate this candidate's customer service skills and flexibility based on their resume data and interview results, and determine whether they are the best match for the job posting below. Job posting: (specific job posting details)."

[0248] Step 8:

[0249] The server proposes the best candidates to the store. The generated list of candidates is displayed on a terminal in the store for the store staff to review. The input of this process is the list of best candidates, and the output is an interface for the store staff to review, contact, and schedule interviews.

[0250] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0251] This invention is a recruitment system that utilizes generative AI and an emotion engine to effectively match job seekers with companies' job information. This system recognizes the user's emotions and reflects that emotion data in evaluation and matching, thereby achieving more accurate talent matching.

[0252] Program processing

[0253] 1. The user uploads their resume and skill sheet from their device to the server.

[0254] The user uses a dedicated upload form to select a resume or skill sheet file and send it from the terminal to the server.

[0255] The server determines the file format (PDF, DOCX, etc.) and saves the received file.

[0256] 2. The server analyzes the uploaded resume and skill sheet

[0257] The server uses a document analysis engine to extract information about education, work history, and skill sets from resumes and skill sheets.

[0258] 3. The server uses the AI ​​to generate a skill profile for the user.

[0259] The server inputs the extracted information into a generation AI to generate a skill profile based on the user's educational background, work history, and skill set.

[0260] The generative AI analyzes the user's past project data and performance reviews, and also evaluates their learning ability and flexibility.

[0261] 4. Users take interviews and technical tests, and the results are imported into the system.

[0262] After the interview, the interviewer (user) enters the evaluation score and comments into the system using an input form and sends them to the server.

[0263] The results of the technical tests are also entered and sent to the server.

[0264] During the interview, the emotion engine analyzes the user's emotions and transmits the emotion information to the server.

[0265] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[0266] The server analyzes the results of interviews and technical tests to evaluate the user's communication and technical skills.

[0267] Emotional data obtained through the emotion engine is also analyzed and reflected in the overall evaluation.

[0268] 6. The server uses the generated AI to update the user's skill profile.

[0269] The generative AI updates the user's skill profile based on interview and test results and emotional data.

[0270] An updated skill profile reflecting the overall assessment is generated.

[0271] 7. Enter the company's job information and the server analyzes it.

[0272] A company's recruiter (user) submits job information to the server via an input form.

[0273] The server analyzes the job information and extracts the required skills and characteristics.

[0274] 8. The server matches the user's skill profile with company job listings

[0275] The server uses generated AI to match the user's skill profile with company job postings.

[0276] Based on the matching results, optimal matching candidates are generated.

[0277] 9. The server proposes the best matching candidates to the company.

[0278] The server creates a list of the most suitable candidates and presents them to the company's recruiter's device.

[0279] The recruiter (user) checks the proposed candidate information in the review form and makes the final decision.

[0280] Specific examples

[0281] Job seeker A uploads his / her resume and skill sheet to the server. The server receives this information and uses a document analysis engine to extract A's educational background, work history, and skill set. Generative AI then generates A's skill profile based on this information, and also evaluates A's learning ability and flexibility based on past project data and performance reviews.

[0282] Next, Person A takes an online interview. When the interviewer enters the interview evaluation scores and comments into the system, the emotion engine analyzes Person A's emotions and sends the emotional information to the server. The server analyzes these results and evaluates Person A's communication skills and technical abilities, while also taking emotional information into account to make an overall evaluation.

[0283] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0284] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system enables efficient and fair talent matching, greatly improving the effectiveness of the recruitment process.

[0285] The processing flow will be explained below.

[0286] Step 1:

[0287] The user uploads their resume and skill sheet from their terminal to the server.

[0288] The user opens a dedicated upload form in the web interface and selects a resume or skill sheet file.

[0289] The user presses the upload button and the device sends these files to the server.

[0290] Step 2:

[0291] The server receives and stores the uploaded file.

[0292] The server automatically determines the format of the received file and saves it.

[0293] The server passes the saved file to the document analysis engine.

[0294] Step 3:

[0295] The server uses a document analysis engine to extract information from resumes and skill sheets.

[0296] The server extracts information such as educational background, work history, and skill sets from resumes and skill sheets as text data.

[0297] The extracted information is stored in a database.

[0298] Step 4:

[0299] The server uses a generation AI to generate a skill profile for the user.

[0300] Based on the extracted data, generative AI creates a skill profile for the user.

[0301] Generative AI analyzes past project data and performance reviews to assess learning ability and flexibility.

[0302] Step 5:

[0303] Users take interviews and technical tests, and the results are entered into the system.

[0304] After the interview, the interviewer (user) enters the evaluation score and comments into the input form and sends it to the server.

[0305] Technical test results are also entered and sent to the server.

[0306] Step 6:

[0307] The emotion engine recognizes the user's emotion and transmits the emotion information to the server.

[0308] While the user is undergoing an interview, the emotion engine analyzes the emotion data in real time and transmits it to the server.

[0309] Step 7:

[0310] The server analyzes interview results, test results, and emotional information to provide an overall evaluation of the user.

[0311] The server analyzes the interview results, test results, and emotional data received.

[0312] A comprehensive evaluation is made taking into account the user's communication skills, technical ability, and emotional data.

[0313] Step 8:

[0314] The server uses the generated AI to update the user's skill profile.

[0315] Update your skills profile with interview and test results, as well as sentiment data.

[0316] Generative AI generates a comprehensive skill profile for the user based on new data.

[0317] Step 9:

[0318] A company's recruiter (user) enters job information and sends it to the server.

[0319] Recruiters enter job information through a web interface and send it to the server.

[0320] Step 10:

[0321] The server receives and analyzes the company's job information.

[0322] The server analyzes the job information and extracts the required skills and characteristics.

[0323] The extracted information is stored in a database.

[0324] Step 11:

[0325] The server matches the user's skill profile with company job postings.

[0326] The server uses generated AI to evaluate the match between the user's skill profile and the job posting.

[0327] Based on the matching results, optimal matching candidates are generated.

[0328] Step 12:

[0329] The server proposes the best matching candidates to the company.

[0330] The server creates a list of the most suitable candidates and presents them to the recruiter's device.

[0331] The recruiter (user) checks the proposed candidate information in the review form.

[0332] In this way, the system achieves efficient and fair talent matching and optimizes the recruitment process.

[0333] Example 2

[0334] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0335] Conventional talent matching systems have low accuracy in matching applicants' skill profiles with job information, making it difficult to find suitable candidates. Furthermore, because they do not take into account applicants' emotional data, they have the problem of being unable to accurately evaluate their communication skills or interview performance. This makes it easy for mismatches to occur between companies and applicants, reducing the efficiency of the recruitment process.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for applicants to submit resumes and skill sheets, means for analyzing the submitted resumes and skill sheets, means using a generation AI to generate a skill profile of the applicant based on the analyzed information, means for importing interview results and test results, means for analyzing the imported interview results and test results to perform a comprehensive evaluation of the applicant, an emotion engine for analyzing the emotions of the applicant during the interview, and means for analyzing the applicant's emotion data and reflecting it in the comprehensive evaluation. This enables a comprehensive evaluation that includes the applicant's emotion data, thereby achieving more accurate talent matching.

[0338] "Applicant" refers to an individual who applies for a job.

[0339] A "resume" refers to a document that lists information such as an applicant's educational background, work history, and qualifications.

[0340] A "skills sheet" is a document that details an applicant's technical abilities and work experience.

[0341] "Terminal" refers to a computer device operated by a user. Examples include personal computers, smartphones, and tablets.

[0342] "Server" refers to a computer system that stores, analyzes, and provides data over a network.

[0343] "Generative AI" refers to artificial intelligence that generates new data and predictive models based on input data.

[0344] "Document analysis engine" refers to software or algorithms for extracting specific information from documents.

[0345] "Emotion engine" refers to a system or algorithm for analyzing applicants' emotions.

[0346] A "prompt sentence" refers to text data that is input into a generative AI model, and is a specific format that structures the input information.

[0347] "Job information" refers to information that describes the qualifications and job content of the personnel that a company is looking for.

[0348] "Skills profile" refers to data that integrates an applicant's educational background, work history, skills, and other evaluation information.

[0349] "Comprehensive evaluation" refers to the applicant's overall evaluation based on multiple factors.

[0350] A "matching candidate" refers to an applicant who is judged to have a high compatibility between the applicant and the company's job information.

[0351] This invention is a recruitment system that uses generative AI and an emotion engine to match job seekers (hereafter referred to as applicants) with company job information with high accuracy. The entire system consists of a terminal, a server, generative AI, a document analysis engine, an emotion engine, prompts, etc.

[0352] First, the user (applicant) uses a device (PC, smartphone, tablet, etc.) to upload their resume and skill sheet. When the user opens a dedicated upload form, selects a file, and presses the upload button, the device sends the file to the server using an HTTP POST request. The server saves the received file in a designated directory and checks the file format (PDF, DOCX, etc.).

[0353] The server then passes the saved file to a document analysis engine (such as Google Cloud Vision API) to extract text data using OCR (optical character recognition) technology. The extracted text data is then passed to a natural language processing engine (such as spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is formatted and stored in a database.

[0354] The server then inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user, with the following prompt:

[0355] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[0356] The generation AI generates a skill profile, and the server receives the output and stores it in a database.

[0357] When a user takes an online interview, the interviewer enters their evaluation scores and comments into a dedicated form and sends it from their device to the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (for example, the Affectiva SDK) analyzes the user's emotions during the interview and sends the data to the server. Emotional data is analyzed based on the user's facial expressions, tone of voice, etc.

[0358] The server integrates the interview results, test results, and emotional data it receives, and uses a natural language processing engine to evaluate the user's communication and technical skills. Based on this information, the server makes an overall evaluation of the user.

[0359] Company recruiters enter their company's job information into a dedicated form and send it to the server. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is formatted and stored in a database.

[0360] The server uses generation AI to match the applicant's skill profile with the company's job information, calculates a match score, and lists the best matching candidates. Finally, the server generates a list of the best matching candidates and notifies the company's recruiter's device. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[0361] This system enables comprehensive evaluation of applicants, including their emotional data, leading to more accurate talent matching. By using specific prompts, the generative AI can generate highly accurate skill profiles that can be matched with company job postings.

[0362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0363] Step 1:

[0364] Users upload their resumes and skill sheets to the server from their devices.

[0365] The user opens a dedicated web form and selects their file. The selected file is sent from the device to the server by pressing the upload button. The device uses an HTTP POST request to send the file to the server. The specific input is a resume or skill sheet file, and the output is a file to be saved on the server. The server checks the format of the received file and saves it in a specified directory.

[0366] Step 2:

[0367] The server analyzes the uploaded resume and skill sheet.

[0368] The server passes the saved file to a document analysis engine (e.g., Google Cloud Vision API). The document analysis engine uses OCR technology to extract text data. The specific input is the uploaded file, and the output is the extracted text data. The server then passes the extracted text data to a natural language processing engine (e.g., spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is stored in a database.

[0369] Step 3:

[0370] The server uses AI to generate a skill profile for the user.

[0371] The server inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user. The specific input is the extracted information, and the output is the generated skill profile. An example of a prompt is as follows:

[0372] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[0373] The generation AI generates a skill profile, and the server receives the output. The generated skill profile is also stored in the database.

[0374] Step 4:

[0375] Users take interviews and technical tests, and the results are input into the system.

[0376] After the user takes the online interview, the interviewer enters the evaluation score and comments into a dedicated form and sends it from the terminal to the server. The specific input is the interview evaluation score and comments, and the output is evaluation data stored on the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (e.g., Affectiva SDK) analyzes the user's facial expressions and tone of voice during the interview and sends emotional data to the server.

[0377] Step 5:

[0378] The server analyzes the interview and test results and gives the user an overall evaluation.

[0379] The server retrieves the evaluation scores and comments received from the interviewer, the results of the technical test, and emotional data from the database. The specific inputs are the evaluation scores, comments, results of the technical test, and emotional data, and the output is overall evaluation data. The comments are analyzed using a natural language processing engine to evaluate the user's communication skills and technical ability. The emotional data is analyzed to evaluate the level of tension and ability to express oneself during the interview. This information is then integrated to provide an overall evaluation of the user.

[0380] Step 6:

[0381] The server uses the generated AI to update the user's skill profile.

[0382] The server then inputs the final evaluation data back into the generation AI to generate a new skill profile. The input is the evaluation data, and the output is an updated skill profile. The generated profile is then saved in the database, replacing the previous profile.

[0383] Step 7:

[0384] Companies enter job information and the server analyzes it.

[0385] A company's recruiter enters job information into a dedicated form and sends it from their device to the server. The specific input is the job information, and the output is analyzed job data. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is stored in a database.

[0386] Step 8:

[0387] The server matches the user's skill profile with company job listings

[0388] The server uses a generation AI to match job postings with the user's skill profile. The specific inputs are the job posting and skill profile, and the output is matching candidates. A match score is calculated and the best matching candidates are listed.

[0389] Step 9:

[0390] The server proposes optimal matching candidates to the company.

[0391] The server generates a list of optimal matching candidates and notifies the company's recruiter's device. The specific input is the matching candidate list, and the output is candidate information proposed to the company's recruiter. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[0392] (Application example 2)

[0393] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0394] Traditional recruitment systems only evaluate applicants' skills and experience, without taking into account important soft skills such as the applicant's emotional state and flexibility. This makes it easy for mismatches to occur between applicants and companies, making it difficult to achieve effective talent matching. Furthermore, with the spread of online interviews, there has been a lack of means to accurately assess an applicant's emotional state. Therefore, to achieve more accurate talent matching, a comprehensive evaluation is needed that takes into account not only skills and experience, but also emotional state and flexibility.

[0395] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0396] In this invention, the server includes an emotion analysis means for analyzing the emotions of applicants and acquiring emotion data, a means for generating and updating the applicant's skill profile using a generation AI, and a means for matching the applicant's skill profile with the company's job information to generate optimal matching candidates. This enables highly accurate talent matching that also takes into account the applicant's soft skills, such as their emotional state.

[0397] An "applicant" is an individual who submits their information in response to a job opening and seeks employment.

[0398] A "resume" is a document that provides basic information about an applicant, including educational background, work history, qualifications, skills, etc.

[0399] A "skills sheet" is a document that details an applicant's technical abilities and expertise.

[0400] A "terminal" is a hardware device for inputting and outputting data, and includes personal computers, smartphones, tablets, etc.

[0401] A "server" is a high-performance computer system for processing and storing data over a network.

[0402] "Generative AI" is artificial intelligence that uses machine learning algorithms to automatically generate and update applicant skill profiles.

[0403] "Emotion analysis means" is a combination of hardware and software for analyzing the emotional state of an applicant and obtaining emotional data.

[0404] "Interview results" is data showing the results of the interviewer's evaluation of the applicant's performance and suitability.

[0405] "Technical test results" are data showing the results of tests conducted to assess the technical capabilities of applicants.

[0406] A "comprehensive evaluation" is an evaluation that takes into account the applicant's interview results, technical test results, emotional data, etc.

[0407] A "company" is an organization whose purpose is to employ people and have them perform specific tasks.

[0408] "Job information" is information that specifically specifies details of the jobs offered by a company, the skills required, recruitment conditions, etc.

[0409] A "matching candidate" is an applicant who is deemed to be a high fit after comparing the applicant's skill profile with the company's job information.

[0410] In this invention, the system for effectively matching job seekers with company recruitment information is configured using the following hardware and software.

[0411] First, job seekers (hereafter referred to as applicants) upload their resumes and skill sheets to the server using a dedicated device. The device can be a PC, smartphone, tablet, etc. The uploaded files are received by the server and analyzed by a document analysis engine. Here, educational background, work history, and skill sets are extracted from the contents of the resume and skill sheets.

[0412] The information extracted by the server using a document analysis engine is input into the generation AI, which generates a skill profile based on the applicant's educational background, work history, and skill set, and analyzes the applicant's past project data and performance reviews, as well as assessing their learning ability and flexibility. The generated skill profile can be viewed on the applicant's device or the company's device.

[0413] Next, when an applicant takes an online interview or technical test, the interviewer or test administrator uses a dedicated terminal to enter the interview results, evaluation scores, and comments into a server. At this time, an emotion analysis tool is used to analyze the applicant's emotional state, and this data is also sent to the server. The emotion analysis tool uses a device equipped with a camera and microphone, and the analysis software captures emotional data in real time.

[0414] The server integrates interview results, technical test results, and emotional data to perform a comprehensive evaluation. This allows for a comprehensive assessment of the applicant's communication skills, technical ability, and emotional state. The generating AI then updates the applicant's skill profile based on this comprehensive evaluation.

[0415] Company recruitment information is entered into the server by the company's recruiting staff via a dedicated terminal. The server analyzes the information and identifies the required skills and characteristics. This allows the job information to be matched with the applicant's skill profile, and highly suitable candidates are generated by the generation AI.

[0416] Finally, the generated candidates are listed and presented to the company's recruiter's device. The recruiter then reviews the proposed candidate information and makes a final decision. This system enables highly accurate talent matching that takes into account the applicant's skills, experience, and even emotional state.

[0417] For example, when an applicant uploads their resume and takes an online interview, sentiment analysis measures their nervousness and confidence levels, after which generative AI updates their skills profile and matches them with company job openings.

[0418] An example of a prompt for the generative AI model is, "User's resume data: {resume_data}, User's interview results: {interview_results}, Emotion data: {emotions}. Please generate the user's latest skill profile based on this data." This prompt enables advanced matching.

[0419] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0420] Step 1:

[0421] Users upload their resumes and skill sheets to the server via dedicated terminals.

[0422] Input: Resume and skill sheet file (PDF, DOCX, etc.)

[0423] Data processing: The server determines the file format and saves the received file.

[0424] Output: Saved resume and skill sheet files

[0425] Step 2:

[0426] The server uses a document analysis engine to analyze the uploaded resume or skill sheet.

[0427] Input: Saved resume and skill sheet files

[0428] Data processing: A document analysis engine extracts information on education, employment history, and skill sets.

[0429] Output: Extracted education, work history, and skill set data

[0430] Step 3:

[0431] The server uses generative AI to generate a skill profile for the applicant based on the extracted information.

[0432] Input: Extracted education, work history, and skill set data

[0433] Data processing: Generative AI analyzes input data to generate a skill profile. It also analyzes past project data and performance reviews to assess learning ability and flexibility.

[0434] Output: Generated skill profile

[0435] Step 4:

[0436] Applicants take online interviews and technical tests, and the interviewers and test administrators enter the results into a server via dedicated terminals.

[0437] Input: Interview results, evaluation scores, comments, technical test results

[0438] Data processing: The server stores the received data and, if necessary, uses emotion analysis means to obtain emotion data.

[0439] Output: Stored interview results, evaluation scores, comments, technical test results, and sentiment data

[0440] Step 5:

[0441] The server analyzes the interview results, technical test results, and emotional data obtained and makes an overall evaluation of the applicant.

[0442] Input: Stored interview results, evaluation scores, comments, technical test results, emotional data

[0443] Data processing: The server integrates the results, and the generating AI performs an overall evaluation.

[0444] Output: Comprehensively evaluated data

[0445] Step 6:

[0446] The generative AI updates the applicant's skill profile based on the overall evaluation data.

[0447] Input: Comprehensively evaluated data

[0448] Data processing: The generating AI updates the skill profile to reflect the overall evaluation.

[0449] Output: Updated skill profile

[0450] Step 7:

[0451] Job information is entered into the server by company recruiters via dedicated terminals.

[0452] Input: Job information (job details, required skills, recruitment conditions)

[0453] Data processing: The server analyzes job postings to identify required skills and characteristics.

[0454] Output: Parsed job listings

[0455] Step 8:

[0456] The server uses generative AI to match the applicant's skill profile with job information and generate the best matching candidates.

[0457] Input: Updated skills profile, parsed job information

[0458] Data processing: Generative AI matches profiles with job listings to generate highly suitable candidates.

[0459] Output: A list of possible matches

[0460] Step 9:

[0461] The generated matching candidates are then presented to the company's recruiter's device.

[0462] Input: Match candidate list

[0463] Data processing: The server converts the list into the proposed format and sends it to the terminal.

[0464] Output: A list of suggested matches

[0465] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0466] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search<url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0467] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0468] [Second embodiment]

[0469] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0470] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0471] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0472] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0473] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0475] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0476] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0477] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0478] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0479] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0480] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0481] This invention is a system that utilizes generative AI to effectively match job seekers with company job information. Below, we will explain the program processing of this system in natural language and provide specific examples.

[0482] Program processing

[0483] 1. The user uploads their resume and skill sheet from their device to the server.

[0484] A user uploads a file using a dedicated upload form.

[0485] The server receives the uploaded file and determines its format (e.g. PDF, DOCX, etc.).

[0486] 2. The server analyzes the uploaded resume and skill sheet.

[0487] The server uses a document analysis engine to extract information such as educational background, work history, and skill sets from resumes and skill sheets.

[0488] 3. The server uses the generation AI to generate a skill profile for the user.

[0489] Based on the extracted information, the generative AI generates a skill profile for the user.

[0490] At this time, past project data and performance reviews are also analyzed, and learning ability and flexibility are also evaluated.

[0491] 4. The user undergoes an interview and technical test, and the results are entered into the system.

[0492] The interviewer (user) enters the interview results and technical test results into the system through an input form.

[0493] The server receives these inputs and begins parsing them.

[0494] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[0495] The server analyzes interview results and technical test scores to evaluate communication skills and technical abilities.

[0496] Based on this, the user's skill profile is updated.

[0497] 6. Collect and analyze company job information.

[0498] Companies submit job information to the server using an input form.

[0499] The server receives the job information and analyzes the required skills and characteristics.

[0500] 7. The server matches the user's skill profile with company job listings.

[0501] The server uses generated AI to match the user's skill profile with job listings.

[0502] Based on the matching results, optimal matching candidates are generated.

[0503] 8. The server proposes the best matching candidates to the company.

[0504] The server creates a list of the generated matching candidates and presents them to the company's terminal.

[0505] The company's recruiter (user) reviews the provided candidate information and makes the final decision.

[0506] Specific examples

[0507] A job seeker, A, uploads his / her resume and skill sheet to the server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[0508] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[0509] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0510] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] The user uploads their resume and skill sheet from their terminal to the server.

[0514] The user uses the system's dedicated upload form, selects the resume or skill sheet file, and begins uploading.

[0515] The device sends the uploaded file to the server.

[0516] Step 2:

[0517] The server receives and stores the uploaded resumes and skill sheets.

[0518] The server automatically determines the file format (PDF, DOCX, etc.).

[0519] The server stores the file for passing to the analysis engine.

[0520] Step 3:

[0521] The server uses a document analysis engine to extract information from resumes and skill sheets.

[0522] The server analyzes the contents of the resume and skill sheet and extracts educational background, work history, and skill set as text data.

[0523] The server organizes the extracted data and extracts the necessary information.

[0524] Step 4:

[0525] The server uses a generation AI to generate a skill profile for the user.

[0526] The server inputs the extracted information into a generation AI, which creates a skill profile based on the user's educational background, work history, and skill set.

[0527] The generative AI performs additional analysis to assess the user's learning ability and flexibility.

[0528] Step 5:

[0529] Users take interviews and technical tests, and the results are entered into the system.

[0530] After the interview, the interviewer (user) sends the evaluation score and comments to the server using an input form.

[0531] The results of the technical tests are also entered and sent to the server.

[0532] Step 6:

[0533] The server analyzes the interview and test results and gives the user an overall evaluation.

[0534] The server analyzes the interview results received from the interviewer and evaluates the user's performance and aptitude.

[0535] Based on the scores of the technical test, the user's technical ability and expertise are evaluated.

[0536] Step 7:

[0537] The server uses the generated AI to update the user's skill profile.

[0538] The generative AI updates the user's skill profile based on interview results and technical test evaluations.

[0539] Generate an updated skills profile that reflects your overall assessment.

[0540] Step 8:

[0541] Companies enter job information.

[0542] A company's recruiter (user) submits job information to the server via an input form.

[0543] Company job postings include the required skill sets and job duties.

[0544] Step 9:

[0545] The server receives and analyzes the company's job information.

[0546] The server analyzes the job information using an analytical engine and extracts the required skills and characteristics.

[0547] The server stores the job listings in a database.

[0548] Step 10:

[0549] The server matches the user's skill profile with company job postings.

[0550] The server uses the generated AI to begin matching the user's skill profile with job listings.

[0551] Based on the matching results, the degree of skill matching and compatibility is evaluated.

[0552] Step 11:

[0553] The server generates optimal matching candidates and presents them to the company's terminal.

[0554] The server selects the best matching candidates from the matching results and generates a list.

[0555] The generated list is sent to the company's recruiter's device.

[0556] The recruiter (user) checks the proposed candidate information in the review form.

[0557] In this way, the system achieves efficient and fair talent matching.

[0558] Example 1

[0559] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0560] Conventional job change support systems have difficulty managing a wide range of information about applicants in one place and effectively matching them with companies' job openings. Furthermore, they lack the functionality to import interview and technical test results into the system and perform a comprehensive evaluation based on those results. As a result, there are cases where applicants are not properly matched with companies, which creates problems that prevent the job change process from proceeding smoothly.

[0561] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0562] In this invention, the server includes a terminal for applicants to submit resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and test results, a server that analyzes the imported interview results and test results to perform a comprehensive evaluation of the applicant, a server that collects and analyzes company job information, a generation AI that compares company job information with the applicant's skill profile and generates optimal matching candidates, a terminal for proposing the generated matching candidates to companies, a document analysis engine, a natural language processing tool, and a generation AI model for matching candidates with job information. This makes it possible to efficiently and accurately match applicants with company job information.

[0563] A resume is a document in which an applicant lists information such as their work history, educational background, and skills.

[0564] A "skills sheet" is a document in which an applicant details his or her technical skills and expertise.

[0565] A "terminal" is a device such as a computer or smartphone that is operated by a user.

[0566] A "server" is a computer system that stores and processes data on a network.

[0567] "Generative AI" is an artificial intelligence technology that generates new information and profiles based on given data.

[0568] "Interview results" refers to the evaluation and feedback of the applicant obtained through the interview.

[0569] "Test results" refer to the numerical results or evaluations of the technical tests or evaluation tests taken by the applicant.

[0570] A "skills profile" is a profile that summarizes an applicant's skills and characteristics based on analyzed information.

[0571] "Job information" refers to detailed information published by companies, such as job types, required skills, and compensation.

[0572] A "document analysis engine" is a software technology for analyzing uploaded documents and extracting necessary information.

[0573] A "natural language processing tool" is a software technology for analyzing text data and understanding human language.

[0574] A "generative AI model" is an artificial intelligence algorithm or framework that learns from massive amounts of data and generates new information and patterns.

[0575] This invention relates to a system that effectively matches job seekers with company job information. This system uses generative AI to create a skill profile of the applicant and compares it with the company's job information to achieve optimal matching.

[0576] The system consists of multiple components, including the following hardware and software:

[0577] 1. Terminal

[0578] A device such as a computer or smartphone that is operated by a user.

[0579] The terminal is used by users to upload resumes and skill sheets.

[0580] For example, a user can use a dedicated upload form to select a file, and the terminal will then send the file to the server.

[0581] 2. Server

[0582] A computer system for receiving and analyzing resumes and skill sheets.

[0583] The server uses the Python library PyMuPDF and the OCR tool Tesseract to parse the uploaded documents.

[0584] 3. Generation AI

[0585] It is an artificial intelligence technology for generating skill profiles of applicants.

[0586] For example, OpenAI's GPT-4 model is used to generate a skill profile based on the extracted information and store it in a database.

[0587] Specific examples of prompt sentences are as follows:

[0588] "Extract the following information from the job applicant's resume and skill sheet: educational background, work history, skill set, past project data, and performance review."

[0589] 4. Input Form and Analysis Tools

[0590] This is an input form for capturing interview and test results.

[0591] The server uses NLP tools (e.g., SpaCy or Gensim) to analyze the input data.

[0592] 5. Matching Engine

[0593] This is software for collecting and analyzing corporate job information.

[0594] Analyze job postings using text mining tools (e.g., NLTK).

[0595] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to assess the match between the applicant's skill profile and the company's job posting.

[0596] 6. Proposed System

[0597] This is a system that proposes the most suitable matching candidates to companies.

[0598] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiting staff reviews the candidate information provided and makes the final decision.

[0599] As a specific example, suppose a job seeker, A, uploads his / her resume and skill sheet to a server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[0600] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[0601] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0602] Finally, the server proposes information about Person A to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching. This invention makes it possible to achieve an ideal match for both job seekers and companies.

[0603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] The user uploads their resume and skill sheet from their terminal to the server.

[0606] Specifically, the user selects a file using a dedicated upload form. The terminal then sends the selected file to the server. The server receives the uploaded file and determines its format (e.g., PDF, DOCX). The input is the uploaded file, and the output is the result of determining the file format.

[0607] Step 2:

[0608] The server analyzes the uploaded resume and skill sheet.

[0609] Specifically, the server launches a document analysis engine (for example, the Python library PyMuPDF or the OCR tool Tesseract). The server uses this analysis engine to automatically extract information such as educational background, work history, and skill set from resumes and skill sheets. The input is the received file, and the output is the extracted information.

[0610] Step 3:

[0611] The server uses a generation AI to generate a skill profile for the user.

[0612] Based on the extracted information, the server uses a generative AI (for example, OpenAI's GPT-4 model) to generate a skill profile for the user. Specifically, the server uses the following prompt for the generative AI: "Please extract the following information from the job seeker's resume and skill sheet: educational background, work history, skill set, past project data, and performance review." The input is the extracted information, and the output is the generated skill profile.

[0613] Step 4:

[0614] Users take interviews and technical tests, and the results are entered into the system.

[0615] The interviewer (user) enters the interview results and technical test results into the system through an input form. The terminal sends the entered data to the server. The server analyzes the received data. An NLP tool (e.g., SpaCy or Gensim) is used for the analysis. The input is the interview results and technical test results, and the output is the analyzed data.

[0616] Step 5:

[0617] The server analyzes the interview and test results and gives the user an overall evaluation.

[0618] Specifically, the server analyzes interview results and technical test scores to evaluate the applicant's communication and technical skills. This information is used to update the user's skill profile. The input is the analyzed interview and test results, and the output is the updated skill profile.

[0619] Step 6:

[0620] Companies enter job information and the server analyzes it.

[0621] Companies enter job information into the system using an input form. The terminal sends the entered job information to the server. The server receives the job information and analyzes it for required skills and characteristics. A text mining tool (e.g., NLTK) is used for the analysis. The input is the job information, and the output is the analyzed job information.

[0622] Step 7:

[0623] The server matches the user's skill profile with company job postings.

[0624] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to match the user's skill profile with job postings. The input is the skill profile and job posting, and the output is the match and candidate matches.

[0625] Step 8:

[0626] The server proposes the best matching candidates to the company.

[0627] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiter (user) reviews the provided candidate information and makes a final decision. The input is the list of matching candidates, and the output is the company's final decision.

[0628] (Application example 1)

[0629] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0630] The manual hiring process for brick-and-mortar stores is time-consuming and labor-intensive, and matching applicants with job listings is difficult to optimize. Furthermore, the difficulty of properly assessing applicants' skills and communication abilities can lead to reduced hiring efficiency and accuracy. Furthermore, there is a lack of methods to virtually recreate interviews in a real-world store environment and evaluate applicant suitability.

[0631] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0632] In this invention, the server includes a terminal through which applicants submit their resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and technical evaluations, a server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant, a server that collects and analyzes job information from physical stores, a generation AI that compares the job information from physical stores with the applicant's skill profile and generates optimal matching candidates, and a terminal for proposing the generated matching candidates to physical stores.This makes it possible to improve the efficiency and accuracy of staff recruitment at physical stores and to increase the accuracy of applicant aptitude evaluations.

[0633] "Applicant" refers to an individual who applies for a job by submitting a resume or skill sheet.

[0634] A "resume" is a document that lists information such as an applicant's educational background, work history, and qualifications.

[0635] A "skills sheet" is a document that details an applicant's specialized skills and experience.

[0636] "Terminal" refers to the device used by applicants and companies to input, submit, and view information, specifically a smartphone or computer.

[0637] A "server" is a computer system that communicates with multiple terminals via a network and stores and processes data.

[0638] "Generative AI" refers to artificial intelligence that generates responses and actions based on input data. In particular, in this invention, it generates the applicant's skill profile and compares it with job information.

[0639] A "skills profile" is a detailed competency assessment document of an applicant that is generated based on the applicant's educational background, work history, skill set, etc.

[0640] "Interview results" refers to the evaluation results of the applicant when they were interviewed.

[0641] "Technical assessment" refers to the assessment of applicants when they are tested on specific technologies or skills.

[0642] A "comprehensive evaluation" is an overall assessment of an applicant based on a comprehensive analysis of various information such as resumes, skill sheets, interview results, and technical evaluations.

[0643] A "brick and mortar store" refers to a physical commercial establishment, such as a cafe or retail store.

[0644] "Job information" is information that describes the qualifications and job duties of the personnel that a company is looking for.

[0645] The present invention provides a system for improving the efficiency and accuracy of the staff recruitment process in brick-and-mortar stores. Specific embodiments of this system are described below.

[0646] System Configuration

[0647] The system consists of the following main components:

[0648] 1. A device for applicants to submit their resumes and skill sheets

[0649] 2. Server for analyzing submitted resumes and skill sheets

[0650] 3. Generative AI that generates skill profiles for applicants based on analyzed information

[0651] 4. Terminal for capturing interview results and technical evaluations

[0652] 5. A server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant.

[0653] 6. Server that collects and analyzes job information from brick-and-mortar stores

[0654] 7. Generative AI that matches job postings at brick-and-mortar stores with applicants' skill profiles to generate optimal matching candidates

[0655] 8. A device for proposing the generated matching candidates to the physical store

[0656] Hardware and software used

[0657] Hardware:

[0658] Smartphones and computers (devices used by applicants and brick-and-mortar stores)

[0659] Server (data analysis and storage)

[0660] Head-mounted displays (HMDs, used for virtual interviews, etc.)

[0661] software:

[0662] Generative AI models (GPT-4 and BERT)

[0663] Document analysis engine (e.g. Google Cloud Vision API)

[0664] Program processing

[0665] The server receives data from the device on which applicants submit their resumes and skill sheets. The document analysis engine on the server extracts information such as educational background, work history, and skill sets from the submitted data. The AI ​​then generates a skill profile based on the extracted data. At the same time, the server also imports interview results and technical evaluations, and performs a comprehensive evaluation.

[0666] When a brick-and-mortar store inputs job information, the server analyzes the information and identifies the required skills and characteristics. The generation AI matches the applicant's skill profile with the brick-and-mortar store's job information and generates the best matching candidates. This matching is performed by analyzing the data input into the generation AI using prompt sentences.

[0667] Finally, the generated candidates are presented to the store, where staff can review and select candidates. The store can then use touch and voice commands to check candidate information, contact them, schedule interviews, and more.

[0668] Specific examples

[0669] For example, if physical store A registers a job posting for a service staff member in the system, the generation AI will match applicant B's skill profile with store A's job posting. Applicant B had previously uploaded a resume and was evaluated for his excellent customer service skills in an online interview. The generation AI will determine that applicant B is highly suitable for store A's requirements and suggest applicant B to the store A staff member. The staff member can then check applicant B's details within the app and contact him, resulting in an efficient recruitment process.

[0670] Prompt Sentence Examples

[0671] An example of a prompt is:

[0672] "Evaluate this candidate's customer service skills and flexibility based on their resume and interview results to determine if they are an ideal match for the following job posting: (specific job posting details)"

[0673] By inputting these prompts into the generation AI, it is possible to analyze suitable candidates and propose optimal matching candidates.

[0674] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0675] Step 1:

[0676] The user uploads a resume or skill sheet from their device to the server. The user uploads a file in PDF or DOCX format using a dedicated upload form. The server receives the uploaded file and determines the file format. The input of this process is the resume or skill sheet, and the output is the file data stored on the server.

[0677] Step 2:

[0678] The server analyzes the uploaded resumes and skill sheets. The server's document analysis engine (e.g., Google Cloud Vision API) extracts information such as educational background, work history, and skill sets from the resumes and skill sheets. The input to this process is the file data saved in step 1, and the output is a dataset of the extracted information.

[0679] Step 3:

[0680] The server uses a generative AI to generate a skill profile for the user. The generative AI (e.g., GPT-4) generates the skill profile based on the extracted information. The input to this process is the dataset obtained in step 2, and the output is a skill profile. Specifically, past project data and performance reviews are also analyzed.

[0681] Step 4:

[0682] A user undergoes an interview or technical evaluation, and the results are imported into the system. The user's interview results and technical evaluation data are input from their terminal to the server. The input to this process is the interview results and technical evaluation entered by the interviewer via their terminal, and the output is the evaluation data stored on the server.

[0683] Step 5:

[0684] The server analyzes the interview results and technical evaluation and performs an overall evaluation of the user. The server evaluates communication and technical skills based on the interview results and technical evaluation. The input to this process is the evaluation data saved in step 4, and the output is an updated skill profile.

[0685] Step 6:

[0686] The server collects and analyzes job postings from brick-and-mortar stores. A brick-and-mortar store representative submits the job posting to the server using an input form. The server receives the job posting and analyzes the required skills and characteristics. The input to this process is the brick-and-mortar store's job postings, and the output is a dataset of analyzed job postings.

[0687] Step 7:

[0688] The server uses a generation AI to match the user's skill profile with job postings at brick-and-mortar stores. The generation AI uses a prompt to determine the degree of match between the skill profile and the job posting. The input to this process is the dataset obtained in steps 3 and 6, and the output is a list of the best matching candidates. An example of a specific prompt is, "Evaluate this candidate's customer service skills and flexibility based on their resume data and interview results, and determine whether they are the best match for the job posting below. Job posting: (specific job posting details)."

[0689] Step 8:

[0690] The server proposes the best candidates to the store. The generated list of candidates is displayed on a terminal in the store for the store staff to review. The input of this process is the list of best candidates, and the output is an interface for the store staff to review, contact, and schedule interviews.

[0691] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0692] This invention is a recruitment system that utilizes generative AI and an emotion engine to effectively match job seekers with companies' job information. This system recognizes the user's emotions and reflects that emotion data in evaluation and matching, thereby achieving more accurate talent matching.

[0693] Program processing

[0694] 1. The user uploads their resume and skill sheet from their device to the server.

[0695] The user uses a dedicated upload form to select a resume or skill sheet file and send it from the terminal to the server.

[0696] The server determines the file format (PDF, DOCX, etc.) and saves the received file.

[0697] 2. The server analyzes the uploaded resume and skill sheet

[0698] The server uses a document analysis engine to extract information about education, work history, and skill sets from resumes and skill sheets.

[0699] 3. The server uses the AI ​​to generate a skill profile for the user.

[0700] The server inputs the extracted information into a generation AI to generate a skill profile based on the user's educational background, work history, and skill set.

[0701] The generative AI analyzes the user's past project data and performance reviews, and also evaluates their learning ability and flexibility.

[0702] 4. Users take interviews and technical tests, and the results are imported into the system.

[0703] After the interview, the interviewer (user) enters the evaluation score and comments into the system using an input form and sends them to the server.

[0704] The results of the technical tests are also entered and sent to the server.

[0705] During the interview, the emotion engine analyzes the user's emotions and transmits the emotion information to the server.

[0706] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[0707] The server analyzes the results of interviews and technical tests to evaluate the user's communication and technical skills.

[0708] Emotional data obtained through the emotion engine is also analyzed and reflected in the overall evaluation.

[0709] 6. The server uses the generated AI to update the user's skill profile.

[0710] The generative AI updates the user's skill profile based on interview and test results and emotional data.

[0711] An updated skill profile reflecting the overall assessment is generated.

[0712] 7. Enter the company's job information and the server analyzes it.

[0713] A company's recruiter (user) submits job information to the server via an input form.

[0714] The server analyzes the job information and extracts the required skills and characteristics.

[0715] 8. The server matches the user's skill profile with company job listings

[0716] The server uses generated AI to match the user's skill profile with company job postings.

[0717] Based on the matching results, optimal matching candidates are generated.

[0718] 9. The server proposes the best matching candidates to the company.

[0719] The server creates a list of the most suitable candidates and presents them to the company's recruiter's device.

[0720] The recruiter (user) checks the proposed candidate information in the review form and makes the final decision.

[0721] Specific examples

[0722] Job seeker A uploads his / her resume and skill sheet to the server. The server receives this information and uses a document analysis engine to extract A's educational background, work history, and skill set. Generative AI then generates A's skill profile based on this information, and also evaluates A's learning ability and flexibility based on past project data and performance reviews.

[0723] Next, Person A takes an online interview. When the interviewer enters the interview evaluation scores and comments into the system, the emotion engine analyzes Person A's emotions and sends the emotional information to the server. The server analyzes these results and evaluates Person A's communication skills and technical abilities, while also taking emotional information into account to make an overall evaluation.

[0724] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0725] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system enables efficient and fair talent matching, greatly improving the effectiveness of the recruitment process.

[0726] The processing flow will be explained below.

[0727] Step 1:

[0728] The user uploads their resume and skill sheet from their terminal to the server.

[0729] The user opens a dedicated upload form in the web interface and selects a resume or skill sheet file.

[0730] The user presses the upload button and the device sends these files to the server.

[0731] Step 2:

[0732] The server receives and stores the uploaded file.

[0733] The server automatically determines the format of the received file and saves it.

[0734] The server passes the saved file to the document analysis engine.

[0735] Step 3:

[0736] The server uses a document analysis engine to extract information from resumes and skill sheets.

[0737] The server extracts information such as educational background, work history, and skill sets from resumes and skill sheets as text data.

[0738] The extracted information is stored in a database.

[0739] Step 4:

[0740] The server uses a generation AI to generate a skill profile for the user.

[0741] Based on the extracted data, generative AI creates a skill profile for the user.

[0742] Generative AI analyzes past project data and performance reviews to assess learning ability and flexibility.

[0743] Step 5:

[0744] Users take interviews and technical tests, and the results are entered into the system.

[0745] After the interview, the interviewer (user) enters the evaluation score and comments into the input form and sends it to the server.

[0746] Technical test results are also entered and sent to the server.

[0747] Step 6:

[0748] The emotion engine recognizes the user's emotion and transmits the emotion information to the server.

[0749] While the user is undergoing an interview, the emotion engine analyzes the emotion data in real time and transmits it to the server.

[0750] Step 7:

[0751] The server analyzes interview results, test results, and emotional information to provide an overall evaluation of the user.

[0752] The server analyzes the interview results, test results, and emotional data received.

[0753] A comprehensive evaluation is made taking into account the user's communication skills, technical ability, and emotional data.

[0754] Step 8:

[0755] The server uses the generated AI to update the user's skill profile.

[0756] Update your skills profile with interview and test results, as well as sentiment data.

[0757] Generative AI generates a comprehensive skill profile for the user based on new data.

[0758] Step 9:

[0759] A company's recruiter (user) enters job information and sends it to the server.

[0760] Recruiters enter job information through a web interface and send it to the server.

[0761] Step 10:

[0762] The server receives and analyzes the company's job information.

[0763] The server analyzes the job information and extracts the required skills and characteristics.

[0764] The extracted information is stored in a database.

[0765] Step 11:

[0766] The server matches the user's skill profile with company job postings.

[0767] The server uses generated AI to evaluate the match between the user's skill profile and the job posting.

[0768] Based on the matching results, optimal matching candidates are generated.

[0769] Step 12:

[0770] The server proposes the best matching candidates to the company.

[0771] The server creates a list of the most suitable candidates and presents them to the recruiter's device.

[0772] The recruiter (user) checks the proposed candidate information in the review form.

[0773] In this way, the system achieves efficient and fair talent matching and optimizes the recruitment process.

[0774] Example 2

[0775] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0776] Conventional talent matching systems have low accuracy in matching applicants' skill profiles with job information, making it difficult to find suitable candidates. Furthermore, because they do not take into account applicants' emotional data, they have the problem of being unable to accurately evaluate their communication skills or interview performance. This makes it easy for mismatches to occur between companies and applicants, reducing the efficiency of the recruitment process.

[0777] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0778] In this invention, the server includes means for applicants to submit resumes and skill sheets, means for analyzing the submitted resumes and skill sheets, means using a generation AI to generate a skill profile of the applicant based on the analyzed information, means for importing interview results and test results, means for analyzing the imported interview results and test results to perform a comprehensive evaluation of the applicant, an emotion engine for analyzing the emotions of the applicant during the interview, and means for analyzing the applicant's emotion data and reflecting it in the comprehensive evaluation. This enables a comprehensive evaluation that includes the applicant's emotion data, thereby achieving more accurate talent matching.

[0779] "Applicant" refers to an individual who applies for a job.

[0780] A "resume" refers to a document that lists information such as an applicant's educational background, work history, and qualifications.

[0781] A "skills sheet" is a document that details an applicant's technical abilities and work experience.

[0782] "Terminal" refers to a computer device operated by a user. Examples include personal computers, smartphones, and tablets.

[0783] "Server" refers to a computer system that stores, analyzes, and provides data over a network.

[0784] "Generative AI" refers to artificial intelligence that generates new data and predictive models based on input data.

[0785] "Document analysis engine" refers to software or algorithms for extracting specific information from documents.

[0786] "Emotion engine" refers to a system or algorithm for analyzing applicants' emotions.

[0787] A "prompt sentence" refers to text data that is input into a generative AI model, and is a specific format that structures the input information.

[0788] "Job information" refers to information that describes the qualifications and job content of the personnel that a company is looking for.

[0789] "Skills profile" refers to data that integrates an applicant's educational background, work history, skills, and other evaluation information.

[0790] "Comprehensive evaluation" refers to the applicant's overall evaluation based on multiple factors.

[0791] A "matching candidate" refers to an applicant who is judged to have a high compatibility between the applicant and the company's job information.

[0792] This invention is a recruitment system that uses generative AI and an emotion engine to match job seekers (hereafter referred to as applicants) with company job information with high accuracy. The entire system consists of a terminal, a server, generative AI, a document analysis engine, an emotion engine, prompts, etc.

[0793] First, the user (applicant) uses a device (PC, smartphone, tablet, etc.) to upload their resume and skill sheet. When the user opens a dedicated upload form, selects a file, and presses the upload button, the device sends the file to the server using an HTTP POST request. The server saves the received file in a designated directory and checks the file format (PDF, DOCX, etc.).

[0794] The server then passes the saved file to a document analysis engine (such as Google Cloud Vision API) to extract text data using OCR (optical character recognition) technology. The extracted text data is then passed to a natural language processing engine (such as spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is formatted and stored in a database.

[0795] The server then inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user, with the following prompt:

[0796] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[0797] The generation AI generates a skill profile, and the server receives the output and stores it in a database.

[0798] When a user takes an online interview, the interviewer enters their evaluation scores and comments into a dedicated form and sends it from their device to the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (for example, the Affectiva SDK) analyzes the user's emotions during the interview and sends the data to the server. Emotional data is analyzed based on the user's facial expressions, tone of voice, etc.

[0799] The server integrates the interview results, test results, and emotional data it receives, and uses a natural language processing engine to evaluate the user's communication and technical skills. Based on this information, the server makes an overall evaluation of the user.

[0800] Company recruiters enter their company's job information into a dedicated form and send it to the server. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is formatted and stored in a database.

[0801] The server uses generation AI to match the applicant's skill profile with the company's job information, calculates a match score, and lists the best matching candidates. Finally, the server generates a list of the best matching candidates and notifies the company's recruiter's device. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[0802] This system enables comprehensive evaluation of applicants, including their emotional data, leading to more accurate talent matching. By using specific prompts, the generative AI can generate highly accurate skill profiles that can be matched with company job postings.

[0803] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0804] Step 1:

[0805] Users upload their resumes and skill sheets to the server from their devices.

[0806] The user opens a dedicated web form and selects their file. The selected file is sent from the device to the server by pressing the upload button. The device uses an HTTP POST request to send the file to the server. The specific input is a resume or skill sheet file, and the output is a file to be saved on the server. The server checks the format of the received file and saves it in a specified directory.

[0807] Step 2:

[0808] The server analyzes the uploaded resume and skill sheet.

[0809] The server passes the saved file to a document analysis engine (e.g., Google Cloud Vision API). The document analysis engine uses OCR technology to extract text data. The specific input is the uploaded file, and the output is the extracted text data. The server then passes the extracted text data to a natural language processing engine (e.g., spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is stored in a database.

[0810] Step 3:

[0811] The server uses AI to generate a skill profile for the user.

[0812] The server inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user. The specific input is the extracted information, and the output is the generated skill profile. An example of a prompt is as follows:

[0813] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[0814] The generation AI generates a skill profile, and the server receives the output. The generated skill profile is also stored in the database.

[0815] Step 4:

[0816] Users take interviews and technical tests, and the results are input into the system.

[0817] After the user takes the online interview, the interviewer enters the evaluation score and comments into a dedicated form and sends it from the terminal to the server. The specific input is the interview evaluation score and comments, and the output is evaluation data stored on the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (e.g., Affectiva SDK) analyzes the user's facial expressions and tone of voice during the interview and sends emotional data to the server.

[0818] Step 5:

[0819] The server analyzes the interview and test results and gives the user an overall evaluation.

[0820] The server retrieves the evaluation scores and comments received from the interviewer, the results of the technical test, and emotional data from the database. The specific inputs are the evaluation scores, comments, results of the technical test, and emotional data, and the output is overall evaluation data. The comments are analyzed using a natural language processing engine to evaluate the user's communication skills and technical ability. The emotional data is analyzed to evaluate the level of tension and ability to express oneself during the interview. This information is then integrated to provide an overall evaluation of the user.

[0821] Step 6:

[0822] The server uses the generated AI to update the user's skill profile.

[0823] The server then inputs the final evaluation data back into the generation AI to generate a new skill profile. The input is the evaluation data, and the output is an updated skill profile. The generated profile is then saved in the database, replacing the previous profile.

[0824] Step 7:

[0825] Companies enter job information and the server analyzes it.

[0826] A company's recruiter enters job information into a dedicated form and sends it from their device to the server. The specific input is the job information, and the output is analyzed job data. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is stored in a database.

[0827] Step 8:

[0828] The server matches the user's skill profile with company job listings

[0829] The server uses a generation AI to match job postings with the user's skill profile. The specific inputs are the job posting and skill profile, and the output is matching candidates. A match score is calculated and the best matching candidates are listed.

[0830] Step 9:

[0831] The server proposes optimal matching candidates to the company.

[0832] The server generates a list of optimal matching candidates and notifies the company's recruiter's device. The specific input is the matching candidate list, and the output is candidate information proposed to the company's recruiter. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[0833] (Application example 2)

[0834] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0835] Traditional recruitment systems only evaluate applicants' skills and experience, without taking into account important soft skills such as the applicant's emotional state and flexibility. This makes it easy for mismatches to occur between applicants and companies, making it difficult to achieve effective talent matching. Furthermore, with the spread of online interviews, there has been a lack of means to accurately assess an applicant's emotional state. Therefore, to achieve more accurate talent matching, a comprehensive evaluation is needed that takes into account not only skills and experience, but also emotional state and flexibility.

[0836] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0837] In this invention, the server includes an emotion analysis means for analyzing the emotions of applicants and acquiring emotion data, a means for generating and updating the applicant's skill profile using a generation AI, and a means for matching the applicant's skill profile with the company's job information to generate optimal matching candidates. This enables highly accurate talent matching that also takes into account the applicant's soft skills, such as their emotional state.

[0838] An "applicant" is an individual who submits their information in response to a job opening and seeks employment.

[0839] A "resume" is a document that provides basic information about an applicant, including educational background, work history, qualifications, skills, etc.

[0840] A "skills sheet" is a document that details an applicant's technical abilities and expertise.

[0841] A "terminal" is a hardware device for inputting and outputting data, and includes personal computers, smartphones, tablets, etc.

[0842] A "server" is a high-performance computer system for processing and storing data over a network.

[0843] "Generative AI" is artificial intelligence that uses machine learning algorithms to automatically generate and update applicant skill profiles.

[0844] "Emotion analysis means" is a combination of hardware and software for analyzing the emotional state of an applicant and obtaining emotional data.

[0845] "Interview results" is data showing the results of the interviewer's evaluation of the applicant's performance and suitability.

[0846] "Technical test results" are data showing the results of tests conducted to assess the technical capabilities of applicants.

[0847] A "comprehensive evaluation" is an evaluation that takes into account the applicant's interview results, technical test results, emotional data, etc.

[0848] A "company" is an organization whose purpose is to employ people and have them perform specific tasks.

[0849] "Job information" is information that specifically specifies details of the jobs offered by a company, the skills required, recruitment conditions, etc.

[0850] A "matching candidate" is an applicant who is deemed to be a high fit after comparing the applicant's skill profile with the company's job information.

[0851] In this invention, the system for effectively matching job seekers with company recruitment information is configured using the following hardware and software.

[0852] First, job seekers (hereafter referred to as applicants) upload their resumes and skill sheets to the server using a dedicated device. The device can be a PC, smartphone, tablet, etc. The uploaded files are received by the server and analyzed by a document analysis engine. Here, educational background, work history, and skill sets are extracted from the contents of the resume and skill sheets.

[0853] The information extracted by the server using a document analysis engine is input into the generation AI, which generates a skill profile based on the applicant's educational background, work history, and skill set, and analyzes the applicant's past project data and performance reviews, as well as assessing their learning ability and flexibility. The generated skill profile can be viewed on the applicant's device or the company's device.

[0854] Next, when an applicant takes an online interview or technical test, the interviewer or test administrator uses a dedicated terminal to enter the interview results, evaluation scores, and comments into a server. At this time, an emotion analysis tool is used to analyze the applicant's emotional state, and this data is also sent to the server. The emotion analysis tool uses a device equipped with a camera and microphone, and the analysis software captures emotional data in real time.

[0855] The server integrates interview results, technical test results, and emotional data to perform a comprehensive evaluation. This allows for a comprehensive assessment of the applicant's communication skills, technical ability, and emotional state. The generating AI then updates the applicant's skill profile based on this comprehensive evaluation.

[0856] Company recruitment information is entered into the server by the company's recruiting staff via a dedicated terminal. The server analyzes the information and identifies the required skills and characteristics. This allows the job information to be matched with the applicant's skill profile, and highly suitable candidates are generated by the generation AI.

[0857] Finally, the generated candidates are listed and presented to the company's recruiter's device. The recruiter then reviews the proposed candidate information and makes a final decision. This system enables highly accurate talent matching that takes into account the applicant's skills, experience, and even emotional state.

[0858] For example, when an applicant uploads their resume and takes an online interview, sentiment analysis measures their nervousness and confidence levels, after which generative AI updates their skills profile and matches them with company job openings.

[0859] An example of a prompt for the generative AI model is, "User's resume data: {resume_data}, User's interview results: {interview_results}, Emotion data: {emotions}. Please generate the user's latest skill profile based on this data." This prompt enables advanced matching.

[0860] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0861] Step 1:

[0862] Users upload their resumes and skill sheets to the server via dedicated terminals.

[0863] Input: Resume and skill sheet file (PDF, DOCX, etc.)

[0864] Data processing: The server determines the file format and saves the received file.

[0865] Output: Saved resume and skill sheet files

[0866] Step 2:

[0867] The server uses a document analysis engine to analyze the uploaded resume or skill sheet.

[0868] Input: Saved resume and skill sheet files

[0869] Data processing: A document analysis engine extracts information on education, employment history, and skill sets.

[0870] Output: Extracted education, work history, and skill set data

[0871] Step 3:

[0872] The server uses generative AI to generate a skill profile for the applicant based on the extracted information.

[0873] Input: Extracted education, work history, and skill set data

[0874] Data processing: Generative AI analyzes input data to generate a skill profile. It also analyzes past project data and performance reviews to assess learning ability and flexibility.

[0875] Output: Generated skill profile

[0876] Step 4:

[0877] Applicants take online interviews and technical tests, and the interviewers and test administrators enter the results into a server via dedicated terminals.

[0878] Input: Interview results, evaluation scores, comments, technical test results

[0879] Data processing: The server stores the received data and, if necessary, uses emotion analysis means to obtain emotion data.

[0880] Output: Stored interview results, evaluation scores, comments, technical test results, and sentiment data

[0881] Step 5:

[0882] The server analyzes the interview results, technical test results, and emotional data obtained and makes an overall evaluation of the applicant.

[0883] Input: Stored interview results, evaluation scores, comments, technical test results, emotional data

[0884] Data processing: The server integrates the results, and the generating AI performs an overall evaluation.

[0885] Output: Comprehensively evaluated data

[0886] Step 6:

[0887] The generative AI updates the applicant's skill profile based on the overall evaluation data.

[0888] Input: Comprehensively evaluated data

[0889] Data processing: The generating AI updates the skill profile to reflect the overall evaluation.

[0890] Output: Updated skill profile

[0891] Step 7:

[0892] Job information is entered into the server by company recruiters via dedicated terminals.

[0893] Input: Job information (job details, required skills, recruitment conditions)

[0894] Data processing: The server analyzes job postings to identify required skills and characteristics.

[0895] Output: Parsed job listings

[0896] Step 8:

[0897] The server uses generative AI to match the applicant's skill profile with job information and generate the best matching candidates.

[0898] Input: Updated skills profile, parsed job information

[0899] Data processing: Generative AI matches profiles with job listings to generate highly suitable candidates.

[0900] Output: A list of possible matches

[0901] Step 9:

[0902] The generated matching candidates are then presented to the company's recruiter's device.

[0903] Input: Match candidate list

[0904] Data processing: The server converts the list into the proposed format and sends it to the terminal.

[0905] Output: A list of suggested matches

[0906] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0907] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0908] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0909] [Third embodiment]

[0910] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0911] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0912] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0913] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0914] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0915] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0916] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0917] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0918] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0919] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0920] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0921] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0922] This invention is a system that utilizes generative AI to effectively match job seekers with company job information. Below, we will explain the program processing of this system in natural language and provide specific examples.

[0923] Program processing

[0924] 1. The user uploads their resume and skill sheet from their device to the server.

[0925] A user uploads a file using a dedicated upload form.

[0926] The server receives the uploaded file and determines its format (e.g. PDF, DOCX, etc.).

[0927] 2. The server analyzes the uploaded resume and skill sheet.

[0928] The server uses a document analysis engine to extract information such as educational background, work history, and skill sets from resumes and skill sheets.

[0929] 3. The server uses the generation AI to generate a skill profile for the user.

[0930] Based on the extracted information, the generative AI generates a skill profile for the user.

[0931] At this time, past project data and performance reviews are also analyzed, and learning ability and flexibility are also evaluated.

[0932] 4. The user undergoes an interview and technical test, and the results are entered into the system.

[0933] The interviewer (user) enters the interview results and technical test results into the system through an input form.

[0934] The server receives these inputs and begins parsing them.

[0935] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[0936] The server analyzes interview results and technical test scores to evaluate communication skills and technical abilities.

[0937] Based on this, the user's skill profile is updated.

[0938] 6. Collect and analyze company job information.

[0939] Companies submit job information to the server using an input form.

[0940] The server receives the job information and analyzes the required skills and characteristics.

[0941] 7. The server matches the user's skill profile with company job listings.

[0942] The server uses generated AI to match the user's skill profile with job listings.

[0943] Based on the matching results, optimal matching candidates are generated.

[0944] 8. The server proposes the best matching candidates to the company.

[0945] The server creates a list of the generated matching candidates and presents them to the company's terminal.

[0946] The company's recruiter (user) reviews the provided candidate information and makes the final decision.

[0947] Specific examples

[0948] A job seeker, A, uploads his / her resume and skill sheet to the server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[0949] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[0950] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[0951] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching.

[0952] The processing flow will be explained below.

[0953] Step 1:

[0954] The user uploads their resume and skill sheet from their terminal to the server.

[0955] The user uses the system's dedicated upload form, selects the resume or skill sheet file, and begins uploading.

[0956] The device sends the uploaded file to the server.

[0957] Step 2:

[0958] The server receives and stores the uploaded resumes and skill sheets.

[0959] The server automatically determines the file format (PDF, DOCX, etc.).

[0960] The server stores the file for passing to the analysis engine.

[0961] Step 3:

[0962] The server uses a document analysis engine to extract information from resumes and skill sheets.

[0963] The server analyzes the contents of the resume and skill sheet and extracts educational background, work history, and skill set as text data.

[0964] The server organizes the extracted data and extracts the necessary information.

[0965] Step 4:

[0966] The server uses a generation AI to generate a skill profile for the user.

[0967] The server inputs the extracted information into a generation AI, which creates a skill profile based on the user's educational background, work history, and skill set.

[0968] The generative AI performs additional analysis to assess the user's learning ability and flexibility.

[0969] Step 5:

[0970] Users take interviews and technical tests, and the results are entered into the system.

[0971] After the interview, the interviewer (user) sends the evaluation score and comments to the server using an input form.

[0972] The results of the technical tests are also entered and sent to the server.

[0973] Step 6:

[0974] The server analyzes the interview and test results and gives the user an overall evaluation.

[0975] The server analyzes the interview results received from the interviewer and evaluates the user's performance and aptitude.

[0976] Based on the scores of the technical test, the user's technical ability and expertise are evaluated.

[0977] Step 7:

[0978] The server uses the generated AI to update the user's skill profile.

[0979] The generative AI updates the user's skill profile based on interview results and technical test evaluations.

[0980] Generate an updated skills profile that reflects your overall assessment.

[0981] Step 8:

[0982] Companies enter job information.

[0983] A company's recruiter (user) submits job information to the server via an input form.

[0984] Company job postings include the required skill sets and job duties.

[0985] Step 9:

[0986] The server receives and analyzes the company's job information.

[0987] The server analyzes the job information using an analytical engine and extracts the required skills and characteristics.

[0988] The server stores the job listings in a database.

[0989] Step 10:

[0990] The server matches the user's skill profile with company job postings.

[0991] The server uses the generated AI to begin matching the user's skill profile with job listings.

[0992] Based on the matching results, the degree of skill matching and compatibility is evaluated.

[0993] Step 11:

[0994] The server generates optimal matching candidates and presents them to the company's terminal.

[0995] The server selects the best matching candidates from the matching results and generates a list.

[0996] The generated list is sent to the company's recruiter's device.

[0997] The recruiter (user) checks the proposed candidate information in the review form.

[0998] In this way, the system achieves efficient and fair talent matching.

[0999] Example 1

[1000] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1001] Conventional job change support systems have difficulty managing a wide range of information about applicants in one place and effectively matching them with companies' job openings. Furthermore, they lack the functionality to import interview and technical test results into the system and perform a comprehensive evaluation based on those results. As a result, there are cases where applicants are not properly matched with companies, which creates problems that prevent the job change process from proceeding smoothly.

[1002] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1003] In this invention, the server includes a terminal for applicants to submit resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and test results, a server that analyzes the imported interview results and test results to perform a comprehensive evaluation of the applicant, a server that collects and analyzes company job information, a generation AI that compares company job information with the applicant's skill profile and generates optimal matching candidates, a terminal for proposing the generated matching candidates to companies, a document analysis engine, a natural language processing tool, and a generation AI model for matching candidates with job information. This makes it possible to efficiently and accurately match applicants with company job information.

[1004] A resume is a document in which an applicant lists information such as their work history, educational background, and skills.

[1005] A "skills sheet" is a document in which an applicant details his or her technical skills and expertise.

[1006] A "terminal" is a device such as a computer or smartphone that is operated by a user.

[1007] A "server" is a computer system that stores and processes data on a network.

[1008] "Generative AI" is an artificial intelligence technology that generates new information and profiles based on given data.

[1009] "Interview results" refers to the evaluation and feedback of the applicant obtained through the interview.

[1010] "Test results" refer to the numerical results or evaluations of the technical tests or evaluation tests taken by the applicant.

[1011] A "skills profile" is a profile that summarizes an applicant's skills and characteristics based on analyzed information.

[1012] "Job information" refers to detailed information published by companies, such as job types, required skills, and compensation.

[1013] A "document analysis engine" is a software technology for analyzing uploaded documents and extracting necessary information.

[1014] A "natural language processing tool" is a software technology for analyzing text data and understanding human language.

[1015] A "generative AI model" is an artificial intelligence algorithm or framework that learns from massive amounts of data and generates new information and patterns.

[1016] This invention relates to a system that effectively matches job seekers with company job information. This system uses generative AI to create a skill profile of the applicant and compares it with the company's job information to achieve optimal matching.

[1017] The system consists of multiple components, including the following hardware and software:

[1018] 1. Terminal

[1019] A device such as a computer or smartphone that is operated by a user.

[1020] The terminal is used by users to upload resumes and skill sheets.

[1021] For example, a user can use a dedicated upload form to select a file, and the terminal will then send the file to the server.

[1022] 2. Server

[1023] A computer system for receiving and analyzing resumes and skill sheets.

[1024] The server uses the Python library PyMuPDF and the OCR tool Tesseract to parse the uploaded documents.

[1025] 3. Generation AI

[1026] It is an artificial intelligence technology for generating skill profiles of applicants.

[1027] For example, OpenAI's GPT-4 model is used to generate a skill profile based on the extracted information and store it in a database.

[1028] Specific examples of prompt sentences are as follows:

[1029] "Extract the following information from the job applicant's resume and skill sheet: educational background, work history, skill set, past project data, and performance review."

[1030] 4. Input Form and Analysis Tools

[1031] This is an input form for capturing interview and test results.

[1032] The server uses NLP tools (e.g., SpaCy or Gensim) to analyze the input data.

[1033] 5. Matching Engine

[1034] This is software for collecting and analyzing corporate job information.

[1035] Analyze job postings using text mining tools (e.g., NLTK).

[1036] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to assess the match between the applicant's skill profile and the company's job posting.

[1037] 6. Proposed System

[1038] This is a system that proposes the most suitable matching candidates to companies.

[1039] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiting staff reviews the candidate information provided and makes the final decision.

[1040] As a specific example, suppose a job seeker, A, uploads his / her resume and skill sheet to a server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[1041] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[1042] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[1043] Finally, the server proposes information about Person A to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching. This invention makes it possible to achieve an ideal match for both job seekers and companies.

[1044] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1045] Step 1:

[1046] The user uploads their resume and skill sheet from their terminal to the server.

[1047] Specifically, the user selects a file using a dedicated upload form. The terminal then sends the selected file to the server. The server receives the uploaded file and determines its format (e.g., PDF, DOCX). The input is the uploaded file, and the output is the result of determining the file format.

[1048] Step 2:

[1049] The server analyzes the uploaded resume and skill sheet.

[1050] Specifically, the server launches a document analysis engine (for example, the Python library PyMuPDF or the OCR tool Tesseract). The server uses this analysis engine to automatically extract information such as educational background, work history, and skill set from resumes and skill sheets. The input is the received file, and the output is the extracted information.

[1051] Step 3:

[1052] The server uses a generation AI to generate a skill profile for the user.

[1053] Based on the extracted information, the server uses a generative AI (for example, OpenAI's GPT-4 model) to generate a skill profile for the user. Specifically, the server uses the following prompt for the generative AI: "Please extract the following information from the job seeker's resume and skill sheet: educational background, work history, skill set, past project data, and performance review." The input is the extracted information, and the output is the generated skill profile.

[1054] Step 4:

[1055] Users take interviews and technical tests, and the results are entered into the system.

[1056] The interviewer (user) enters the interview results and technical test results into the system through an input form. The terminal sends the entered data to the server. The server analyzes the received data. An NLP tool (e.g., SpaCy or Gensim) is used for the analysis. The input is the interview results and technical test results, and the output is the analyzed data.

[1057] Step 5:

[1058] The server analyzes the interview and test results and gives the user an overall evaluation.

[1059] Specifically, the server analyzes interview results and technical test scores to evaluate the applicant's communication and technical skills. This information is used to update the user's skill profile. The input is the analyzed interview and test results, and the output is the updated skill profile.

[1060] Step 6:

[1061] Companies enter job information and the server analyzes it.

[1062] Companies enter job information into the system using an input form. The terminal sends the entered job information to the server. The server receives the job information and analyzes it for required skills and characteristics. A text mining tool (e.g., NLTK) is used for the analysis. The input is the job information, and the output is the analyzed job information.

[1063] Step 7:

[1064] The server matches the user's skill profile with company job postings.

[1065] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to match the user's skill profile with job postings. The input is the skill profile and job posting, and the output is the match and candidate matches.

[1066] Step 8:

[1067] The server proposes the best matching candidates to the company.

[1068] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiter (user) reviews the provided candidate information and makes a final decision. The input is the list of matching candidates, and the output is the company's final decision.

[1069] (Application example 1)

[1070] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1071] The manual hiring process for brick-and-mortar stores is time-consuming and labor-intensive, and matching applicants with job listings is difficult to optimize. Furthermore, the difficulty of properly assessing applicants' skills and communication abilities can lead to reduced hiring efficiency and accuracy. Furthermore, there is a lack of methods to virtually recreate interviews in a real-world store environment and evaluate applicant suitability.

[1072] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1073] In this invention, the server includes a terminal through which applicants submit their resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and technical evaluations, a server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant, a server that collects and analyzes job information from physical stores, a generation AI that compares the job information from physical stores with the applicant's skill profile and generates optimal matching candidates, and a terminal for proposing the generated matching candidates to physical stores.This makes it possible to improve the efficiency and accuracy of staff recruitment at physical stores and to increase the accuracy of applicant aptitude evaluations.

[1074] "Applicant" refers to an individual who applies for a job by submitting a resume or skill sheet.

[1075] A "resume" is a document that lists information such as an applicant's educational background, work history, and qualifications.

[1076] A "skills sheet" is a document that details an applicant's specialized skills and experience.

[1077] "Terminal" refers to the device used by applicants and companies to input, submit, and view information, specifically a smartphone or computer.

[1078] A "server" is a computer system that communicates with multiple terminals via a network and stores and processes data.

[1079] "Generative AI" refers to artificial intelligence that generates responses and actions based on input data. In particular, in this invention, it generates the applicant's skill profile and compares it with job information.

[1080] A "skills profile" is a detailed competency assessment document of an applicant that is generated based on the applicant's educational background, work history, skill set, etc.

[1081] "Interview results" refers to the evaluation results of the applicant when they were interviewed.

[1082] "Technical assessment" refers to the assessment of applicants when they are tested on specific technologies or skills.

[1083] A "comprehensive evaluation" is an overall assessment of an applicant based on a comprehensive analysis of various information such as resumes, skill sheets, interview results, and technical evaluations.

[1084] A "brick and mortar store" refers to a physical commercial establishment, such as a cafe or retail store.

[1085] "Job information" is information that describes the qualifications and job duties of the personnel that a company is looking for.

[1086] The present invention provides a system for improving the efficiency and accuracy of the staff recruitment process in brick-and-mortar stores. Specific embodiments of this system are described below.

[1087] System Configuration

[1088] The system consists of the following main components:

[1089] 1. A device for applicants to submit their resumes and skill sheets

[1090] 2. Server for analyzing submitted resumes and skill sheets

[1091] 3. Generative AI that generates skill profiles for applicants based on analyzed information

[1092] 4. Terminal for capturing interview results and technical evaluations

[1093] 5. A server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant.

[1094] 6. Server that collects and analyzes job information from brick-and-mortar stores

[1095] 7. Generative AI that matches job postings at brick-and-mortar stores with applicants' skill profiles to generate optimal matching candidates

[1096] 8. A device for proposing the generated matching candidates to the physical store

[1097] Hardware and software used

[1098] Hardware:

[1099] Smartphones and computers (devices used by applicants and brick-and-mortar stores)

[1100] Server (data analysis and storage)

[1101] Head-mounted displays (HMDs, used for virtual interviews, etc.)

[1102] software:

[1103] Generative AI models (GPT-4 and BERT)

[1104] Document analysis engine (e.g. Google Cloud Vision API)

[1105] Program processing

[1106] The server receives data from the device on which applicants submit their resumes and skill sheets. The document analysis engine on the server extracts information such as educational background, work history, and skill sets from the submitted data. The AI ​​then generates a skill profile based on the extracted data. At the same time, the server also imports interview results and technical evaluations, and performs a comprehensive evaluation.

[1107] When a brick-and-mortar store inputs job information, the server analyzes the information and identifies the required skills and characteristics. The generation AI matches the applicant's skill profile with the brick-and-mortar store's job information and generates the best matching candidates. This matching is performed by analyzing the data input into the generation AI using prompt sentences.

[1108] Finally, the generated candidates are presented to the store, where staff can review and select candidates. The store can then use touch and voice commands to check candidate information, contact them, schedule interviews, and more.

[1109] Specific examples

[1110] For example, if physical store A registers a job posting for a service staff member in the system, the generation AI will match applicant B's skill profile with store A's job posting. Applicant B had previously uploaded a resume and was evaluated for his excellent customer service skills in an online interview. The generation AI will determine that applicant B is highly suitable for store A's requirements and suggest applicant B to the store A staff member. The staff member can then check applicant B's details within the app and contact him, resulting in an efficient recruitment process.

[1111] Prompt Sentence Examples

[1112] An example of a prompt is:

[1113] "Evaluate this candidate's customer service skills and flexibility based on their resume and interview results to determine if they are an ideal match for the following job posting: (specific job posting details)"

[1114] By inputting these prompts into the generation AI, it is possible to analyze suitable candidates and propose optimal matching candidates.

[1115] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1116] Step 1:

[1117] The user uploads a resume or skill sheet from their device to the server. The user uploads a file in PDF or DOCX format using a dedicated upload form. The server receives the uploaded file and determines the file format. The input of this process is the resume or skill sheet, and the output is the file data stored on the server.

[1118] Step 2:

[1119] The server analyzes the uploaded resumes and skill sheets. The server's document analysis engine (e.g., Google Cloud Vision API) extracts information such as educational background, work history, and skill sets from the resumes and skill sheets. The input to this process is the file data saved in step 1, and the output is a dataset of the extracted information.

[1120] Step 3:

[1121] The server uses a generative AI to generate a skill profile for the user. The generative AI (e.g., GPT-4) generates the skill profile based on the extracted information. The input to this process is the dataset obtained in step 2, and the output is a skill profile. Specifically, past project data and performance reviews are also analyzed.

[1122] Step 4:

[1123] A user undergoes an interview or technical evaluation, and the results are imported into the system. The user's interview results and technical evaluation data are input from their terminal to the server. The input to this process is the interview results and technical evaluation entered by the interviewer via their terminal, and the output is the evaluation data stored on the server.

[1124] Step 5:

[1125] The server analyzes the interview results and technical evaluation and performs an overall evaluation of the user. The server evaluates communication and technical skills based on the interview results and technical evaluation. The input to this process is the evaluation data saved in step 4, and the output is an updated skill profile.

[1126] Step 6:

[1127] The server collects and analyzes job postings from brick-and-mortar stores. A brick-and-mortar store representative submits the job posting to the server using an input form. The server receives the job posting and analyzes the required skills and characteristics. The input to this process is the brick-and-mortar store's job postings, and the output is a dataset of analyzed job postings.

[1128] Step 7:

[1129] The server uses a generation AI to match the user's skill profile with job postings at brick-and-mortar stores. The generation AI uses a prompt to determine the degree of match between the skill profile and the job posting. The input to this process is the dataset obtained in steps 3 and 6, and the output is a list of the best matching candidates. An example of a specific prompt is, "Evaluate this candidate's customer service skills and flexibility based on their resume data and interview results, and determine whether they are the best match for the job posting below. Job posting: (specific job posting details)."

[1130] Step 8:

[1131] The server proposes the best candidates to the store. The generated list of candidates is displayed on a terminal in the store for the store staff to review. The input of this process is the list of best candidates, and the output is an interface for the store staff to review, contact, and schedule interviews.

[1132] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1133] This invention is a recruitment system that utilizes generative AI and an emotion engine to effectively match job seekers with companies' job information. This system recognizes the user's emotions and reflects that emotion data in evaluation and matching, thereby achieving more accurate talent matching.

[1134] Program processing

[1135] 1. The user uploads their resume and skill sheet from their device to the server.

[1136] The user uses a dedicated upload form to select a resume or skill sheet file and send it from the terminal to the server.

[1137] The server determines the file format (PDF, DOCX, etc.) and saves the received file.

[1138] 2. The server analyzes the uploaded resume and skill sheet

[1139] The server uses a document analysis engine to extract information about education, work history, and skill sets from resumes and skill sheets.

[1140] 3. The server uses the AI ​​to generate a skill profile for the user.

[1141] The server inputs the extracted information into a generation AI to generate a skill profile based on the user's educational background, work history, and skill set.

[1142] The generative AI analyzes the user's past project data and performance reviews, and also evaluates their learning ability and flexibility.

[1143] 4. Users take interviews and technical tests, and the results are imported into the system.

[1144] After the interview, the interviewer (user) enters the evaluation score and comments into the system using an input form and sends them to the server.

[1145] The results of the technical tests are also entered and sent to the server.

[1146] During the interview, the emotion engine analyzes the user's emotions and transmits the emotion information to the server.

[1147] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[1148] The server analyzes the results of interviews and technical tests to evaluate the user's communication and technical skills.

[1149] Emotional data obtained through the emotion engine is also analyzed and reflected in the overall evaluation.

[1150] 6. The server uses the generated AI to update the user's skill profile.

[1151] The generative AI updates the user's skill profile based on interview and test results and emotional data.

[1152] An updated skill profile reflecting the overall assessment is generated.

[1153] 7. Enter the company's job information and the server analyzes it.

[1154] A company's recruiter (user) submits job information to the server via an input form.

[1155] The server analyzes the job information and extracts the required skills and characteristics.

[1156] 8. The server matches the user's skill profile with company job listings

[1157] The server uses generated AI to match the user's skill profile with company job postings.

[1158] Based on the matching results, optimal matching candidates are generated.

[1159] 9. The server proposes the best matching candidates to the company.

[1160] The server creates a list of the most suitable candidates and presents them to the company's recruiter's device.

[1161] The recruiter (user) checks the proposed candidate information in the review form and makes the final decision.

[1162] Specific examples

[1163] Job seeker A uploads his / her resume and skill sheet to the server. The server receives this information and uses a document analysis engine to extract A's educational background, work history, and skill set. Generative AI then generates A's skill profile based on this information, and also evaluates A's learning ability and flexibility based on past project data and performance reviews.

[1164] Next, Person A takes an online interview. When the interviewer enters the interview evaluation scores and comments into the system, the emotion engine analyzes Person A's emotions and sends the emotional information to the server. The server analyzes these results and evaluates Person A's communication skills and technical abilities, while also taking emotional information into account to make an overall evaluation.

[1165] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[1166] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system enables efficient and fair talent matching, greatly improving the effectiveness of the recruitment process.

[1167] The processing flow will be explained below.

[1168] Step 1:

[1169] The user uploads their resume and skill sheet from their terminal to the server.

[1170] The user opens a dedicated upload form in the web interface and selects a resume or skill sheet file.

[1171] The user presses the upload button and the device sends these files to the server.

[1172] Step 2:

[1173] The server receives and stores the uploaded file.

[1174] The server automatically determines the format of the received file and saves it.

[1175] The server passes the saved file to the document analysis engine.

[1176] Step 3:

[1177] The server uses a document analysis engine to extract information from resumes and skill sheets.

[1178] The server extracts information such as educational background, work history, and skill sets from resumes and skill sheets as text data.

[1179] The extracted information is stored in a database.

[1180] Step 4:

[1181] The server uses a generation AI to generate a skill profile for the user.

[1182] Based on the extracted data, generative AI creates a skill profile for the user.

[1183] Generative AI analyzes past project data and performance reviews to assess learning ability and flexibility.

[1184] Step 5:

[1185] Users take interviews and technical tests, and the results are entered into the system.

[1186] After the interview, the interviewer (user) enters the evaluation score and comments into the input form and sends it to the server.

[1187] Technical test results are also entered and sent to the server.

[1188] Step 6:

[1189] The emotion engine recognizes the user's emotion and transmits the emotion information to the server.

[1190] While the user is undergoing an interview, the emotion engine analyzes the emotion data in real time and transmits it to the server.

[1191] Step 7:

[1192] The server analyzes interview results, test results, and emotional information to provide an overall evaluation of the user.

[1193] The server analyzes the interview results, test results, and emotional data received.

[1194] A comprehensive evaluation is made taking into account the user's communication skills, technical ability, and emotional data.

[1195] Step 8:

[1196] The server uses the generated AI to update the user's skill profile.

[1197] Update your skills profile with interview and test results, as well as sentiment data.

[1198] Generative AI generates a comprehensive skill profile for the user based on new data.

[1199] Step 9:

[1200] A company's recruiter (user) enters job information and sends it to the server.

[1201] Recruiters enter job information through a web interface and send it to the server.

[1202] Step 10:

[1203] The server receives and analyzes the company's job information.

[1204] The server analyzes the job information and extracts the required skills and characteristics.

[1205] The extracted information is stored in a database.

[1206] Step 11:

[1207] The server matches the user's skill profile with company job postings.

[1208] The server uses generated AI to evaluate the match between the user's skill profile and the job posting.

[1209] Based on the matching results, optimal matching candidates are generated.

[1210] Step 12:

[1211] The server proposes the best matching candidates to the company.

[1212] The server creates a list of the most suitable candidates and presents them to the recruiter's device.

[1213] The recruiter (user) checks the proposed candidate information in the review form.

[1214] In this way, the system achieves efficient and fair talent matching and optimizes the recruitment process.

[1215] Example 2

[1216] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1217] Conventional talent matching systems have low accuracy in matching applicants' skill profiles with job information, making it difficult to find suitable candidates. Furthermore, because they do not take into account applicants' emotional data, they have the problem of being unable to accurately evaluate their communication skills or interview performance. This makes it easy for mismatches to occur between companies and applicants, reducing the efficiency of the recruitment process.

[1218] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1219] In this invention, the server includes means for applicants to submit resumes and skill sheets, means for analyzing the submitted resumes and skill sheets, means using a generation AI to generate a skill profile of the applicant based on the analyzed information, means for importing interview results and test results, means for analyzing the imported interview results and test results to perform a comprehensive evaluation of the applicant, an emotion engine for analyzing the emotions of the applicant during the interview, and means for analyzing the applicant's emotion data and reflecting it in the comprehensive evaluation. This enables a comprehensive evaluation that includes the applicant's emotion data, thereby achieving more accurate talent matching.

[1220] "Applicant" refers to an individual who applies for a job.

[1221] A "resume" refers to a document that lists information such as an applicant's educational background, work history, and qualifications.

[1222] A "skills sheet" is a document that details an applicant's technical abilities and work experience.

[1223] "Terminal" refers to a computer device operated by a user. Examples include personal computers, smartphones, and tablets.

[1224] "Server" refers to a computer system that stores, analyzes, and provides data over a network.

[1225] "Generative AI" refers to artificial intelligence that generates new data and predictive models based on input data.

[1226] "Document analysis engine" refers to software or algorithms for extracting specific information from documents.

[1227] "Emotion engine" refers to a system or algorithm for analyzing applicants' emotions.

[1228] A "prompt sentence" refers to text data that is input into a generative AI model, and is a specific format that structures the input information.

[1229] "Job information" refers to information that describes the qualifications and job content of the personnel that a company is looking for.

[1230] "Skills profile" refers to data that integrates an applicant's educational background, work history, skills, and other evaluation information.

[1231] "Comprehensive evaluation" refers to the applicant's overall evaluation based on multiple factors.

[1232] A "matching candidate" refers to an applicant who is judged to have a high compatibility between the applicant and the company's job information.

[1233] This invention is a recruitment system that uses generative AI and an emotion engine to match job seekers (hereafter referred to as applicants) with company job information with high accuracy. The entire system consists of a terminal, a server, generative AI, a document analysis engine, an emotion engine, prompts, etc.

[1234] First, the user (applicant) uses a device (PC, smartphone, tablet, etc.) to upload their resume and skill sheet. When the user opens a dedicated upload form, selects a file, and presses the upload button, the device sends the file to the server using an HTTP POST request. The server saves the received file in a designated directory and checks the file format (PDF, DOCX, etc.).

[1235] The server then passes the saved file to a document analysis engine (such as Google Cloud Vision API) to extract text data using OCR (optical character recognition) technology. The extracted text data is then passed to a natural language processing engine (such as spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is formatted and stored in a database.

[1236] The server then inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user, with the following prompt:

[1237] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[1238] The generation AI generates a skill profile, and the server receives the output and stores it in a database.

[1239] When a user takes an online interview, the interviewer enters their evaluation scores and comments into a dedicated form and sends it from their device to the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (for example, the Affectiva SDK) analyzes the user's emotions during the interview and sends the data to the server. Emotional data is analyzed based on the user's facial expressions, tone of voice, etc.

[1240] The server integrates the interview results, test results, and emotional data it receives, and uses a natural language processing engine to evaluate the user's communication and technical skills. Based on this information, the server makes an overall evaluation of the user.

[1241] Company recruiters enter their company's job information into a dedicated form and send it to the server. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is formatted and stored in a database.

[1242] The server uses generation AI to match the applicant's skill profile with the company's job information, calculates a match score, and lists the best matching candidates. Finally, the server generates a list of the best matching candidates and notifies the company's recruiter's device. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[1243] This system enables comprehensive evaluation of applicants, including their emotional data, leading to more accurate talent matching. By using specific prompts, the generative AI can generate highly accurate skill profiles that can be matched with company job postings.

[1244] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1245] Step 1:

[1246] Users upload their resumes and skill sheets to the server from their devices.

[1247] The user opens a dedicated web form and selects their file. The selected file is sent from the device to the server by pressing the upload button. The device uses an HTTP POST request to send the file to the server. The specific input is a resume or skill sheet file, and the output is a file to be saved on the server. The server checks the format of the received file and saves it in a specified directory.

[1248] Step 2:

[1249] The server analyzes the uploaded resume and skill sheet.

[1250] The server passes the saved file to a document analysis engine (e.g., Google Cloud Vision API). The document analysis engine uses OCR technology to extract text data. The specific input is the uploaded file, and the output is the extracted text data. The server then passes the extracted text data to a natural language processing engine (e.g., spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is stored in a database.

[1251] Step 3:

[1252] The server uses AI to generate a skill profile for the user.

[1253] The server inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user. The specific input is the extracted information, and the output is the generated skill profile. An example of a prompt is as follows:

[1254] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[1255] The generation AI generates a skill profile, and the server receives the output. The generated skill profile is also stored in the database.

[1256] Step 4:

[1257] Users take interviews and technical tests, and the results are input into the system.

[1258] After the user takes the online interview, the interviewer enters the evaluation score and comments into a dedicated form and sends it from the terminal to the server. The specific input is the interview evaluation score and comments, and the output is evaluation data stored on the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (e.g., Affectiva SDK) analyzes the user's facial expressions and tone of voice during the interview and sends emotional data to the server.

[1259] Step 5:

[1260] The server analyzes the interview and test results and gives the user an overall evaluation.

[1261] The server retrieves the evaluation scores and comments received from the interviewer, the results of the technical test, and emotional data from the database. The specific inputs are the evaluation scores, comments, results of the technical test, and emotional data, and the output is overall evaluation data. The comments are analyzed using a natural language processing engine to evaluate the user's communication skills and technical ability. The emotional data is analyzed to evaluate the level of tension and ability to express oneself during the interview. This information is then integrated to provide an overall evaluation of the user.

[1262] Step 6:

[1263] The server uses the generated AI to update the user's skill profile.

[1264] The server then inputs the final evaluation data back into the generation AI to generate a new skill profile. The input is the evaluation data, and the output is an updated skill profile. The generated profile is then saved in the database, replacing the previous profile.

[1265] Step 7:

[1266] Companies enter job information and the server analyzes it.

[1267] A company's recruiter enters job information into a dedicated form and sends it from their device to the server. The specific input is the job information, and the output is analyzed job data. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is stored in a database.

[1268] Step 8:

[1269] The server matches the user's skill profile with company job listings

[1270] The server uses a generation AI to match job postings with the user's skill profile. The specific inputs are the job posting and skill profile, and the output is matching candidates. A match score is calculated and the best matching candidates are listed.

[1271] Step 9:

[1272] The server proposes optimal matching candidates to the company.

[1273] The server generates a list of optimal matching candidates and notifies the company's recruiter's device. The specific input is the matching candidate list, and the output is candidate information proposed to the company's recruiter. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[1274] (Application example 2)

[1275] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1276] Traditional recruitment systems only evaluate applicants' skills and experience, without taking into account important soft skills such as the applicant's emotional state and flexibility. This makes it easy for mismatches to occur between applicants and companies, making it difficult to achieve effective talent matching. Furthermore, with the spread of online interviews, there has been a lack of means to accurately assess an applicant's emotional state. Therefore, to achieve more accurate talent matching, a comprehensive evaluation is needed that takes into account not only skills and experience, but also emotional state and flexibility.

[1277] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1278] In this invention, the server includes an emotion analysis means for analyzing the emotions of applicants and acquiring emotion data, a means for generating and updating the applicant's skill profile using a generation AI, and a means for matching the applicant's skill profile with the company's job information to generate optimal matching candidates. This enables highly accurate talent matching that also takes into account the applicant's soft skills, such as their emotional state.

[1279] An "applicant" is an individual who submits their information in response to a job opening and seeks employment.

[1280] A "resume" is a document that provides basic information about an applicant, including educational background, work history, qualifications, skills, etc.

[1281] A "skills sheet" is a document that details an applicant's technical abilities and expertise.

[1282] A "terminal" is a hardware device for inputting and outputting data, and includes personal computers, smartphones, tablets, etc.

[1283] A "server" is a high-performance computer system for processing and storing data over a network.

[1284] "Generative AI" is artificial intelligence that uses machine learning algorithms to automatically generate and update applicant skill profiles.

[1285] "Emotion analysis means" is a combination of hardware and software for analyzing the emotional state of an applicant and obtaining emotional data.

[1286] "Interview results" is data showing the results of the interviewer's evaluation of the applicant's performance and suitability.

[1287] "Technical test results" are data showing the results of tests conducted to assess the technical capabilities of applicants.

[1288] A "comprehensive evaluation" is an evaluation that takes into account the applicant's interview results, technical test results, emotional data, etc.

[1289] A "company" is an organization whose purpose is to employ people and have them perform specific tasks.

[1290] "Job information" is information that specifically specifies details of the jobs offered by a company, the skills required, recruitment conditions, etc.

[1291] A "matching candidate" is an applicant who is deemed to be a high fit after comparing the applicant's skill profile with the company's job information.

[1292] In this invention, the system for effectively matching job seekers with company recruitment information is configured using the following hardware and software.

[1293] First, job seekers (hereafter referred to as applicants) upload their resumes and skill sheets to the server using a dedicated device. The device can be a PC, smartphone, tablet, etc. The uploaded files are received by the server and analyzed by a document analysis engine. Here, educational background, work history, and skill sets are extracted from the contents of the resume and skill sheets.

[1294] The information extracted by the server using a document analysis engine is input into the generation AI, which generates a skill profile based on the applicant's educational background, work history, and skill set, and analyzes the applicant's past project data and performance reviews, as well as assessing their learning ability and flexibility. The generated skill profile can be viewed on the applicant's device or the company's device.

[1295] Next, when an applicant takes an online interview or technical test, the interviewer or test administrator uses a dedicated terminal to enter the interview results, evaluation scores, and comments into a server. At this time, an emotion analysis tool is used to analyze the applicant's emotional state, and this data is also sent to the server. The emotion analysis tool uses a device equipped with a camera and microphone, and the analysis software captures emotional data in real time.

[1296] The server integrates interview results, technical test results, and emotional data to perform a comprehensive evaluation. This allows for a comprehensive assessment of the applicant's communication skills, technical ability, and emotional state. The generating AI then updates the applicant's skill profile based on this comprehensive evaluation.

[1297] Company recruitment information is entered into the server by the company's recruiting staff via a dedicated terminal. The server analyzes the information and identifies the required skills and characteristics. This allows the job information to be matched with the applicant's skill profile, and highly suitable candidates are generated by the generation AI.

[1298] Finally, the generated candidates are listed and presented to the company's recruiter's device. The recruiter then reviews the proposed candidate information and makes a final decision. This system enables highly accurate talent matching that takes into account the applicant's skills, experience, and even emotional state.

[1299] For example, when an applicant uploads their resume and takes an online interview, sentiment analysis measures their nervousness and confidence levels, after which generative AI updates their skills profile and matches them with company job openings.

[1300] An example of a prompt for the generative AI model is, "User's resume data: {resume_data}, User's interview results: {interview_results}, Emotion data: {emotions}. Please generate the user's latest skill profile based on this data." This prompt enables advanced matching.

[1301] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1302] Step 1:

[1303] Users upload their resumes and skill sheets to the server via dedicated terminals.

[1304] Input: Resume and skill sheet file (PDF, DOCX, etc.)

[1305] Data processing: The server determines the file format and saves the received file.

[1306] Output: Saved resume and skill sheet files

[1307] Step 2:

[1308] The server uses a document analysis engine to analyze the uploaded resume or skill sheet.

[1309] Input: Saved resume and skill sheet files

[1310] Data processing: A document analysis engine extracts information on education, employment history, and skill sets.

[1311] Output: Extracted education, work history, and skill set data

[1312] Step 3:

[1313] The server uses generative AI to generate a skill profile for the applicant based on the extracted information.

[1314] Input: Extracted education, work history, and skill set data

[1315] Data processing: Generative AI analyzes input data to generate a skill profile. It also analyzes past project data and performance reviews to assess learning ability and flexibility.

[1316] Output: Generated skill profile

[1317] Step 4:

[1318] Applicants take online interviews and technical tests, and the interviewers and test administrators enter the results into a server via dedicated terminals.

[1319] Input: Interview results, evaluation scores, comments, technical test results

[1320] Data processing: The server stores the received data and, if necessary, uses emotion analysis means to obtain emotion data.

[1321] Output: Stored interview results, evaluation scores, comments, technical test results, and sentiment data

[1322] Step 5:

[1323] The server analyzes the interview results, technical test results, and emotional data obtained and makes an overall evaluation of the applicant.

[1324] Input: Stored interview results, evaluation scores, comments, technical test results, emotional data

[1325] Data processing: The server integrates the results, and the generating AI performs an overall evaluation.

[1326] Output: Comprehensively evaluated data

[1327] Step 6:

[1328] The generative AI updates the applicant's skill profile based on the overall evaluation data.

[1329] Input: Comprehensively evaluated data

[1330] Data processing: The generating AI updates the skill profile to reflect the overall evaluation.

[1331] Output: Updated skill profile

[1332] Step 7:

[1333] Job information is entered into the server by company recruiters via dedicated terminals.

[1334] Input: Job information (job details, required skills, recruitment conditions)

[1335] Data processing: The server analyzes job postings to identify required skills and characteristics.

[1336] Output: Parsed job listings

[1337] Step 8:

[1338] The server uses generative AI to match the applicant's skill profile with job information and generate the best matching candidates.

[1339] Input: Updated skills profile, parsed job information

[1340] Data processing: Generative AI matches profiles with job listings to generate highly suitable candidates.

[1341] Output: A list of possible matches

[1342] Step 9:

[1343] The generated matching candidates are then presented to the company's recruiter's device.

[1344] Input: Match candidate list

[1345] Data processing: The server converts the list into the proposed format and sends it to the terminal.

[1346] Output: A list of suggested matches

[1347] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1348] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1349] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1350] [Fourth embodiment]

[1351] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1352] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1353] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1354] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1355] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1356] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1357] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1358] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1359] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1360] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1361] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1362] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1363] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1364] This invention is a system that utilizes generative AI to effectively match job seekers with company job information. Below, we will explain the program processing of this system in natural language and provide specific examples.

[1365] Program processing

[1366] 1. The user uploads their resume and skill sheet from their device to the server.

[1367] A user uploads a file using a dedicated upload form.

[1368] The server receives the uploaded file and determines its format (e.g. PDF, DOCX, etc.).

[1369] 2. The server analyzes the uploaded resume and skill sheet.

[1370] The server uses a document analysis engine to extract information such as educational background, work history, and skill sets from resumes and skill sheets.

[1371] 3. The server uses the generation AI to generate a skill profile for the user.

[1372] Based on the extracted information, the generative AI generates a skill profile for the user.

[1373] At this time, past project data and performance reviews are also analyzed, and learning ability and flexibility are also evaluated.

[1374] 4. The user undergoes an interview and technical test, and the results are entered into the system.

[1375] The interviewer (user) enters the interview results and technical test results into the system through an input form.

[1376] The server receives these inputs and begins parsing them.

[1377] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[1378] The server analyzes interview results and technical test scores to evaluate communication skills and technical abilities.

[1379] Based on this, the user's skill profile is updated.

[1380] 6. Collect and analyze company job information.

[1381] Companies submit job information to the server using an input form.

[1382] The server receives the job information and analyzes the required skills and characteristics.

[1383] 7. The server matches the user's skill profile with company job listings.

[1384] The server uses generated AI to match the user's skill profile with job listings.

[1385] Based on the matching results, optimal matching candidates are generated.

[1386] 8. The server proposes the best matching candidates to the company.

[1387] The server creates a list of the generated matching candidates and presents them to the company's terminal.

[1388] The company's recruiter (user) reviews the provided candidate information and makes the final decision.

[1389] Specific examples

[1390] A job seeker, A, uploads his / her resume and skill sheet to the server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[1391] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[1392] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[1393] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching.

[1394] The processing flow will be explained below.

[1395] Step 1:

[1396] The user uploads their resume and skill sheet from their terminal to the server.

[1397] The user uses the system's dedicated upload form, selects the resume or skill sheet file, and begins uploading.

[1398] The device sends the uploaded file to the server.

[1399] Step 2:

[1400] The server receives and stores the uploaded resumes and skill sheets.

[1401] The server automatically determines the file format (PDF, DOCX, etc.).

[1402] The server stores the file for passing to the analysis engine.

[1403] Step 3:

[1404] The server uses a document analysis engine to extract information from resumes and skill sheets.

[1405] The server analyzes the contents of the resume and skill sheet and extracts educational background, work history, and skill set as text data.

[1406] The server organizes the extracted data and extracts the necessary information.

[1407] Step 4:

[1408] The server uses a generation AI to generate a skill profile for the user.

[1409] The server inputs the extracted information into a generation AI, which creates a skill profile based on the user's educational background, work history, and skill set.

[1410] The generative AI performs additional analysis to assess the user's learning ability and flexibility.

[1411] Step 5:

[1412] Users take interviews and technical tests, and the results are entered into the system.

[1413] After the interview, the interviewer (user) sends the evaluation score and comments to the server using an input form.

[1414] The results of the technical tests are also entered and sent to the server.

[1415] Step 6:

[1416] The server analyzes the interview and test results and gives the user an overall evaluation.

[1417] The server analyzes the interview results received from the interviewer and evaluates the user's performance and aptitude.

[1418] Based on the scores of the technical test, the user's technical ability and expertise are evaluated.

[1419] Step 7:

[1420] The server uses the generated AI to update the user's skill profile.

[1421] The generative AI updates the user's skill profile based on interview results and technical test evaluations.

[1422] Generate an updated skills profile that reflects your overall assessment.

[1423] Step 8:

[1424] Companies enter job information.

[1425] A company's recruiter (user) submits job information to the server via an input form.

[1426] Company job postings include the required skill sets and job duties.

[1427] Step 9:

[1428] The server receives and analyzes the company's job information.

[1429] The server analyzes the job information using an analytical engine and extracts the required skills and characteristics.

[1430] The server stores the job listings in a database.

[1431] Step 10:

[1432] The server matches the user's skill profile with company job postings.

[1433] The server uses the generated AI to begin matching the user's skill profile with job listings.

[1434] Based on the matching results, the degree of skill matching and compatibility is evaluated.

[1435] Step 11:

[1436] The server generates optimal matching candidates and presents them to the company's terminal.

[1437] The server selects the best matching candidates from the matching results and generates a list.

[1438] The generated list is sent to the company's recruiter's device.

[1439] The recruiter (user) checks the proposed candidate information in the review form.

[1440] In this way, the system achieves efficient and fair talent matching.

[1441] Example 1

[1442] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1443] Conventional job change support systems have difficulty managing a wide range of information about applicants in one place and effectively matching them with companies' job openings. Furthermore, they lack the functionality to import interview and technical test results into the system and perform a comprehensive evaluation based on those results. As a result, there are cases where applicants are not properly matched with companies, which creates problems that prevent the job change process from proceeding smoothly.

[1444] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1445] In this invention, the server includes a terminal for applicants to submit resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and test results, a server that analyzes the imported interview results and test results to perform a comprehensive evaluation of the applicant, a server that collects and analyzes company job information, a generation AI that compares company job information with the applicant's skill profile and generates optimal matching candidates, a terminal for proposing the generated matching candidates to companies, a document analysis engine, a natural language processing tool, and a generation AI model for matching candidates with job information. This makes it possible to efficiently and accurately match applicants with company job information.

[1446] A resume is a document in which an applicant lists information such as their work history, educational background, and skills.

[1447] A "skills sheet" is a document in which an applicant details his or her technical skills and expertise.

[1448] A "terminal" is a device such as a computer or smartphone that is operated by a user.

[1449] A "server" is a computer system that stores and processes data on a network.

[1450] "Generative AI" is an artificial intelligence technology that generates new information and profiles based on given data.

[1451] "Interview results" refers to the evaluation and feedback of the applicant obtained through the interview.

[1452] "Test results" refer to the numerical results or evaluations of the technical tests or evaluation tests taken by the applicant.

[1453] A "skills profile" is a profile that summarizes an applicant's skills and characteristics based on analyzed information.

[1454] "Job information" refers to detailed information published by companies, such as job types, required skills, and compensation.

[1455] A "document analysis engine" is a software technology for analyzing uploaded documents and extracting necessary information.

[1456] A "natural language processing tool" is a software technology for analyzing text data and understanding human language.

[1457] A "generative AI model" is an artificial intelligence algorithm or framework that learns from massive amounts of data and generates new information and patterns.

[1458] This invention relates to a system that effectively matches job seekers with company job information. This system uses generative AI to create a skill profile of the applicant and compares it with the company's job information to achieve optimal matching.

[1459] The system consists of multiple components, including the following hardware and software:

[1460] 1. Terminal

[1461] A device such as a computer or smartphone that is operated by a user.

[1462] The terminal is used by users to upload resumes and skill sheets.

[1463] For example, a user can use a dedicated upload form to select a file, and the terminal will then send the file to the server.

[1464] 2. Server

[1465] A computer system for receiving and analyzing resumes and skill sheets.

[1466] The server uses the Python library PyMuPDF and the OCR tool Tesseract to parse the uploaded documents.

[1467] 3. Generation AI

[1468] It is an artificial intelligence technology for generating skill profiles of applicants.

[1469] For example, OpenAI's GPT-4 model is used to generate a skill profile based on the extracted information and store it in a database.

[1470] Specific examples of prompt sentences are as follows:

[1471] "Extract the following information from the job applicant's resume and skill sheet: educational background, work history, skill set, past project data, and performance review."

[1472] 4. Input Form and Analysis Tools

[1473] This is an input form for capturing interview and test results.

[1474] The server uses NLP tools (e.g., SpaCy or Gensim) to analyze the input data.

[1475] 5. Matching Engine

[1476] This is software for collecting and analyzing corporate job information.

[1477] Analyze job postings using text mining tools (e.g., NLTK).

[1478] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to assess the match between the applicant's skill profile and the company's job posting.

[1479] 6. Proposed System

[1480] This is a system that proposes the most suitable matching candidates to companies.

[1481] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiting staff reviews the candidate information provided and makes the final decision.

[1482] As a specific example, suppose a job seeker, A, uploads his / her resume and skill sheet to a server. The server receives the information and begins analyzing it. For example, it extracts information that A majored in computer science at university and worked as a software engineer for five years.

[1483] Next, A takes an online interview, and the interviewer enters the results into the system. The server analyzes the interview results and evaluates A's excellent communication skills and teamwork.

[1484] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[1485] Finally, the server proposes information about Person A to Company B, and the recruiter at Company B makes the final decision. This system achieves efficient and fair talent matching. This invention makes it possible to achieve an ideal match for both job seekers and companies.

[1486] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1487] Step 1:

[1488] The user uploads their resume and skill sheet from their terminal to the server.

[1489] Specifically, the user selects a file using a dedicated upload form. The terminal then sends the selected file to the server. The server receives the uploaded file and determines its format (e.g., PDF, DOCX). The input is the uploaded file, and the output is the result of determining the file format.

[1490] Step 2:

[1491] The server analyzes the uploaded resume and skill sheet.

[1492] Specifically, the server launches a document analysis engine (for example, the Python library PyMuPDF or the OCR tool Tesseract). The server uses this analysis engine to automatically extract information such as educational background, work history, and skill set from resumes and skill sheets. The input is the received file, and the output is the extracted information.

[1493] Step 3:

[1494] The server uses a generation AI to generate a skill profile for the user.

[1495] Based on the extracted information, the server uses a generative AI (for example, OpenAI's GPT-4 model) to generate a skill profile for the user. Specifically, the server uses the following prompt for the generative AI: "Please extract the following information from the job seeker's resume and skill sheet: educational background, work history, skill set, past project data, and performance review." The input is the extracted information, and the output is the generated skill profile.

[1496] Step 4:

[1497] Users take interviews and technical tests, and the results are entered into the system.

[1498] The interviewer (user) enters the interview results and technical test results into the system through an input form. The terminal sends the entered data to the server. The server analyzes the received data. An NLP tool (e.g., SpaCy or Gensim) is used for the analysis. The input is the interview results and technical test results, and the output is the analyzed data.

[1499] Step 5:

[1500] The server analyzes the interview and test results and gives the user an overall evaluation.

[1501] Specifically, the server analyzes interview results and technical test scores to evaluate the applicant's communication and technical skills. This information is used to update the user's skill profile. The input is the analyzed interview and test results, and the output is the updated skill profile.

[1502] Step 6:

[1503] Companies enter job information and the server analyzes it.

[1504] Companies enter job information into the system using an input form. The terminal sends the entered job information to the server. The server receives the job information and analyzes it for required skills and characteristics. A text mining tool (e.g., NLTK) is used for the analysis. The input is the job information, and the output is the analyzed job information.

[1505] Step 7:

[1506] The server matches the user's skill profile with company job postings.

[1507] The server uses a generative AI model (e.g., Word2Vec or TF-IDF) to match the user's skill profile with job postings. The input is the skill profile and job posting, and the output is the match and candidate matches.

[1508] Step 8:

[1509] The server proposes the best matching candidates to the company.

[1510] The server creates a list of matching candidates and presents it to the company's terminal. The company's recruiter (user) reviews the provided candidate information and makes a final decision. The input is the list of matching candidates, and the output is the company's final decision.

[1511] (Application example 1)

[1512] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1513] The manual hiring process for brick-and-mortar stores is time-consuming and labor-intensive, and matching applicants with job listings is difficult to optimize. Furthermore, the difficulty of properly assessing applicants' skills and communication abilities can lead to reduced hiring efficiency and accuracy. Furthermore, there is a lack of methods to virtually recreate interviews in a real-world store environment and evaluate applicant suitability.

[1514] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1515] In this invention, the server includes a terminal through which applicants submit their resumes and skill sheets, a server for analyzing the submitted resumes and skill sheets, a generation AI that generates the applicant's skill profile based on the analyzed information, a terminal for importing interview results and technical evaluations, a server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant, a server that collects and analyzes job information from physical stores, a generation AI that compares the job information from physical stores with the applicant's skill profile and generates optimal matching candidates, and a terminal for proposing the generated matching candidates to physical stores.This makes it possible to improve the efficiency and accuracy of staff recruitment at physical stores and to increase the accuracy of applicant aptitude evaluations.

[1516] "Applicant" refers to an individual who applies for a job by submitting a resume or skill sheet.

[1517] A "resume" is a document that lists information such as an applicant's educational background, work history, and qualifications.

[1518] A "skills sheet" is a document that details an applicant's specialized skills and experience.

[1519] "Terminal" refers to the device used by applicants and companies to input, submit, and view information, specifically a smartphone or computer.

[1520] A "server" is a computer system that communicates with multiple terminals via a network and stores and processes data.

[1521] "Generative AI" refers to artificial intelligence that generates responses and actions based on input data. In particular, in this invention, it generates the applicant's skill profile and compares it with job information.

[1522] A "skills profile" is a detailed competency assessment document of an applicant that is generated based on the applicant's educational background, work history, skill set, etc.

[1523] "Interview results" refers to the evaluation results of the applicant when they were interviewed.

[1524] "Technical assessment" refers to the assessment of applicants when they are tested on specific technologies or skills.

[1525] A "comprehensive evaluation" is an overall assessment of an applicant based on a comprehensive analysis of various information such as resumes, skill sheets, interview results, and technical evaluations.

[1526] A "brick and mortar store" refers to a physical commercial establishment, such as a cafe or retail store.

[1527] "Job information" is information that describes the qualifications and job duties of the personnel that a company is looking for.

[1528] The present invention provides a system for improving the efficiency and accuracy of the staff recruitment process in brick-and-mortar stores. Specific embodiments of this system are described below.

[1529] System Configuration

[1530] The system consists of the following main components:

[1531] 1. A device for applicants to submit their resumes and skill sheets

[1532] 2. Server for analyzing submitted resumes and skill sheets

[1533] 3. Generative AI that generates skill profiles for applicants based on analyzed information

[1534] 4. Terminal for capturing interview results and technical evaluations

[1535] 5. A server that analyzes the imported interview results and technical evaluations to perform a comprehensive evaluation of the applicant.

[1536] 6. Server that collects and analyzes job information from brick-and-mortar stores

[1537] 7. Generative AI that matches job postings at brick-and-mortar stores with applicants' skill profiles to generate optimal matching candidates

[1538] 8. A device for proposing the generated matching candidates to the physical store

[1539] Hardware and software used

[1540] Hardware:

[1541] Smartphones and computers (devices used by applicants and brick-and-mortar stores)

[1542] Server (data analysis and storage)

[1543] Head-mounted displays (HMDs, used for virtual interviews, etc.)

[1544] software:

[1545] Generative AI models (GPT-4 and BERT)

[1546] Document analysis engine (e.g. Google Cloud Vision API)

[1547] Program processing

[1548] The server receives data from the device on which applicants submit their resumes and skill sheets. The document analysis engine on the server extracts information such as educational background, work history, and skill sets from the submitted data. The AI ​​then generates a skill profile based on the extracted data. At the same time, the server also imports interview results and technical evaluations, and performs a comprehensive evaluation.

[1549] When a brick-and-mortar store inputs job information, the server analyzes the information and identifies the required skills and characteristics. The generation AI matches the applicant's skill profile with the brick-and-mortar store's job information and generates the best matching candidates. This matching is performed by analyzing the data input into the generation AI using prompt sentences.

[1550] Finally, the generated candidates are presented to the store, where staff can review and select candidates. The store can then use touch and voice commands to check candidate information, contact them, schedule interviews, and more.

[1551] Specific examples

[1552] For example, if physical store A registers a job posting for a service staff member in the system, the generation AI will match applicant B's skill profile with store A's job posting. Applicant B had previously uploaded a resume and was evaluated for his excellent customer service skills in an online interview. The generation AI will determine that applicant B is highly suitable for store A's requirements and suggest applicant B to the store A staff member. The staff member can then check applicant B's details within the app and contact him, resulting in an efficient recruitment process.

[1553] Prompt Sentence Examples

[1554] An example of a prompt is:

[1555] "Evaluate this candidate's customer service skills and flexibility based on their resume and interview results to determine if they are an ideal match for the following job posting: (specific job posting details)"

[1556] By inputting these prompts into the generation AI, it is possible to analyze suitable candidates and propose optimal matching candidates.

[1557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1558] Step 1:

[1559] The user uploads a resume or skill sheet from their device to the server. The user uploads a file in PDF or DOCX format using a dedicated upload form. The server receives the uploaded file and determines the file format. The input of this process is the resume or skill sheet, and the output is the file data stored on the server.

[1560] Step 2:

[1561] The server analyzes the uploaded resumes and skill sheets. The server's document analysis engine (e.g., Google Cloud Vision API) extracts information such as educational background, work history, and skill sets from the resumes and skill sheets. The input to this process is the file data saved in step 1, and the output is a dataset of the extracted information.

[1562] Step 3:

[1563] The server uses a generative AI to generate a skill profile for the user. The generative AI (e.g., GPT-4) generates the skill profile based on the extracted information. The input to this process is the dataset obtained in step 2, and the output is a skill profile. Specifically, past project data and performance reviews are also analyzed.

[1564] Step 4:

[1565] A user undergoes an interview or technical evaluation, and the results are imported into the system. The user's interview results and technical evaluation data are input from their terminal to the server. The input to this process is the interview results and technical evaluation entered by the interviewer via their terminal, and the output is the evaluation data stored on the server.

[1566] Step 5:

[1567] The server analyzes the interview results and technical evaluation and performs an overall evaluation of the user. The server evaluates communication and technical skills based on the interview results and technical evaluation. The input to this process is the evaluation data saved in step 4, and the output is an updated skill profile.

[1568] Step 6:

[1569] The server collects and analyzes job postings from brick-and-mortar stores. A brick-and-mortar store representative submits the job posting to the server using an input form. The server receives the job posting and analyzes the required skills and characteristics. The input to this process is the brick-and-mortar store's job postings, and the output is a dataset of analyzed job postings.

[1570] Step 7:

[1571] The server uses a generation AI to match the user's skill profile with job postings at brick-and-mortar stores. The generation AI uses a prompt to determine the degree of match between the skill profile and the job posting. The input to this process is the dataset obtained in steps 3 and 6, and the output is a list of the best matching candidates. An example of a specific prompt is, "Evaluate this candidate's customer service skills and flexibility based on their resume data and interview results, and determine whether they are the best match for the job posting below. Job posting: (specific job posting details)."

[1572] Step 8:

[1573] The server proposes the best candidates to the store. The generated list of candidates is displayed on a terminal in the store for the store staff to review. The input of this process is the list of best candidates, and the output is an interface for the store staff to review, contact, and schedule interviews.

[1574] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1575] This invention is a recruitment system that utilizes generative AI and an emotion engine to effectively match job seekers with companies' job information. This system recognizes the user's emotions and reflects that emotion data in evaluation and matching, thereby achieving more accurate talent matching.

[1576] Program processing

[1577] 1. The user uploads their resume and skill sheet from their device to the server.

[1578] The user uses a dedicated upload form to select a resume or skill sheet file and send it from the terminal to the server.

[1579] The server determines the file format (PDF, DOCX, etc.) and saves the received file.

[1580] 2. The server analyzes the uploaded resume and skill sheet

[1581] The server uses a document analysis engine to extract information about education, work history, and skill sets from resumes and skill sheets.

[1582] 3. The server uses the AI ​​to generate a skill profile for the user.

[1583] The server inputs the extracted information into a generation AI to generate a skill profile based on the user's educational background, work history, and skill set.

[1584] The generative AI analyzes the user's past project data and performance reviews, and also evaluates their learning ability and flexibility.

[1585] 4. Users take interviews and technical tests, and the results are imported into the system.

[1586] After the interview, the interviewer (user) enters the evaluation score and comments into the system using an input form and sends them to the server.

[1587] The results of the technical tests are also entered and sent to the server.

[1588] During the interview, the emotion engine analyzes the user's emotions and transmits the emotion information to the server.

[1589] 5. The server analyzes the interview and test results and gives the user an overall evaluation.

[1590] The server analyzes the results of interviews and technical tests to evaluate the user's communication and technical skills.

[1591] Emotional data obtained through the emotion engine is also analyzed and reflected in the overall evaluation.

[1592] 6. The server uses the generated AI to update the user's skill profile.

[1593] The generative AI updates the user's skill profile based on interview and test results and emotional data.

[1594] An updated skill profile reflecting the overall assessment is generated.

[1595] 7. Enter the company's job information and the server analyzes it.

[1596] A company's recruiter (user) submits job information to the server via an input form.

[1597] The server analyzes the job information and extracts the required skills and characteristics.

[1598] 8. The server matches the user's skill profile with company job listings

[1599] The server uses generated AI to match the user's skill profile with company job postings.

[1600] Based on the matching results, optimal matching candidates are generated.

[1601] 9. The server proposes the best matching candidates to the company.

[1602] The server creates a list of the most suitable candidates and presents them to the company's recruiter's device.

[1603] The recruiter (user) checks the proposed candidate information in the review form and makes the final decision.

[1604] Specific examples

[1605] Job seeker A uploads his / her resume and skill sheet to the server. The server receives this information and uses a document analysis engine to extract A's educational background, work history, and skill set. Generative AI then generates A's skill profile based on this information, and also evaluates A's learning ability and flexibility based on past project data and performance reviews.

[1606] Next, Person A takes an online interview. When the interviewer enters the interview evaluation scores and comments into the system, the emotion engine analyzes Person A's emotions and sends the emotional information to the server. The server analyzes these results and evaluates Person A's communication skills and technical abilities, while also taking emotional information into account to make an overall evaluation.

[1607] When Company B inputs a new job posting for a software developer into the server, the server analyzes the information and identifies the skills and characteristics the job seeker is looking for. Using generative AI, the server compares Company A's skill profile with Company B's job posting and determines that Company A is a good fit for Company B's requirements.

[1608] Finally, the server proposes Person A's information to Company B, and the recruiter at Company B makes the final decision. This system enables efficient and fair talent matching, greatly improving the effectiveness of the recruitment process.

[1609] The processing flow will be explained below.

[1610] Step 1:

[1611] The user uploads their resume and skill sheet from their terminal to the server.

[1612] The user opens a dedicated upload form in the web interface and selects a resume or skill sheet file.

[1613] The user presses the upload button and the device sends these files to the server.

[1614] Step 2:

[1615] The server receives and stores the uploaded file.

[1616] The server automatically determines the format of the received file and saves it.

[1617] The server passes the saved file to the document analysis engine.

[1618] Step 3:

[1619] The server uses a document analysis engine to extract information from resumes and skill sheets.

[1620] The server extracts information such as educational background, work history, and skill sets from resumes and skill sheets as text data.

[1621] The extracted information is stored in a database.

[1622] Step 4:

[1623] The server uses a generation AI to generate a skill profile for the user.

[1624] Based on the extracted data, generative AI creates a skill profile for the user.

[1625] Generative AI analyzes past project data and performance reviews to assess learning ability and flexibility.

[1626] Step 5:

[1627] Users take interviews and technical tests, and the results are entered into the system.

[1628] After the interview, the interviewer (user) enters the evaluation score and comments into the input form and sends it to the server.

[1629] Technical test results are also entered and sent to the server.

[1630] Step 6:

[1631] The emotion engine recognizes the user's emotion and transmits the emotion information to the server.

[1632] While the user is undergoing an interview, the emotion engine analyzes the emotion data in real time and transmits it to the server.

[1633] Step 7:

[1634] The server analyzes interview results, test results, and emotional information to provide an overall evaluation of the user.

[1635] The server analyzes the interview results, test results, and emotional data received.

[1636] A comprehensive evaluation is made taking into account the user's communication skills, technical ability, and emotional data.

[1637] Step 8:

[1638] The server uses the generated AI to update the user's skill profile.

[1639] Update your skills profile with interview and test results, as well as sentiment data.

[1640] Generative AI generates a comprehensive skill profile for the user based on new data.

[1641] Step 9:

[1642] A company's recruiter (user) enters job information and sends it to the server.

[1643] Recruiters enter job information through a web interface and send it to the server.

[1644] Step 10:

[1645] The server receives and analyzes the company's job information.

[1646] The server analyzes the job information and extracts the required skills and characteristics.

[1647] The extracted information is stored in a database.

[1648] Step 11:

[1649] The server matches the user's skill profile with company job postings.

[1650] The server uses generated AI to evaluate the match between the user's skill profile and the job posting.

[1651] Based on the matching results, optimal matching candidates are generated.

[1652] Step 12:

[1653] The server proposes the best matching candidates to the company.

[1654] The server creates a list of the most suitable candidates and presents them to the recruiter's device.

[1655] The recruiter (user) checks the proposed candidate information in the review form.

[1656] In this way, the system achieves efficient and fair talent matching and optimizes the recruitment process.

[1657] Example 2

[1658] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1659] Conventional talent matching systems have low accuracy in matching applicants' skill profiles with job information, making it difficult to find suitable candidates. Furthermore, because they do not take into account applicants' emotional data, they have the problem of being unable to accurately evaluate their communication skills or interview performance. This makes it easy for mismatches to occur between companies and applicants, reducing the efficiency of the recruitment process.

[1660] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1661] In this invention, the server includes means for applicants to submit resumes and skill sheets, means for analyzing the submitted resumes and skill sheets, means using a generation AI to generate a skill profile of the applicant based on the analyzed information, means for importing interview results and test results, means for analyzing the imported interview results and test results to perform a comprehensive evaluation of the applicant, an emotion engine for analyzing the emotions of the applicant during the interview, and means for analyzing the applicant's emotion data and reflecting it in the comprehensive evaluation. This enables a comprehensive evaluation that includes the applicant's emotion data, thereby achieving more accurate talent matching.

[1662] "Applicant" refers to an individual who applies for a job.

[1663] A "resume" refers to a document that lists information such as an applicant's educational background, work history, and qualifications.

[1664] A "skills sheet" is a document that details an applicant's technical abilities and work experience.

[1665] "Terminal" refers to a computer device operated by a user. Examples include personal computers, smartphones, and tablets.

[1666] "Server" refers to a computer system that stores, analyzes, and provides data over a network.

[1667] "Generative AI" refers to artificial intelligence that generates new data and predictive models based on input data.

[1668] "Document analysis engine" refers to software or algorithms for extracting specific information from documents.

[1669] "Emotion engine" refers to a system or algorithm for analyzing applicants' emotions.

[1670] A "prompt sentence" refers to text data that is input into a generative AI model, and is a specific format that structures the input information.

[1671] "Job information" refers to information that describes the qualifications and job content of the personnel that a company is looking for.

[1672] "Skills profile" refers to data that integrates an applicant's educational background, work history, skills, and other evaluation information.

[1673] "Comprehensive evaluation" refers to the applicant's overall evaluation based on multiple factors.

[1674] A "matching candidate" refers to an applicant who is judged to have a high compatibility between the applicant and the company's job information.

[1675] This invention is a recruitment system that uses generative AI and an emotion engine to match job seekers (hereafter referred to as applicants) with company job information with high accuracy. The entire system consists of a terminal, a server, generative AI, a document analysis engine, an emotion engine, prompts, etc.

[1676] First, the user (applicant) uses a device (PC, smartphone, tablet, etc.) to upload their resume and skill sheet. When the user opens a dedicated upload form, selects a file, and presses the upload button, the device sends the file to the server using an HTTP POST request. The server saves the received file in a designated directory and checks the file format (PDF, DOCX, etc.).

[1677] The server then passes the saved file to a document analysis engine (such as Google Cloud Vision API) to extract text data using OCR (optical character recognition) technology. The extracted text data is then passed to a natural language processing engine (such as spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is formatted and stored in a database.

[1678] The server then inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user, with the following prompt:

[1679] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[1680] The generation AI generates a skill profile, and the server receives the output and stores it in a database.

[1681] When a user takes an online interview, the interviewer enters their evaluation scores and comments into a dedicated form and sends it from their device to the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (for example, the Affectiva SDK) analyzes the user's emotions during the interview and sends the data to the server. Emotional data is analyzed based on the user's facial expressions, tone of voice, etc.

[1682] The server integrates the interview results, test results, and emotional data it receives, and uses a natural language processing engine to evaluate the user's communication and technical skills. Based on this information, the server makes an overall evaluation of the user.

[1683] Company recruiters enter their company's job information into a dedicated form and send it to the server. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is formatted and stored in a database.

[1684] The server uses generation AI to match the applicant's skill profile with the company's job information, calculates a match score, and lists the best matching candidates. Finally, the server generates a list of the best matching candidates and notifies the company's recruiter's device. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[1685] This system enables comprehensive evaluation of applicants, including their emotional data, leading to more accurate talent matching. By using specific prompts, the generative AI can generate highly accurate skill profiles that can be matched with company job postings.

[1686] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1687] Step 1:

[1688] Users upload their resumes and skill sheets to the server from their devices.

[1689] The user opens a dedicated web form and selects their file. The selected file is sent from the device to the server by pressing the upload button. The device uses an HTTP POST request to send the file to the server. The specific input is a resume or skill sheet file, and the output is a file to be saved on the server. The server checks the format of the received file and saves it in a specified directory.

[1690] Step 2:

[1691] The server analyzes the uploaded resume and skill sheet.

[1692] The server passes the saved file to a document analysis engine (e.g., Google Cloud Vision API). The document analysis engine uses OCR technology to extract text data. The specific input is the uploaded file, and the output is the extracted text data. The server then passes the extracted text data to a natural language processing engine (e.g., spaCy) to extract keywords such as educational background, work history, and skill set. The extracted information is stored in a database.

[1693] Step 3:

[1694] The server uses AI to generate a skill profile for the user.

[1695] The server inputs the extracted information into a generative AI (e.g., GPT-4) to generate a skill profile for the user. The specific input is the extracted information, and the output is the generated skill profile. An example of a prompt is as follows:

[1696] Generate a skill profile for a user based on the following information: Education: Graduated from XX University. Work history: Worked at XX Co., Ltd. for XX years. Skill set: Programming (Python, Java), data analysis, project management.

[1697] The generation AI generates a skill profile, and the server receives the output. The generated skill profile is also stored in the database.

[1698] Step 4:

[1699] Users take interviews and technical tests, and the results are input into the system.

[1700] After the user takes the online interview, the interviewer enters the evaluation score and comments into a dedicated form and sends it from the terminal to the server. The specific input is the interview evaluation score and comments, and the output is evaluation data stored on the server. The results of the technical test are also imported into the system in a similar format. In addition, an emotion engine (e.g., Affectiva SDK) analyzes the user's facial expressions and tone of voice during the interview and sends emotional data to the server.

[1701] Step 5:

[1702] The server analyzes the interview and test results and gives the user an overall evaluation.

[1703] The server retrieves the evaluation scores and comments received from the interviewer, the results of the technical test, and emotional data from the database. The specific inputs are the evaluation scores, comments, results of the technical test, and emotional data, and the output is overall evaluation data. The comments are analyzed using a natural language processing engine to evaluate the user's communication skills and technical ability. The emotional data is analyzed to evaluate the level of tension and ability to express oneself during the interview. This information is then integrated to provide an overall evaluation of the user.

[1704] Step 6:

[1705] The server uses the generated AI to update the user's skill profile.

[1706] The server then inputs the final evaluation data back into the generation AI to generate a new skill profile. The input is the evaluation data, and the output is an updated skill profile. The generated profile is then saved in the database, replacing the previous profile.

[1707] Step 7:

[1708] Companies enter job information and the server analyzes it.

[1709] A company's recruiter enters job information into a dedicated form and sends it from their device to the server. The specific input is the job information, and the output is analyzed job data. The server analyzes the job information and extracts the required skills and characteristics. The extracted data is stored in a database.

[1710] Step 8:

[1711] The server matches the user's skill profile with company job listings

[1712] The server uses a generation AI to match job postings with the user's skill profile. The specific inputs are the job posting and skill profile, and the output is matching candidates. A match score is calculated and the best matching candidates are listed.

[1713] Step 9:

[1714] The server proposes optimal matching candidates to the company.

[1715] The server generates a list of optimal matching candidates and notifies the company's recruiter's device. The specific input is the matching candidate list, and the output is candidate information proposed to the company's recruiter. The recruiter logs into the system, checks the proposed candidate information in a review form, and makes a final decision.

[1716] (Application example 2)

[1717] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1718] Traditional recruitment systems only evaluate applicants' skills and experience, without taking into account important soft skills such as the applicant's emotional state and flexibility. This makes it easy for mismatches to occur between applicants and companies, making it difficult to achieve effective talent matching. Furthermore, with the spread of online interviews, there has been a lack of means to accurately assess an applicant's emotional state. Therefore, to achieve more accurate talent matching, a comprehensive evaluation is needed that takes into account not only skills and experience, but also emotional state and flexibility.

[1719] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1720] In this invention, the server includes an emotion analysis means for analyzing the emotions of applicants and acquiring emotion data, a means for generating and updating the applicant's skill profile using a generation AI, and a means for matching the applicant's skill profile with the company's job information to generate optimal matching candidates. This enables highly accurate talent matching that also takes into account the applicant's soft skills, such as their emotional state.

[1721] An "applicant" is an individual who submits their information in response to a job opening and seeks employment.

[1722] A "resume" is a document that provides basic information about an applicant, including educational background, work history, qualifications, skills, etc.

[1723] A "skills sheet" is a document that details an applicant's technical abilities and expertise.

[1724] A "terminal" is a hardware device for inputting and outputting data, and includes personal computers, smartphones, tablets, etc.

[1725] A "server" is a high-performance computer system for processing and storing data over a network.

[1726] "Generative AI" is artificial intelligence that uses machine learning algorithms to automatically generate and update applicant skill profiles.

[1727] "Emotion analysis means" is a combination of hardware and software for analyzing the emotional state of an applicant and obtaining emotional data.

[1728] "Interview results" is data showing the results of the interviewer's evaluation of the applicant's performance and suitability.

[1729] "Technical test results" are data showing the results of tests conducted to assess the technical capabilities of applicants.

[1730] A "comprehensive evaluation" is an evaluation that takes into account the applicant's interview results, technical test results, emotional data, etc.

[1731] A "company" is an organization whose purpose is to employ people and have them perform specific tasks.

[1732] "Job information" is information that specifically specifies details of the jobs offered by a company, the skills required, recruitment conditions, etc.

[1733] A "matching candidate" is an applicant who is deemed to be a high fit after comparing the applicant's skill profile with the company's job information.

[1734] In this invention, the system for effectively matching job seekers with company recruitment information is configured using the following hardware and software.

[1735] First, job seekers (hereafter referred to as applicants) upload their resumes and skill sheets to the server using a dedicated device. The device can be a PC, smartphone, tablet, etc. The uploaded files are received by the server and analyzed by a document analysis engine. Here, educational background, work history, and skill sets are extracted from the contents of the resume and skill sheets.

[1736] The information extracted by the server using a document analysis engine is input into the generation AI, which generates a skill profile based on the applicant's educational background, work history, and skill set, and analyzes the applicant's past project data and performance reviews, as well as assessing their learning ability and flexibility. The generated skill profile can be viewed on the applicant's device or the company's device.

[1737] Next, when an applicant takes an online interview or technical test, the interviewer or test administrator uses a dedicated terminal to enter the interview results, evaluation scores, and comments into a server. At this time, an emotion analysis tool is used to analyze the applicant's emotional state, and this data is also sent to the server. The emotion analysis tool uses a device equipped with a camera and microphone, and the analysis software captures emotional data in real time.

[1738] The server integrates interview results, technical test results, and emotional data to perform a comprehensive evaluation. This allows for a comprehensive assessment of the applicant's communication skills, technical ability, and emotional state. The generating AI then updates the applicant's skill profile based on this comprehensive evaluation.

[1739] Company recruitment information is entered into the server by the company's recruiting staff via a dedicated terminal. The server analyzes the information and identifies the required skills and characteristics. This allows the job information to be matched with the applicant's skill profile, and highly suitable candidates are generated by the generation AI.

[1740] Finally, the generated candidates are listed and presented to the company's recruiter's device. The recruiter then reviews the proposed candidate information and makes a final decision. This system enables highly accurate talent matching that takes into account the applicant's skills, experience, and even emotional state.

[1741] For example, when an applicant uploads their resume and takes an online interview, sentiment analysis measures their nervousness and confidence levels, after which generative AI updates their skills profile and matches them with company job openings.

[1742] An example of a prompt for the generative AI model is, "User's resume data: {resume_data}, User's interview results: {interview_results}, Emotion data: {emotions}. Please generate the user's latest skill profile based on this data." This prompt enables advanced matching.

[1743] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1744] Step 1:

[1745] Users upload their resumes and skill sheets to the server via dedicated terminals.

[1746] Input: Resume and skill sheet file (PDF, DOCX, etc.)

[1747] Data processing: The server determines the file format and saves the received file.

[1748] Output: Saved resume and skill sheet files

[1749] Step 2:

[1750] The server uses a document analysis engine to analyze the uploaded resume or skill sheet.

[1751] Input: Saved resume and skill sheet files

[1752] Data processing: A document analysis engine extracts information on education, employment history, and skill sets.

[1753] Output: Extracted education, work history, and skill set data

[1754] Step 3:

[1755] The server uses generative AI to generate a skill profile for the applicant based on the extracted information.

[1756] Input: Extracted education, work history, and skill set data

[1757] Data processing: Generative AI analyzes input data to generate a skill profile. It also analyzes past project data and performance reviews to assess learning ability and flexibility.

[1758] Output: Generated skill profile

[1759] Step 4:

[1760] Applicants take online interviews and technical tests, and the interviewers and test administrators enter the results into a server via dedicated terminals.

[1761] Input: Interview results, evaluation scores, comments, technical test results

[1762] Data processing: The server stores the received data and, if necessary, uses emotion analysis means to obtain emotion data.

[1763] Output: Stored interview results, evaluation scores, comments, technical test results, and sentiment data

[1764] Step 5:

[1765] The server analyzes the interview results, technical test results, and emotional data obtained and makes an overall evaluation of the applicant.

[1766] Input: Stored interview results, evaluation scores, comments, technical test results, emotional data

[1767] Data processing: The server integrates the results, and the generating AI performs an overall evaluation.

[1768] Output: Comprehensively evaluated data

[1769] Step 6:

[1770] The generative AI updates the applicant's skill profile based on the overall evaluation data.

[1771] Input: Comprehensively evaluated data

[1772] Data processing: The generating AI updates the skill profile to reflect the overall evaluation.

[1773] Output: Updated skill profile

[1774] Step 7:

[1775] Job information is entered into the server by company recruiters via dedicated terminals.

[1776] Input: Job information (job details, required skills, recruitment conditions)

[1777] Data processing: The server analyzes job postings to identify required skills and characteristics.

[1778] Output: Parsed job listings

[1779] Step 8:

[1780] The server uses generative AI to match the applicant's skill profile with job information and generate the best matching candidates.

[1781] Input: Updated skills profile, parsed job information

[1782] Data processing: Generative AI matches profiles with job listings to generate highly suitable candidates.

[1783] Output: A list of possible matches

[1784] Step 9:

[1785] The generated matching candidates are then presented to the company's recruiter's device.

[1786] Input: Match candidate list

[1787] Data processing: The server converts the list into the proposed format and sends it to the terminal.

[1788] Output: A list of suggested matches

[1789] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1790] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1791] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1792] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1793] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1794] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1795] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1796] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1797] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1798] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1799] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1800] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1801] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1802] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1803] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1804] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1805] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1806] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1807] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1808] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1809] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1810] The following is further disclosed regarding the above embodiment.

[1811] (Claim 1)

[1812] A terminal for applicants to submit their resumes and skill sheets,

[1813] A server for analyzing submitted resumes and skill sheets;

[1814] A generation AI that generates a skill profile of the applicant based on the analyzed information, and

[1815] A terminal for importing interview and test results,

[1816] A server that analyzes the imported interview and test results and performs a comprehensive evaluation of the applicant;

[1817] A server that collects and analyzes company recruitment information;

[1818] Generative AI that matches companies' job information with applicants' skill profiles to generate optimal matching candidates;

[1819] The system includes a terminal for proposing the generated matching candidates to companies.

[1820] (Claim 2)

[1821] The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and performance reviews.

[1822] (Claim 3)

[1823] The system of claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on the company's job information.

[1824] "Example 1"

[1825] (Claim 1)

[1826] A terminal for applicants to submit their resumes and skill sheets,

[1827] A server for analyzing submitted resumes and skill sheets;

[1828] A generation AI that generates a skill profile of the applicant based on the analyzed information, and

[1829] A terminal for importing interview and test results,

[1830] A server that analyzes the imported interview and test results and performs a comprehensive evaluation of the applicant;

[1831] A server that collects and analyzes company recruitment information;

[1832] Generative AI that matches companies' job information with applicants' skill profiles to generate optimal matching candidates;

[1833] a terminal for proposing the generated matching candidates to companies;

[1834] A document analysis engine,

[1835] Natural language processing tools and

[1836] Generative AI models for matching candidates with job postings

[1837] A system including:

[1838] (Claim 2)

[1839] The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and performance reviews.

[1840] (Claim 3)

[1841] The system of claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on the company's job information.

[1842] "Application Example 1"

[1843] (Claim 1)

[1844] A terminal for applicants to submit their resumes and skill sheets,

[1845] A server for analyzing submitted resumes and skill sheets;

[1846] A generation AI that generates a skill profile of the applicant based on the analyzed information, and

[1847] A terminal for inputting interview results and technical evaluations,

[1848] A server that analyzes the imported interview results and technical evaluations to make a comprehensive evaluation of the applicants;

[1849] A server that collects and analyzes job information from brick-and-mortar stores;

[1850] Generative AI that matches job information from brick-and-mortar stores with the skill profile of applicants to generate optimal matching candidates;

[1851] A system including a terminal for proposing the generated matching candidates to physical stores.

[1852] (Claim 2)

[1853] The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and work reviews.

[1854] (Claim 3)

[1855] The system of claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on job information from physical stores.

[1856] "Example 2: Combining Emotion Engines"

[1857] (Claim 1)

[1858] A terminal for applicants to submit their resumes and skill sheets,

[1859] A server for analyzing submitted resumes and skill sheets;

[1860] A generation AI that generates a skill profile of the applicant based on the analyzed information, and

[1861] A terminal for importing interview and test results,

[1862] A server that analyzes the imported interview and test results and performs a comprehensive evaluation of the applicant;

[1863] A server that collects and analyzes company recruitment information;

[1864] Generative AI that matches companies' job information with applicants' skill profiles to generate optimal matching candidates;

[1865] a terminal for proposing the generated matching candidates to companies;

[1866] An emotion engine that analyzes applicants' emotions during interviews;

[1867] A system that includes a server that analyzes applicants' emotional data and reflects this in the overall evaluation.

[1868] (Claim 2)

[1869] The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and performance reviews.

[1870] (Claim 3)

[1871] The system of claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on the company's job information.

[1872] "Application example 2 when combining emotion engines"

[1873] (Claim 1)

[1874] A terminal for applicants to submit their resumes and skill sheets,

[1875] A server for analyzing submitted resumes and skill sheets;

[1876] A generation AI that generates a skill profile of the applicant based on the analyzed information, and

[1877] A terminal for inputting interview results and technical test results,

[1878] A server that analyzes the imported interview results and technical test results and performs a comprehensive evaluation of the applicants;

[1879] emotion analysis means for analyzing emotions of applicants and acquiring emotion data;

[1880] A server that collects and analyzes company recruitment information;

[1881] Generative AI that matches companies' job information with applicants' skill profiles to generate optimal matching candidates;

[1882] The system includes a terminal for proposing the generated matching candidates to companies.

[1883] (Claim 2)

[1884] The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and performance reviews.

[1885] (Claim 3)

[1886] The system of claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on the company's job information. [Explanation of symbols]

[1887] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal for applicants to submit their resumes and skill sheets, A server for analyzing submitted resumes and skill sheets; A generation AI that generates a skill profile of the applicant based on the analyzed information, and A terminal for importing interview and test results, A server that analyzes the imported interview and test results and performs a comprehensive evaluation of the applicant; A server that collects and analyzes company recruitment information; Generative AI that matches companies' job information with applicants' skill profiles to generate optimal matching candidates; The system includes a terminal for proposing the generated matching candidates to companies.

2. The system of claim 1, wherein the generating AI evaluates the applicant's learning ability and flexibility based on the applicant's past project data and performance reviews.

3. The system according to claim 1, wherein the generation AI evaluates the degree of match between the applicant's skill profile and the job information based on the company's job information.

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