System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining job offer information; means for obtaining job applicant resumes; generating and AI means for comparing the job offer information and the resumes and optimizing the job offer information; means for providing the generated job offer information to the job applicant; analyzing means for identifying missing information in the resumes; interactive AI means for hearing the missing information from the job applicant; means for modifying the resumes based on the obtained information; and means for providing the modified resumes 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] Conventional systems for providing job information and managing job seeker resumes pose a challenge in improving the accuracy of matching between job seekers and companies. Specifically, there is a lack of efficient means to resolve cases where job information does not match the job seeker's interests or skills, or where the job seeker's resume lacks necessary information. Furthermore, there are many cases where companies are unable to accurately assess the job seeker's suitability due to insufficient information provided by the job seeker. There is a need for a system that can solve these problems and achieve more accurate matching between job seekers and companies. [Means for solving the problem]

[0005] The present invention first provides a means for acquiring job information and a means for acquiring a job seeker's resume. It then provides a generation AI means for comparing the job information with the resume and optimizing the job information based on the comparison. The generated job information is provided to the job seeker. It also includes an analysis means for identifying missing information in the resume and a conversational AI means for hearing the missing information from the job seeker. This conversational AI can also hear recommendation information from those related to the job seeker as needed. It also includes a means for amending the resume based on the acquired information and providing the amended resume to the company. This enables more accurate matching between job seekers and companies.

[0006] "Job information" refers to information provided by companies when recruiting, including details such as job content, required skills, work location, and salary.

[0007] A resume is a document that lists a job seeker's career history, skills, educational background, work experience, etc., and is submitted to a company when seeking a job.

[0008] "Generative AI" is a technology that uses artificial intelligence to analyze data and generate and optimize information for specific purposes.

[0009] "Conversational AI" is artificial intelligence that interacts with users through voice and text, collecting information and answering questions.

[0010] "Analysis means" refers to a method or device for analyzing specific data and extracting its contents or characteristics.

[0011] A "hearing instrument" is a method or device for asking questions of a person of interest and obtaining their answers in order to gather specific information.

[0012] "Optimization" is the process of modifying and adjusting data or information to make it more effective and useful for a specific purpose.

[0013] A "database" is a system for systematically storing and managing specific data.

[0014] A "business" is a for-profit organization that provides goods and services and is typically run by an employer.

[0015] A "job seeker" is an individual who searches for and applies for a job or position. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[0038] Overall overview

[0039] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[0040] Acquiring and storing job information

[0041] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0042] Acquiring and storing job seekers' resumes

[0043] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0044] Job Optimization with Generative AI

[0045] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[0046] Identifying and interviewing missing information on resumes

[0047] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0048] Specific examples

[0049] When job seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "experience in digital marketing." When the conversational AI asks job seeker A, "Tell us about your digital marketing skills," job seeker A responds, "I have three years of experience using Google Analytics." The server then corrects the resume based on the information obtained.

[0050] Providing optimized resumes to companies

[0051] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0052] System Overview

[0053] This system processes the following steps in a single sequence: acquiring job information, acquiring job seeker resumes, optimizing the job information using generation AI, gathering missing information using conversational AI, and providing the optimized resumes to companies. This can significantly improve the accuracy of matching job seekers and companies.

[0054] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0055] The processing flow will be explained below.

[0056] Step 1: Get job information

[0057] The server establishes a connection to the company's job database.

[0058] The server runs a query to get the latest job listings.

[0059] The acquired job information is saved in the server database.

[0060] Step 2: Obtaining job seeker resumes

[0061] The user uploads a resume file to the system from their own device.

[0062] The server receives the resume file and stores it in a database.

[0063] Step 3: Initializing the generated AI

[0064] The server loads and initializes the generative AI model.

[0065] The server begins parsing the job listings and resumes.

[0066] Step 4: Optimize your job listing

[0067] The server uses generated AI to compare job postings with resume content.

[0068] AI generates and edits job information that best suits the interests and aptitudes of job seekers.

[0069] The server sends the optimized job information to the job seeker's device.

[0070] Step 5: Identify missing information on your resume

[0071] The server analyzes the content of the received resume.

[0072] The server identifies the missing information based on the analysis results.

[0073] Step 6: Initializing the conversational AI

[0074] The server loads and initializes the conversational AI.

[0075] The server uses conversational AI to set questions to obtain missing information.

[0076] Step 7: Hearing

[0077] The user initiates a dialogue with the conversational AI.

[0078] Conversational AI asks users questions about missing information.

[0079] Users provide answers, and the conversational AI collects that information and, if necessary, obtains recommendations from stakeholders.

[0080] Step 8: Edit your resume

[0081] The server automatically updates the resume based on the new information obtained.

[0082] The modified resume is saved in the database.

[0083] Step 9: Notify the company

[0084] The server sends the modified resume to the company's database.

[0085] Companies will receive notifications to review the optimized resume and contact the job seeker.

[0086] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[0087] Example 1

[0088] 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."

[0089] The current recruitment system has a low accuracy in matching job seekers with companies, and the job information that job seekers apply for often does not match their own skills or experience. It is also difficult to efficiently collect information missing from job seekers' resumes, resulting in ineffective job searches. Companies also face the problem of not being able to hire the right people because they make hiring decisions based on incomplete resumes.

[0090] 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.

[0091] In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for analyzing uploaded resumes and identifying missing information, conversational AI means for hearing from job seekers about the missing information, means for correcting resumes based on the acquired missing information, and means for notifying and providing the corrected resumes to companies. This effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and enabling more efficient job and recruitment activities.

[0092] The "means for acquiring job information" is a function that enables the server to acquire information about job offers, such as job content, required skills, work location, and salary, provided by companies.

[0093] The "means for obtaining a job seeker's resume" is a function that enables the server to receive a job seeker's resume that lists their work experience, educational background, skills, qualifications, etc.

[0094] "Generative AI means" refers to an artificial intelligence function that analyzes job postings and job seekers' resumes and edits job postings to match the interests and aptitudes of job seekers in order to optimize job postings.

[0095] The "means for providing generated job information to job seekers" is a function for transmitting optimized job information to the job seeker's terminal so that the job seeker can view it.

[0096] "Analysis means" is a function for analyzing the uploaded resume of a job seeker and identifying missing information.

[0097] "Conversational AI tools" are artificial intelligence functions that interactively collect identified missing information from job seekers.

[0098] The "means for correcting a resume based on the acquired missing information" is a function for correcting a resume using the missing information collected from a job seeker.

[0099] The "means of notifying and providing the revised resume to the company" is a function for saving the revised resume in a database and notifying the company so that the resume can be checked.

[0100] MODE FOR CARRYING OUT THE INVENTION

[0101] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[0102] Overall overview

[0103] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[0104] Acquiring and storing job information

[0105] The server retrieves job information from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0106] Specific examples

[0107] When a company submits a new job posting to the server, the server analyzes the data and stores the information in a database. For example, if a company submits a job posting for a "software engineer," the server analyzes the job description and required skills and stores them in a database.

[0108] Acquiring and storing job seekers' resumes

[0109] Job seekers upload their resumes from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0110] Specific examples

[0111] When a job seeker uploads a resume, the server analyzes the data and stores it in a database. For example, if a job seeker uploads a resume for a "project manager," the server analyzes the job experience and qualifications held and stores them in a database.

[0112] Job Optimization with Generative AI

[0113] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[0114] Specific examples

[0115] The generative AI analyzes job postings for "data scientist" and optimizes them based on the job seeker's resume. For example, if a job seeker has skills in "Python" and "machine learning," the generative AI will optimize and provide job postings that utilize these skills.

[0116] Example prompt sentence:

[0117] "Analyze job postings and optimize them based on job seekers' resumes."

[0118] Identifying and interviewing missing information on resumes

[0119] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0120] Specific examples

[0121] If a job seeker uploads a resume for a "software tester," the server identifies the missing information: "Test automation experience is not listed." The conversational AI then asks the job seeker, "Tell me about your test automation experience," and the job seeker replies, "I have two years of experience in automated testing using TestNG." The server then corrects the resume based on the information obtained.

[0122] Example prompt sentence:

[0123] "Identify missing information on a job seeker's resume and collect that information."

[0124] Providing optimized resumes to companies

[0125] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0126] Specific examples

[0127] The server stores the optimized resume in a database and sends a notification to the company, which can then view the resume on the system and contact the job seeker.

[0128] Example prompt sentence:

[0129] "Please let companies know about your optimized resume so they can review it."

[0130] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Processing Steps

[0133] Step 1: Get job information

[0134] input:

[0135] Job information such as job description, required skills, work location, salary, etc. sent from the company's device.

[0136] Specific behavior:

[0137] Server: The server receives job information sent as an HTTP POST request from the company's device.

[0138] Data processing / calculation:

[0139] The server parses the received job information in JSON format and extracts the necessary fields (job description, skills, location, salary, etc.).

[0140] output:

[0141] Extracted job posting data.

[0142] Step 2: Save your job posting

[0143] input:

[0144] Job posting data extracted in step 1.

[0145] Specific behavior:

[0146] Server: The server converts the job data into the appropriate database format and stores it in the database using SQL queries.

[0147] Data processing / calculation:

[0148] The server converts the JSON data into an SQL INSERT statement.

[0149] output:

[0150] Job information stored in a database.

[0151] Step 3: Upload your resume

[0152] input:

[0153] Resume file (PDF or text format) sent from the job seeker's device.

[0154] Specific behavior:

[0155] Terminal (job seeker): Job seeker uploads resume file.

[0156] Data processing / calculation:

[0157] The file is sent to the server via an HTTP POST request.

[0158] output:

[0159] Resume file received by server.

[0160] Step 4: Save your resume

[0161] input:

[0162] Resume file received in Step 3.

[0163] Specific behavior:

[0164] Server: The server parses the received resume file, extracts the text, and stores it in a database.

[0165] Data processing / calculation:

[0166] Use OCR and text analysis tools to extract text from your resume and break it down into the necessary fields.

[0167] output:

[0168] Resume information stored in a database.

[0169] Step 5: Optimizing job listings with generative AI

[0170] input:

[0171] Job information data, resume information data.

[0172] Specific behavior:

[0173] Server: The server initializes the generative AI model and provides job postings and resume information to the model.

[0174] Data processing / calculation:

[0175] Generative AI analyzes input data and optimizes job listings based on the skills and aptitudes of job seekers.

[0176] output:

[0177] Optimized job listings.

[0178] An example of hardware is using a GPU server (e.g., NVIDIA GPU).

[0179] Step 6: Optimized job postings

[0180] input:

[0181] The optimized job listing generated in step 5.

[0182] Specific behavior:

[0183] Server: The server sends the optimized job information to the job seeker's device as an HTTP response.

[0184] Data processing / calculation:

[0185] Convert job information into HTML or JSON format and send it.

[0186] output:

[0187] Optimized job listings displayed on job seekers' devices.

[0188] Step 7: Identify missing information on your resume

[0189] input:

[0190] Saved resume information.

[0191] Specific behavior:

[0192] Server: The server analyzes the stored resume information and identifies any missing information.

[0193] Data processing / calculation:

[0194] Use NLP tools to analyze the text of the resume and extract missing information.

[0195] output:

[0196] A list of missing information.

[0197] Step 8: Start the hearing

[0198] input:

[0199] List of missing information, job seeker's terminal.

[0200] Specific behavior:

[0201] Server: The server initializes the conversational AI and sends questions to the job seeker to interactively gather missing information.

[0202] Data processing / calculation:

[0203] Use a conversational AI model (e.g., Dialogflow) to generate interview questions and collect answers from job seekers.

[0204] output:

[0205] Missing information collected.

[0206] Step 9: Edit your resume

[0207] input:

[0208] Missing information collected, existing resume information.

[0209] Specific behavior:

[0210] Server: The server corrects the resume based on the missing information obtained and updates the database.

[0211] Data processing / calculation:

[0212] The retrieved information is added to the appropriate fields in the resume and the database is updated using a SQL UPDATE statement.

[0213] output:

[0214] Revised resume information.

[0215] Step 10: Submit your resume to the company

[0216] input:

[0217] Revised resume information.

[0218] Specific behavior:

[0219] Server: The server stores the modified resume in a database and sends a notification to the company.

[0220] Data processing / calculation:

[0221] Format the revised resume and notify the company via a notification system (e.g. email, HTTP request).

[0222] output:

[0223] Revised resume notified to company.

[0224] These are the specific processing steps of the system, which effectively compare and optimize job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and making job searches and recruitment more efficient.

[0225] (Application example 1)

[0226] 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."

[0227] Conventional recruitment systems have a low matching accuracy between job information provided by companies and resumes submitted by job seekers, and companies often do not clearly state the specific skills and experience they are looking for in job seekers. Mismatches also often occur because job seekers are unable to effectively promote their own skills and experience. Furthermore, in certain industries, such as virtual store operators, effective matching is difficult because job information is not optimized and insufficient information on resumes is not fully supplemented. A system that can solve these issues and improve the matching accuracy between companies and job seekers is needed.

[0228] 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.

[0229] In this invention, the server includes means for acquiring job information, means for acquiring resumes of job seekers, generation AI means for comparing the job information with the resumes and optimizing the job information, means for providing the optimized job information to the smart device, analysis means for identifying missing information in the resume, conversational AI means for interactively hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to efficiently optimize job information and complete resumes, significantly improving the accuracy of matching between companies and job seekers.

[0230] "Job information" is information about a specific job, such as the job description, required skills, work location, and salary, that a company provides to job seekers.

[0231] A resume is a document in which a job seeker lists detailed information about their work experience, educational background, skills, qualifications, etc.

[0232] "Generative AI" is a technological means of analyzing and optimizing job postings and resumes using artificial intelligence techniques.

[0233] A "smart device" is a mobile terminal that has computer functions and can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[0234] "Analysis means" refers to technical means for analyzing the contents of a resume and identifying missing information.

[0235] "Conversational AI" is an artificial intelligence technology that uses natural language processing technology to converse with job seekers and collect missing information.

[0236] "Hearing" is the process in which conversational AI engages in an interactive dialogue with job seekers to collect necessary information.

[0237] This invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. This system consists of a server, job seeker terminals, and company terminals.

[0238] Overall overview

[0239] The server retrieves job postings and job seekers' resumes, optimizes the job postings using generative AI, and uses conversational AI to collect missing information from job seekers and correct their resumes.

[0240] Acquiring and storing job information

[0241] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0242] Acquiring and storing job seekers' resumes

[0243] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0244] Job Optimization with Generative AI

[0245] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The optimized job information is provided to the smart device so that the job seeker can view it.

[0246] Specific examples

[0247] Below are some example prompts that can be provided to a generative AI model:

[0248] Optimize your job listing:

[0249] Job Description: Sales Staff

[0250] Required skills: Customer service skills, communication skills

[0251] Location: Tokyo

[0252] Salary: From 1,200 yen per hour

[0253] Identifying and interviewing missing information on resumes

[0254] The server analyzes the uploaded resume and identifies missing information, including details of specific skills and experience, and then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0255] Specific examples

[0256] Below are some examples of prompts provided by conversational AI:

[0257] Please provide the missing information from your resume:

[0258] Work experience: Retail sales experience

[0259] Education: High school graduate

[0260] Tell us about your digital marketing skills

[0261] If a job seeker answers, "I have three years of experience using Google Analytics," the server will use this information to modify the resume.

[0262] Providing optimized resumes to companies

[0263] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0264] Hardware and Software Used

[0265] Hardware: Smartphones, smart glasses, head-mounted displays

[0266] Software: Python, OpenAI GPT-3, Cloud server

[0267] Data processing and calculation

[0268] The server uses a generative AI model (e.g., GPT-3) to optimize job information and create prompts. It also uses conversational AI to interact with job seekers and collect missing information, improving the accuracy of matching between companies and job seekers.

[0269] By using the above means, the present invention can efficiently optimize job information and complement resumes, significantly improving the accuracy of matching between companies and job seekers.

[0270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0271] Processing step flow

[0272] Step 1:

[0273] The server retrieves job information from companies. Companies enter job information using their terminals and send detailed information such as job content, required skills, work location, and salary to the server. The server stores this information in a database.

[0274] Input: Job information provided by the company

[0275] Output: Job listings stored in a database

[0276] Specific operation: A company employee enters job information into a terminal and sends it to the server, which receives it and stores it in a database.

[0277] Step 2:

[0278] Job seekers upload their resumes from their own devices, and the server receives the uploaded resumes and stores them in a database.

[0279] Input: Resume uploaded by job seeker

[0280] Output: Resume saved in database

[0281] Specific operation: A job seeker uploads his / her resume to the system using a terminal. The server receives the resume and stores it in the database.

[0282] Step 3:

[0283] The server initializes the generation AI and analyzes the job postings and resumes. The generation AI optimizes the job postings based on the analysis results.

[0284] Input: Job listings and resumes stored in a database

[0285] Output: Optimized job listings

[0286] How it works: The server initializes a generative AI model (e.g., GPT-3) and inputs the job posting and resume as prompts. The generative AI analyzes this and generates an optimized job posting.

[0287] Step 4:

[0288] The server provides optimized job information to smart devices, which job seekers can view.

[0289] Input: Optimized Job Postings

[0290] Output: Optimized job listings displayed on job seekers' smart devices

[0291] Specific operation: The server sends the optimized job information to the job seeker's smart device, where the job seeker can view it.

[0292] Step 5:

[0293] The server analyzes resumes to identify missing information, and uses conversational AI to interactively gather missing information from job seekers to identify specific skills and experience details.

[0294] Input: Saved Resume

[0295] Output: Identified missing information

[0296] Specific operation: The server initializes the conversational AI, analyzes the resume content to identify missing information, generates prompts to ask questions to the job seeker, and the job seeker answers.

[0297] Step 6:

[0298] Based on the missing information collected from the job seeker, the server amends the resume and stores it in a database.

[0299] Input: Collected information

[0300] Output: Revised resume

[0301] Specific operation: The server receives the missing information, corrects the resume, and saves the corrected resume in the database.

[0302] Step 7:

[0303] The server provides the revised resume to the company, which can review it and contact the job seeker.

[0304] Input: Revised resume

[0305] Output: The revised resume delivered to the company's terminal

[0306] Specific operation: The server retrieves the revised resume from the database and sends it to the company's terminal, where the company's personnel can review it.

[0307] Summary

[0308] This series of processing steps efficiently optimizes job information and complements resumes, significantly improving the accuracy of matching between companies and job seekers.

[0309] 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.

[0310] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. It also includes a mechanism for improving the reliability of collected information and the dialogue quality of conversational AI by combining it with an emotion engine that recognizes user emotions. The following describes in detail the embodiments of the present invention.

[0311] Overall overview

[0312] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[0313] Acquiring and storing job information

[0314] The server connects to the company's job database, retrieves the latest job postings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[0315] Acquiring and storing job seekers' resumes

[0316] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[0317] Job Optimization with Generative AI

[0318] The server initializes the generation AI and analyzes the job postings and resumes. Based on the results of this analysis, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[0319] Emotion recognition by emotion engine

[0320] An emotion engine is installed on the user's device and analyzes the emotions expressed when the job seeker types or interacts with the information. This emotion information is sent to the server and integrated with other data. The emotion engine analyzes emotions and evaluates the reliability of the information provided.

[0321] Identifying and interviewing missing information on resumes

[0322] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI interactively asks questions to the job seeker and collects information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions. If necessary, it also asks related parties of the job seeker for recommended information.

[0323] Specific examples

[0324] When Job Seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "Experience in digital marketing is not listed." The emotion engine analyzes Job Seeker A's stress level and determines that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A answers, "I've been using it for three years," this information is added to his / her resume.

[0325] Providing optimized resumes to companies

[0326] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0327] System Overview

[0328] This system processes the following steps in a series: acquiring job information, acquiring job seeker resumes, optimizing the job information using generative AI, recognizing emotions using an emotion engine, gathering missing information using conversational AI, and providing the optimized resumes to companies. This process achieves highly accurate matching between job seekers and companies.

[0329] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0330] The processing flow will be explained below.

[0331] Step 1: Get job information

[0332] The server establishes a connection to the company's job database.

[0333] The server runs a query to get the latest job listings.

[0334] The server saves the acquired job information in its database.

[0335] Step 2: Obtaining job seeker resumes

[0336] The user uploads a resume file to the system from their own device.

[0337] The server receives the resume file and stores it in a database.

[0338] Step 3: Initializing the generated AI

[0339] The server loads and initializes the generative AI model.

[0340] The server begins parsing the job listings and resumes.

[0341] Step 4: Optimize your job listing

[0342] The server uses generated AI to compare job postings with resume content.

[0343] Optimize job listings to match job seekers' interests and aptitudes.

[0344] The server sends the optimized job information to the job seeker's device.

[0345] Step 5: Initializing the Emotion Engine

[0346] The user's device activates the emotion engine.

[0347] The emotion engine analyzes the user's input and emotions during the conversation and sends them to the server.

[0348] Step 6: Identify missing information on your resume

[0349] The server analyzes the content of the received resume.

[0350] Based on the analysis results, the server identifies the missing information.

[0351] Step 7: Initializing the conversational AI

[0352] The server loads and initializes the conversational AI.

[0353] Sets the questions for the server to hear.

[0354] Step 8: Integrating hearing and sentiment analysis

[0355] The user initiates a dialogue with the conversational AI.

[0356] Conversational AI asks users questions about missing information.

[0357] The emotion engine analyzes the user's emotions in real time and sends the data to the server.

[0358] Conversational AI adjusts the content and timing of questions based on emotional data.

[0359] Step 9: Get Recommendations (Optional)

[0360] In addition to identifying missing information, the conversational AI will also ask the job seeker's associates for recommendations if necessary.

[0361] The server stores the obtained recommendation information.

[0362] Step 10: Edit your resume

[0363] The server automatically modifies the resume based on the new information and recommendations it obtains.

[0364] The modified resume is saved in the database.

[0365] Step 11: Notify the company

[0366] The server sends the modified resume to the company's database.

[0367] Companies will receive notifications to review the optimized resume and contact the job seeker.

[0368] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[0369] Example 2

[0370] 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."

[0371] Conventional systems for matching job information with job seekers' resumes have had problems with low matching accuracy between job seekers and companies due to insufficient optimization of job information and identification of missing information in resumes. Furthermore, interactive interviews and optimizations are performed without taking into account the feelings of job seekers, resulting in low dialogue quality and information reliability. This has made it difficult for both job seekers and companies to carry out efficient recruitment and job search activities.

[0372] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring a job seeker's resume, generation AI means for comparing the job information with the resume and optimizing the job information, means for providing the generated job information to the job seeker, means including an emotion engine for analyzing the job seeker's emotions, analysis means for identifying missing information in the resume, conversational AI means for hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to collect and optimize information while taking the job seeker's emotions into consideration, and achieves highly accurate matching between job seekers and companies.

[0373] "Means of obtaining job information" refers to a system that accesses a company's job database and obtains detailed information such as job content, required skills, work location, and salary.

[0374] "Means for obtaining job seekers' resumes" refers to a system for receiving and storing resume data uploaded by job seekers to the system from their own devices.

[0375] "Generative AI methods" refers to artificial intelligence technologies used to analyze job postings and resumes and optimize job postings based on job seekers' interests and aptitudes.

[0376] The "means for providing the generated job information to job seekers" is a mechanism for transmitting optimized job information to the job seekers' terminals so that the job seekers can view it.

[0377] "Means including an emotion engine" refers to technology for analyzing emotions in job seeker inputs and interactions and integrating the emotion information with other data.

[0378] The "analysis means for identifying missing information in a resume" is a method by which the server analyzes an uploaded resume and identifies missing information.

[0379] "Conversational AI means for gathering missing information from job seekers" is a conversational artificial intelligence technology that asks interactive questions based on identified missing information and gathers information from job seekers.

[0380] A "resume correction method" is a system for updating and completing a resume based on the collected information.

[0381] The "means of providing the company with the revised resume" is a mechanism for storing the revised resume in the company's database and notifying the company.

[0382] The above are definitions of the important terms included in the claims of the present invention.

[0383] The present invention is a system that effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system improves the reliability of collected information and enhances the dialogue quality of conversational AI. The following describes in detail the embodiments of the present invention.

[0384] Overall overview

[0385] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[0386] Acquiring and storing job information

[0387] The server connects to the company's job database to retrieve the latest job listings and store them in the database. For example, it sends an API request to retrieve the job listings, parses the data received in JSON format, and stores it in the database. This database contains details such as job description, required skills, location, salary, etc.

[0388] Acquiring and storing job seekers' resumes

[0389] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes, determines the path to store them on the file server, and then saves the file path and other related information in the database. This operation saves information such as the job seeker's work experience, educational background, skills, and qualifications.

[0390] Job Optimization with Generative AI

[0391] The server initializes a generative AI model and analyzes job postings and resumes. Typically, OpenAI's GPT-3 is used. Based on the analysis results, the generative AI reconstructs the job postings in a format that is optimal for the job seeker. This generated job posting is then sent from the server to the job seeker's device, where it can be viewed by the job seeker.

[0392] Prompt Sentence Examples

[0393] Here are some example prompts to input to a generative AI model:

[0394] Analyze the job postings and job seekers' resumes below and optimize your job postings based on the job seekers' interests and aptitudes.

[0395] Job information:

[0396] 1. Job Description: Digital Marketing Specialist

[0397] 2. Required skills: SEO, SEM, Google Analytics

[0398] 3. Work location: Tokyo

[0399] 4. Salary: 300,000 to 400,000 yen per month

[0400] Job Seeker's Resume:

[0401] 1. Work experience: SNS management, content marketing

[0402] 2. Education: Graduated from the Faculty of Economics at XXXX University

[0403] 3. Skills: Social media management, content creation

[0404] Emotion recognition by emotion engine

[0405] An emotion engine is installed on the job seeker's device and analyzes the emotion expressed when the job seeker types or interacts with the system. For example, it uses technologies such as facial expression recognition and voice tone analysis. This emotion information is sent to a server and integrated with other data. The emotion engine analyzes the job seeker's emotional state and evaluates the reliability of the information provided.

[0406] Identifying and interviewing missing information on resumes

[0407] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI asks interactive questions to the job seeker to collect information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions.

[0408] Specific examples

[0409] When a job seeker uploads a resume, the server analyzes it and identifies missing information, such as "digital marketing experience." The emotion engine analyzes the job seeker's stress level and determines that they are relaxed. Based on this, the conversational AI asks, "Tell me about your experience with Google Analytics." If the job seeker replies, "I've been using it for three years," this information is added to the resume.

[0410] Providing optimized resumes to companies

[0411] The server saves the revised resume in a database and sends a notification to the company's terminal. The company receives the notification and can contact the job seeker, for example, by email or phone.

[0412] This series of processes will enable highly accurate matching between job seekers and companies, which is expected to make job-seeking and recruitment activities more effective and efficient.

[0413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0414] Step 1: Retrieve and save job information

[0415] The server accesses the company's job database to retrieve the latest job listings, sends an API request, and parses the data received in JSON format. This parsed data includes the job description, required skills, location, salary, etc. The server then stores this data in a database.

[0416] Input: Job information from the company's job database (JSON format)

[0417] Data processing: Analyze JSON format data and extract necessary fields

[0418] Output: Job listings stored in a database

[0419] Specific behavior:

[0420] Creating and Sending API Requests

[0421] Parsing received JSON data

[0422] Extract required fields and generate SQL statements

[0423] Executes an insert statement into the database

[0424] Step 2: Capture and store job seeker resumes

[0425] A job seeker uploads his / her resume to the system from his / her own device. The server receives the uploaded file and determines the path to store it on the file server. Then the server stores the file path and other related information in the database.

[0426] Input: Resume file uploaded by job seeker

[0427] Data processing: receiving files and determining the save path

[0428] Output: File paths and related information stored in the database

[0429] Specific behavior:

[0430] Display the upload form

[0431] Uploading a file

[0432] The server receives the file and generates a save path.

[0433] Stores file paths and related information in a database

[0434] Step 3: Optimizing job listings with generative AI

[0435] The server initializes the generative AI model and analyzes the job posting and resume. It generates a prompt and sends it to the generative AI. This generative AI then optimizes and reconstructs the job posting based on the input data. The optimized job posting is then sent to the job seeker's device.

[0436] Input: Job posting and job seeker resume

[0437] Data processing: Prompt generation and input to the AI ​​model

[0438] Output: Optimized job listings

[0439] Specific behavior:

[0440] Generate prompt statement

[0441] Sending prompts to the generation AI

[0442] Parsing output from generative AI models

[0443] Sending optimized job information to job seekers' devices

[0444] Step 4: Emotion Recognition with the Emotion Engine

[0445] The emotion engine analyzes the emotions expressed by job seekers when they input or interact with the system, and sends the results to the server. The input data is the job seeker's facial expressions and tone of voice, which are analyzed and output as emotional information. The server then integrates this emotional information with other data.

[0446] Input: Job seeker's facial expressions and tone of voice

[0447] Data processing: Sentiment analysis

[0448] Output: Parsed emotion data

[0449] Specific behavior:

[0450] Capture facial and voice data

[0451] Analysis by emotion engine

[0452] Generating emotion data and sending it to the server

[0453] Step 5: Identify missing information on your resume and ask questions

[0454] The server analyzes the uploaded resume and identifies missing information. The conversational AI interactively asks questions based on the missing information and collects information. The emotion engine adjusts the content and timing of the questions based on the emotional information obtained.

[0455] Input: Uploaded resume

[0456] Data processing: Resume analysis and identification of missing information

[0457] Output: A list of missing information and any additional information collected.

[0458] Specific behavior:

[0459] Resume analysis

[0460] Identifying missing information

[0461] Conversational AI generates and sends questions

[0462] Collect job seeker responses and update resumes

[0463] Step 6: Submit your optimized resume to employers

[0464] The server saves the revised resume in a database and notifies the company's terminal, allowing the company to view the revised resume and contact the job seeker.

[0465] Input: Revised resume

[0466] Data processing: storing in database and notifying companies

[0467] Output: Company confirmation of revised resume

[0468] Specific behavior:

[0469] Save the revised resume to the database

[0470] Notifications to corporate devices

[0471] Allowing companies to view your revised resume and establish contact

[0472] (Application example 2)

[0473] 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."

[0474] Current job and job seeker information matching systems have limitations in optimizing and complementing information, making it difficult to accurately match job seekers and companies. It is also difficult to understand customer needs in real time and recommend optimal products in physical stores. Therefore, it is necessary to achieve more efficient and effective matching and product recommendations.

[0475] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for identifying missing information in resumes, conversational AI means for hearing the missing information from job seekers, means for correcting resumes based on the acquired information, means for providing the corrected resumes to companies, means for acquiring product information, emotion analysis means for recognizing customer emotions, recommendation engine means for recommending products based on emotions, and interactive AI means for interacting with customers. This enables highly accurate matching of job information with job seeker resumes, and also realizes product recommendations based on customer needs in physical stores.

[0476] The "means for obtaining job information" refers to a device or program that allows the server to obtain detailed information such as job content, required skills, work location, and salary offered by companies.

[0477] The "means for obtaining a job seeker's resume" refers to a device or program that allows a job seeker to upload a resume containing information about their work experience, educational background, skills, qualifications, etc. to a server.

[0478] A "generative AI means" is a device or program that uses artificial intelligence to compare job postings with resumes and optimize the job postings based on the job seeker's interests and aptitudes.

[0479] "Means for providing job seekers with generated job information" refers to a device or program for transmitting job information optimized by the generating AI means to job seekers and making it viewable.

[0480] The "analysis means for identifying missing information in a resume" is a device or program for analyzing a resume and identifying missing information.

[0481] A "conversational AI means for gathering missing information from job seekers" is a device or program that uses artificial intelligence to interactively ask job seekers questions based on the missing information and gather information.

[0482] "Means for amending a resume based on acquired information" refers to a device or program for amending or supplementing the contents of a resume based on information acquired by a conversational AI means.

[0483] "Means for providing revised resumes to employers" refers to a device or program that notifies employers of revised or supplemented resumes and makes them available for viewing.

[0484] The "means for acquiring product information" refers to a device or program that allows the server to acquire information about products available in-store or online.

[0485] The "emotion analysis means for recognizing customer emotions" is a device or program for analyzing video data from a camera in smart glasses or a head-mounted display and recognizing the emotional state of a customer.

[0486] The "recommendation engine means for recommending products based on emotions" is a device or program for recommending products that a customer is interested in based on the results of emotion analysis.

[0487] "Interactive AI means for interacting with customers" refers to a device or program that uses artificial intelligence to interactively respond to customer questions in real time.

[0488] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Furthermore, by combining this system with an emotion engine that recognizes user emotions, the accuracy of product recommendations in physical stores can also be improved. The following describes in detail the embodiments of the present invention.

[0489] Overall system configuration

[0490] The system consists of a server, job seekers' devices, company devices, and customers' hardware in physical stores (smart glasses, head-mounted displays, etc.). The server optimizes and complements information using the following main means:

[0491] Acquiring and storing job information

[0492] The server connects to the company's job database, retrieves the latest job listings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[0493] Acquiring and storing job seekers' resumes

[0494] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[0495] Job Optimization with Generative AI

[0496] The server initializes the generation AI and analyzes the job postings and resumes. Based on the analysis results, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[0497] Emotion recognition by emotion engine

[0498] The emotion engine is installed on the devices (smart glasses, head-mounted displays, etc.) of job seekers and customers in brick-and-mortar stores. It analyzes emotions from facial expressions and other data via the device's camera and sends this emotional information to a server. The emotion analysis data is used to optimize job search and shopping experiences.

[0499] Specific examples

[0500] For example, consider the case where Job Seeker A uploads his / her resume to the system. The server analyzes the resume and identifies missing information, such as "experience in digital marketing." The emotion engine analyzes Job Seeker A's stress level and finds that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A replies, "I've been using it for three years," this information is added to his / her resume.

[0501] Acquisition and provision of product information in physical stores

[0502] The server connects to the store's product database, retrieves the latest product information, inventory information, and sale information, and stores it in the database. When a customer wearing smart glasses or a head-mounted display looks at products in the store, the camera analyzes the customer's line of sight and sends the information to the server.

[0503] Emotion-based product recommendations

[0504] The emotion engine analyzes customer facial expression data to identify products they are interested in. Generative AI uses that information to recommend related products. This process improves customer satisfaction because customers are presented with product suggestions based on their interests.

[0505] Prompt Sentence Examples

[0506] "When a customer points a product at the camera, use an emotion engine to analyze whether they are interested in that product, and if they are, generate a program that displays recommendations for related products."

[0507] The above is a specific embodiment of the present invention. By using this system, effective and efficient matching and recommendations can be achieved in both recruitment and job-seeking activities, as well as in the in-store shopping experience.

[0508] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0509] Step 1:

[0510] Acquiring and saving job information: Connect to the company's job database and acquire the latest job information. The server automatically acquires job information (job description, required skills, work location, salary, etc.) and saves it in the database. The input is the company's job database, and the output is the job information saved in the server's database.

[0511] Step 2:

[0512] Acquiring and storing job seeker resumes: Job seekers upload their resumes to the system using their own devices. The server receives the resumes and stores them in a database in a parsable format. The input is the job seeker's resume, and the output is the resume stored in the server's database.

[0513] Step 3:

[0514] Optimization of job postings using generation AI: The server initializes the generation AI, which compares and analyzes job postings and resumes. Based on the analysis results, the generation AI optimizes job postings to match the interests and aptitudes of job seekers and generates customized job postings. The input is the job posting and resume, and the output is the optimized job postings.

[0515] Step 4:

[0516] Providing optimized job information: The server sends the job information optimized by the generation AI to the job seeker's device, where it can be viewed by the job seeker. The input is the optimized job information, and the output is customized job information displayed on the job seeker's device.

[0517] Step 5:

[0518] Identifying missing information in a resume: The server analyzes the job seeker's resume and identifies the missing information. The input is the job seeker's resume, and the output is a list of missing information.

[0519] Step 6:

[0520] Hearing for missing information: Conversational AI interactively asks questions to job seekers based on the identified missing information to collect information. An emotion engine analyzes the job seeker's emotional state and adjusts the content and timing of the questions. The input is a list of missing information and the job seeker's response, and the output is the collected additional information.

[0521] Step 7:

[0522] Resume Modification: The server modifies the job seeker's resume based on the additional information collected. The input is the additional information collected, and the output is the modified resume.

[0523] Step 8:

[0524] Providing the revised resume to the company: The server saves the revised resume in the database and notifies the relevant company. The company can check the revised resume and contact the job seeker. The input is the revised resume, and the output is the revised resume notified to the company.

[0525] Step 9:

[0526] Obtaining product information: The server connects to the product database of the physical store, obtains the latest product information, stock information, and sale information, and stores it in the database. The input is the product database of the physical store, and the output is the product information stored in the server's database.

[0527] Step 10:

[0528] Customer emotion analysis: Customer facial expression data is collected through the camera in smart glasses or head-mounted displays and analyzed using an emotion engine. The input is the customer facial expression data, and the output is the customer emotion analysis results.

[0529] Step 11:

[0530] Emotion-based product recommendation: Based on the results of emotion analysis, the generative AI recommends related products. The recommendation engine selects the most suitable products from the product database and proposes them to the customer. The input is the result of the customer's emotion analysis, and the output is recommended product information.

[0531] Step 12:

[0532] Interacting with customers: Conversational AI responds interactively to customer questions and feedback, providing product information and related information. The input is the customer's question, and the output is the response from the conversational AI.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] [Second embodiment]

[0537] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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."

[0549] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[0550] Overall overview

[0551] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[0552] Acquiring and storing job information

[0553] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0554] Acquiring and storing job seekers' resumes

[0555] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0556] Job Optimization with Generative AI

[0557] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[0558] Identifying and interviewing missing information on resumes

[0559] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0560] Specific examples

[0561] When job seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "experience in digital marketing." When the conversational AI asks job seeker A, "Tell us about your digital marketing skills," job seeker A responds, "I have three years of experience using Google Analytics." The server then corrects the resume based on the information obtained.

[0562] Providing optimized resumes to companies

[0563] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0564] System Overview

[0565] This system processes the following steps in a single sequence: acquiring job information, acquiring job seeker resumes, optimizing the job information using generation AI, gathering missing information using conversational AI, and providing the optimized resumes to companies. This can significantly improve the accuracy of matching job seekers and companies.

[0566] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0567] The processing flow will be explained below.

[0568] Step 1: Get job information

[0569] The server establishes a connection to the company's job database.

[0570] The server runs a query to get the latest job listings.

[0571] The acquired job information is saved in the server database.

[0572] Step 2: Obtaining job seeker resumes

[0573] The user uploads a resume file to the system from their own device.

[0574] The server receives the resume file and stores it in a database.

[0575] Step 3: Initializing the generated AI

[0576] The server loads and initializes the generative AI model.

[0577] The server begins parsing the job listings and resumes.

[0578] Step 4: Optimize your job listing

[0579] The server uses generated AI to compare job postings with resume content.

[0580] AI generates and edits job information that best suits the interests and aptitudes of job seekers.

[0581] The server sends the optimized job information to the job seeker's device.

[0582] Step 5: Identify missing information on your resume

[0583] The server analyzes the content of the received resume.

[0584] The server identifies the missing information based on the analysis results.

[0585] Step 6: Initializing the conversational AI

[0586] The server loads and initializes the conversational AI.

[0587] The server uses conversational AI to set questions to obtain missing information.

[0588] Step 7: Hearing

[0589] The user initiates a dialogue with the conversational AI.

[0590] Conversational AI asks users questions about missing information.

[0591] Users provide answers, and the conversational AI collects that information and, if necessary, obtains recommendations from stakeholders.

[0592] Step 8: Edit your resume

[0593] The server automatically updates the resume based on the new information obtained.

[0594] The modified resume is saved in the database.

[0595] Step 9: Notify the company

[0596] The server sends the modified resume to the company's database.

[0597] Companies will receive notifications to review the optimized resume and contact the job seeker.

[0598] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[0599] Example 1

[0600] 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."

[0601] The current recruitment system has a low accuracy in matching job seekers with companies, and the job information that job seekers apply for often does not match their own skills or experience. It is also difficult to efficiently collect information missing from job seekers' resumes, resulting in ineffective job searches. Companies also face the problem of not being able to hire the right people because they make hiring decisions based on incomplete resumes.

[0602] 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.

[0603] In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for analyzing uploaded resumes and identifying missing information, conversational AI means for hearing from job seekers about the missing information, means for correcting resumes based on the acquired missing information, and means for notifying and providing the corrected resumes to companies. This effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and enabling more efficient job and recruitment activities.

[0604] The "means for acquiring job information" is a function that enables the server to acquire information about job offers, such as job content, required skills, work location, and salary, provided by companies.

[0605] The "means for obtaining a job seeker's resume" is a function that enables the server to receive a job seeker's resume that lists their work experience, educational background, skills, qualifications, etc.

[0606] "Generative AI means" refers to an artificial intelligence function that analyzes job postings and job seekers' resumes and edits job postings to match the interests and aptitudes of job seekers in order to optimize job postings.

[0607] The "means for providing generated job information to job seekers" is a function for transmitting optimized job information to the job seeker's terminal so that the job seeker can view it.

[0608] "Analysis means" is a function for analyzing the uploaded resume of a job seeker and identifying missing information.

[0609] "Conversational AI tools" are artificial intelligence functions that interactively collect identified missing information from job seekers.

[0610] The "means for correcting a resume based on the acquired missing information" is a function for correcting a resume using the missing information collected from a job seeker.

[0611] The "means of notifying and providing the revised resume to the company" is a function for saving the revised resume in a database and notifying the company so that the resume can be checked.

[0612] MODE FOR CARRYING OUT THE INVENTION

[0613] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[0614] Overall overview

[0615] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[0616] Acquiring and storing job information

[0617] The server retrieves job information from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0618] Specific examples

[0619] When a company submits a new job posting to the server, the server analyzes the data and stores the information in a database. For example, if a company submits a job posting for a "software engineer," the server analyzes the job description and required skills and stores them in a database.

[0620] Acquiring and storing job seekers' resumes

[0621] Job seekers upload their resumes from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0622] Specific examples

[0623] When a job seeker uploads a resume, the server analyzes the data and stores it in a database. For example, if a job seeker uploads a resume for a "project manager," the server analyzes the job experience and qualifications held and stores them in a database.

[0624] Job Optimization with Generative AI

[0625] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[0626] Specific examples

[0627] The generative AI analyzes job postings for "data scientist" and optimizes them based on the job seeker's resume. For example, if a job seeker has skills in "Python" and "machine learning," the generative AI will optimize and provide job postings that utilize these skills.

[0628] Example prompt sentence:

[0629] "Analyze job postings and optimize them based on job seekers' resumes."

[0630] Identifying and interviewing missing information on resumes

[0631] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0632] Specific examples

[0633] If a job seeker uploads a resume for a "software tester," the server identifies the missing information: "Test automation experience is not listed." The conversational AI then asks the job seeker, "Tell me about your test automation experience," and the job seeker replies, "I have two years of experience in automated testing using TestNG." The server then corrects the resume based on the information obtained.

[0634] Example prompt sentence:

[0635] "Identify missing information on a job seeker's resume and collect that information."

[0636] Providing optimized resumes to companies

[0637] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0638] Specific examples

[0639] The server stores the optimized resume in a database and sends a notification to the company, which can then view the resume on the system and contact the job seeker.

[0640] Example prompt sentence:

[0641] "Please let companies know about your optimized resume so they can review it."

[0642] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0644] Processing Steps

[0645] Step 1: Get job information

[0646] input:

[0647] Job information such as job description, required skills, work location, salary, etc. sent from the company's device.

[0648] Specific behavior:

[0649] Server: The server receives job information sent as an HTTP POST request from the company's device.

[0650] Data processing / calculation:

[0651] The server parses the received job information in JSON format and extracts the necessary fields (job description, skills, location, salary, etc.).

[0652] output:

[0653] Extracted job posting data.

[0654] Step 2: Save your job posting

[0655] input:

[0656] Job posting data extracted in step 1.

[0657] Specific behavior:

[0658] Server: The server converts the job data into the appropriate database format and stores it in the database using SQL queries.

[0659] Data processing / calculation:

[0660] The server converts the JSON data into an SQL INSERT statement.

[0661] output:

[0662] Job information stored in a database.

[0663] Step 3: Upload your resume

[0664] input:

[0665] Resume file (PDF or text format) sent from the job seeker's device.

[0666] Specific behavior:

[0667] Terminal (job seeker): Job seeker uploads resume file.

[0668] Data processing / calculation:

[0669] The file is sent to the server via an HTTP POST request.

[0670] output:

[0671] Resume file received by server.

[0672] Step 4: Save your resume

[0673] input:

[0674] Resume file received in Step 3.

[0675] Specific behavior:

[0676] Server: The server parses the received resume file, extracts the text, and stores it in a database.

[0677] Data processing / calculation:

[0678] Use OCR and text analysis tools to extract text from your resume and break it down into the necessary fields.

[0679] output:

[0680] Resume information stored in a database.

[0681] Step 5: Optimizing job listings with generative AI

[0682] input:

[0683] Job information data, resume information data.

[0684] Specific behavior:

[0685] Server: The server initializes the generative AI model and provides job postings and resume information to the model.

[0686] Data processing / calculation:

[0687] Generative AI analyzes input data and optimizes job listings based on the skills and aptitudes of job seekers.

[0688] output:

[0689] Optimized job listings.

[0690] An example of hardware is using a GPU server (e.g., NVIDIA GPU).

[0691] Step 6: Optimized job postings

[0692] input:

[0693] The optimized job listing generated in step 5.

[0694] Specific behavior:

[0695] Server: The server sends the optimized job information to the job seeker's device as an HTTP response.

[0696] Data processing / calculation:

[0697] Convert job information into HTML or JSON format and send it.

[0698] output:

[0699] Optimized job listings displayed on job seekers' devices.

[0700] Step 7: Identify missing information on your resume

[0701] input:

[0702] Saved resume information.

[0703] Specific behavior:

[0704] Server: The server analyzes the stored resume information and identifies any missing information.

[0705] Data processing / calculation:

[0706] Use NLP tools to analyze the text of the resume and extract missing information.

[0707] output:

[0708] A list of missing information.

[0709] Step 8: Start the hearing

[0710] input:

[0711] List of missing information, job seeker's terminal.

[0712] Specific behavior:

[0713] Server: The server initializes the conversational AI and sends questions to the job seeker to interactively gather missing information.

[0714] Data processing / calculation:

[0715] Use a conversational AI model (e.g., Dialogflow) to generate interview questions and collect answers from job seekers.

[0716] output:

[0717] Missing information collected.

[0718] Step 9: Edit your resume

[0719] input:

[0720] Missing information collected, existing resume information.

[0721] Specific behavior:

[0722] Server: The server corrects the resume based on the missing information obtained and updates the database.

[0723] Data processing / calculation:

[0724] The retrieved information is added to the appropriate fields in the resume and the database is updated using a SQL UPDATE statement.

[0725] output:

[0726] Revised resume information.

[0727] Step 10: Submit your resume to the company

[0728] input:

[0729] Revised resume information.

[0730] Specific behavior:

[0731] Server: The server stores the modified resume in a database and sends a notification to the company.

[0732] Data processing / calculation:

[0733] Format the revised resume and notify the company via a notification system (e.g. email, HTTP request).

[0734] output:

[0735] Revised resume notified to company.

[0736] These are the specific processing steps of the system, which effectively compare and optimize job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and making job searches and recruitment more efficient.

[0737] (Application example 1)

[0738] 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."

[0739] Conventional recruitment systems have a low matching accuracy between job information provided by companies and resumes submitted by job seekers, and companies often do not clearly state the specific skills and experience they are looking for in job seekers. Mismatches also often occur because job seekers are unable to effectively promote their own skills and experience. Furthermore, in certain industries, such as virtual store operators, effective matching is difficult because job information is not optimized and insufficient information on resumes is not fully supplemented. A system that can solve these issues and improve the matching accuracy between companies and job seekers is needed.

[0740] 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.

[0741] In this invention, the server includes means for acquiring job information, means for acquiring resumes of job seekers, generation AI means for comparing the job information with the resumes and optimizing the job information, means for providing the optimized job information to the smart device, analysis means for identifying missing information in the resume, conversational AI means for interactively hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to efficiently optimize job information and complete resumes, significantly improving the accuracy of matching between companies and job seekers.

[0742] "Job information" is information about a specific job, such as the job description, required skills, work location, and salary, that a company provides to job seekers.

[0743] A resume is a document in which a job seeker lists detailed information about their work experience, educational background, skills, qualifications, etc.

[0744] "Generative AI" is a technological means of analyzing and optimizing job postings and resumes using artificial intelligence techniques.

[0745] A "smart device" is a mobile terminal that has computer functions and can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[0746] "Analysis means" refers to technical means for analyzing the contents of a resume and identifying missing information.

[0747] "Conversational AI" is an artificial intelligence technology that uses natural language processing technology to converse with job seekers and collect missing information.

[0748] "Hearing" is the process in which conversational AI engages in an interactive dialogue with job seekers to collect necessary information.

[0749] This invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. This system consists of a server, job seeker terminals, and company terminals.

[0750] Overall overview

[0751] The server retrieves job postings and job seekers' resumes, optimizes the job postings using generative AI, and uses conversational AI to collect missing information from job seekers and correct their resumes.

[0752] Acquiring and storing job information

[0753] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[0754] Acquiring and storing job seekers' resumes

[0755] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[0756] Job Optimization with Generative AI

[0757] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The optimized job information is provided to the smart device so that the job seeker can view it.

[0758] Specific examples

[0759] Below are some example prompts that can be provided to a generative AI model:

[0760] Optimize your job listing:

[0761] Job Description: Sales Staff

[0762] Required skills: Customer service skills, communication skills

[0763] Location: Tokyo

[0764] Salary: From 1,200 yen per hour

[0765] Identifying and interviewing missing information on resumes

[0766] The server analyzes the uploaded resume and identifies missing information, including details of specific skills and experience, and then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[0767] Specific examples

[0768] Below are some examples of prompts provided by conversational AI:

[0769] Please provide the missing information from your resume:

[0770] Work experience: Retail sales experience

[0771] Education: High school graduate

[0772] Tell us about your digital marketing skills

[0773] If a job seeker answers, "I have three years of experience using Google Analytics," the server will use this information to modify the resume.

[0774] Providing optimized resumes to companies

[0775] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0776] Hardware and Software Used

[0777] Hardware: Smartphones, smart glasses, head-mounted displays

[0778] Software: Python, OpenAI GPT-3, Cloud server

[0779] Data processing and calculation

[0780] The server uses a generative AI model (e.g., GPT-3) to optimize job information and create prompts. It also uses conversational AI to interact with job seekers and collect missing information, improving the accuracy of matching between companies and job seekers.

[0781] By using the above means, the present invention can efficiently optimize job information and complement resumes, significantly improving the accuracy of matching between companies and job seekers.

[0782] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0783] Processing step flow

[0784] Step 1:

[0785] The server retrieves job information from companies. Companies enter job information using their terminals and send detailed information such as job content, required skills, work location, and salary to the server. The server stores this information in a database.

[0786] Input: Job information provided by the company

[0787] Output: Job listings stored in a database

[0788] Specific operation: A company employee enters job information into a terminal and sends it to the server, which receives it and stores it in a database.

[0789] Step 2:

[0790] Job seekers upload their resumes from their own devices, and the server receives the uploaded resumes and stores them in a database.

[0791] Input: Resume uploaded by job seeker

[0792] Output: Resume saved in database

[0793] Specific operation: A job seeker uploads his / her resume to the system using a terminal. The server receives the resume and stores it in the database.

[0794] Step 3:

[0795] The server initializes the generation AI and analyzes the job postings and resumes. The generation AI optimizes the job postings based on the analysis results.

[0796] Input: Job listings and resumes stored in a database

[0797] Output: Optimized job listings

[0798] How it works: The server initializes a generative AI model (e.g., GPT-3) and inputs the job posting and resume as prompts. The generative AI analyzes this and generates an optimized job posting.

[0799] Step 4:

[0800] The server provides optimized job information to smart devices, which job seekers can view.

[0801] Input: Optimized Job Postings

[0802] Output: Optimized job listings displayed on job seekers' smart devices

[0803] Specific operation: The server sends the optimized job information to the job seeker's smart device, where the job seeker can view it.

[0804] Step 5:

[0805] The server analyzes resumes to identify missing information, and uses conversational AI to interactively gather missing information from job seekers to identify specific skills and experience details.

[0806] Input: Saved Resume

[0807] Output: Identified missing information

[0808] Specific operation: The server initializes the conversational AI, analyzes the resume content to identify missing information, generates prompts to ask questions to the job seeker, and the job seeker answers.

[0809] Step 6:

[0810] Based on the missing information collected from the job seeker, the server amends the resume and stores it in a database.

[0811] Input: Collected information

[0812] Output: Revised resume

[0813] Specific operation: The server receives the missing information, corrects the resume, and saves the corrected resume in the database.

[0814] Step 7:

[0815] The server provides the revised resume to the company, which can review it and contact the job seeker.

[0816] Input: Revised resume

[0817] Output: The revised resume delivered to the company's terminal

[0818] Specific operation: The server retrieves the revised resume from the database and sends it to the company's terminal, where the company's personnel can review it.

[0819] Summary

[0820] This series of processing steps efficiently optimizes job information and complements resumes, significantly improving the accuracy of matching between companies and job seekers.

[0821] 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.

[0822] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. It also includes a mechanism for improving the reliability of collected information and the dialogue quality of conversational AI by combining it with an emotion engine that recognizes user emotions. The following describes in detail the embodiments of the present invention.

[0823] Overall overview

[0824] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[0825] Acquiring and storing job information

[0826] The server connects to the company's job database, retrieves the latest job postings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[0827] Acquiring and storing job seekers' resumes

[0828] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[0829] Job Optimization with Generative AI

[0830] The server initializes the generation AI and analyzes the job postings and resumes. Based on the results of this analysis, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[0831] Emotion recognition by emotion engine

[0832] An emotion engine is installed on the user's device and analyzes the emotions expressed when the job seeker types or interacts with the information. This emotion information is sent to the server and integrated with other data. The emotion engine analyzes emotions and evaluates the reliability of the information provided.

[0833] Identifying and interviewing missing information on resumes

[0834] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI interactively asks questions to the job seeker and collects information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions. If necessary, it also asks related parties of the job seeker for recommended information.

[0835] Specific examples

[0836] When Job Seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "Experience in digital marketing is not listed." The emotion engine analyzes Job Seeker A's stress level and determines that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A answers, "I've been using it for three years," this information is added to his / her resume.

[0837] Providing optimized resumes to companies

[0838] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[0839] System Overview

[0840] This system processes the following steps in a series: acquiring job information, acquiring job seeker resumes, optimizing the job information using generative AI, recognizing emotions using an emotion engine, gathering missing information using conversational AI, and providing the optimized resumes to companies. This process achieves highly accurate matching between job seekers and companies.

[0841] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[0842] The processing flow will be explained below.

[0843] Step 1: Get job information

[0844] The server establishes a connection to the company's job database.

[0845] The server runs a query to get the latest job listings.

[0846] The server saves the acquired job information in its database.

[0847] Step 2: Obtaining job seeker resumes

[0848] The user uploads a resume file to the system from their own device.

[0849] The server receives the resume file and stores it in a database.

[0850] Step 3: Initializing the generated AI

[0851] The server loads and initializes the generative AI model.

[0852] The server begins parsing the job listings and resumes.

[0853] Step 4: Optimize your job listing

[0854] The server uses generated AI to compare job postings with resume content.

[0855] Optimize job listings to match job seekers' interests and aptitudes.

[0856] The server sends the optimized job information to the job seeker's device.

[0857] Step 5: Initializing the Emotion Engine

[0858] The user's device activates the emotion engine.

[0859] The emotion engine analyzes the user's input and emotions during the conversation and sends them to the server.

[0860] Step 6: Identify missing information on your resume

[0861] The server analyzes the content of the received resume.

[0862] Based on the analysis results, the server identifies the missing information.

[0863] Step 7: Initializing the conversational AI

[0864] The server loads and initializes the conversational AI.

[0865] Sets the questions for the server to hear.

[0866] Step 8: Integrating hearing and sentiment analysis

[0867] The user initiates a dialogue with the conversational AI.

[0868] Conversational AI asks users questions about missing information.

[0869] The emotion engine analyzes the user's emotions in real time and sends the data to the server.

[0870] Conversational AI adjusts the content and timing of questions based on emotional data.

[0871] Step 9: Get Recommendations (Optional)

[0872] In addition to identifying missing information, the conversational AI will also ask the job seeker's associates for recommendations if necessary.

[0873] The server stores the obtained recommendation information.

[0874] Step 10: Edit your resume

[0875] The server automatically modifies the resume based on the new information and recommendations it obtains.

[0876] The modified resume is saved in the database.

[0877] Step 11: Notify the company

[0878] The server sends the modified resume to the company's database.

[0879] Companies will receive notifications to review the optimized resume and contact the job seeker.

[0880] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[0881] Example 2

[0882] 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."

[0883] Conventional systems for matching job information with job seekers' resumes have had problems with low matching accuracy between job seekers and companies due to insufficient optimization of job information and identification of missing information in resumes. Furthermore, interactive interviews and optimizations are performed without taking into account the feelings of job seekers, resulting in low dialogue quality and information reliability. This has made it difficult for both job seekers and companies to carry out efficient recruitment and job search activities.

[0884] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring a job seeker's resume, generation AI means for comparing the job information with the resume and optimizing the job information, means for providing the generated job information to the job seeker, means including an emotion engine for analyzing the job seeker's emotions, analysis means for identifying missing information in the resume, conversational AI means for hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to collect and optimize information while taking the job seeker's emotions into consideration, and achieves highly accurate matching between job seekers and companies.

[0885] "Means of obtaining job information" refers to a system that accesses a company's job database and obtains detailed information such as job content, required skills, work location, and salary.

[0886] "Means for obtaining job seekers' resumes" refers to a system for receiving and storing resume data uploaded by job seekers to the system from their own devices.

[0887] "Generative AI methods" refers to artificial intelligence technologies used to analyze job postings and resumes and optimize job postings based on job seekers' interests and aptitudes.

[0888] The "means for providing the generated job information to job seekers" is a mechanism for transmitting optimized job information to the job seekers' terminals so that the job seekers can view it.

[0889] "Means including an emotion engine" refers to technology for analyzing emotions in job seeker inputs and interactions and integrating the emotion information with other data.

[0890] The "analysis means for identifying missing information in a resume" is a method by which the server analyzes an uploaded resume and identifies missing information.

[0891] "Conversational AI means for gathering missing information from job seekers" is a conversational artificial intelligence technology that asks interactive questions based on identified missing information and gathers information from job seekers.

[0892] A "resume correction method" is a system for updating and completing a resume based on the collected information.

[0893] The "means of providing the company with the revised resume" is a mechanism for storing the revised resume in the company's database and notifying the company.

[0894] The above are definitions of the important terms included in the claims of the present invention.

[0895] The present invention is a system that effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system improves the reliability of collected information and enhances the dialogue quality of conversational AI. The following describes in detail the embodiments of the present invention.

[0896] Overall overview

[0897] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[0898] Acquiring and storing job information

[0899] The server connects to the company's job database to retrieve the latest job listings and store them in the database. For example, it sends an API request to retrieve the job listings, parses the data received in JSON format, and stores it in the database. This database contains details such as job description, required skills, location, salary, etc.

[0900] Acquiring and storing job seekers' resumes

[0901] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes, determines the path to store them on the file server, and then saves the file path and other related information in the database. This operation saves information such as the job seeker's work experience, educational background, skills, and qualifications.

[0902] Job Optimization with Generative AI

[0903] The server initializes a generative AI model and analyzes job postings and resumes. Typically, OpenAI's GPT-3 is used. Based on the analysis results, the generative AI reconstructs the job postings in a format that is optimal for the job seeker. This generated job posting is then sent from the server to the job seeker's device, where it can be viewed by the job seeker.

[0904] Prompt Sentence Examples

[0905] Here are some example prompts to input to a generative AI model:

[0906] Analyze the job postings and job seekers' resumes below and optimize your job postings based on the job seekers' interests and aptitudes.

[0907] Job information:

[0908] 1. Job Description: Digital Marketing Specialist

[0909] 2. Required skills: SEO, SEM, Google Analytics

[0910] 3. Work location: Tokyo

[0911] 4. Salary: 300,000 to 400,000 yen per month

[0912] Job Seeker's Resume:

[0913] 1. Work experience: SNS management, content marketing

[0914] 2. Education: Graduated from the Faculty of Economics at XXXX University

[0915] 3. Skills: Social media management, content creation

[0916] Emotion recognition by emotion engine

[0917] An emotion engine is installed on the job seeker's device and analyzes the emotion expressed when the job seeker types or interacts with the system. For example, it uses technologies such as facial expression recognition and voice tone analysis. This emotion information is sent to a server and integrated with other data. The emotion engine analyzes the job seeker's emotional state and evaluates the reliability of the information provided.

[0918] Identifying and interviewing missing information on resumes

[0919] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI asks interactive questions to the job seeker to collect information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions.

[0920] Specific examples

[0921] When a job seeker uploads a resume, the server analyzes it and identifies missing information, such as "digital marketing experience." The emotion engine analyzes the job seeker's stress level and determines that they are relaxed. Based on this, the conversational AI asks, "Tell me about your experience with Google Analytics." If the job seeker replies, "I've been using it for three years," this information is added to the resume.

[0922] Providing optimized resumes to companies

[0923] The server saves the revised resume in a database and sends a notification to the company's terminal. The company receives the notification and can contact the job seeker, for example, by email or phone.

[0924] This series of processes will enable highly accurate matching between job seekers and companies, which is expected to make job-seeking and recruitment activities more effective and efficient.

[0925] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0926] Step 1: Retrieve and save job information

[0927] The server accesses the company's job database to retrieve the latest job listings, sends an API request, and parses the data received in JSON format. This parsed data includes the job description, required skills, location, salary, etc. The server then stores this data in a database.

[0928] Input: Job information from the company's job database (JSON format)

[0929] Data processing: Analyze JSON format data and extract necessary fields

[0930] Output: Job listings stored in a database

[0931] Specific behavior:

[0932] Creating and Sending API Requests

[0933] Parsing received JSON data

[0934] Extract required fields and generate SQL statements

[0935] Executes an insert statement into the database

[0936] Step 2: Capture and store job seeker resumes

[0937] A job seeker uploads his / her resume to the system from his / her own device. The server receives the uploaded file and determines the path to store it on the file server. Then the server stores the file path and other related information in the database.

[0938] Input: Resume file uploaded by job seeker

[0939] Data processing: receiving files and determining the save path

[0940] Output: File paths and related information stored in the database

[0941] Specific behavior:

[0942] Display the upload form

[0943] Uploading a file

[0944] The server receives the file and generates a save path.

[0945] Stores file paths and related information in a database

[0946] Step 3: Optimizing job listings with generative AI

[0947] The server initializes the generative AI model and analyzes the job posting and resume. It generates a prompt and sends it to the generative AI. This generative AI then optimizes and reconstructs the job posting based on the input data. The optimized job posting is then sent to the job seeker's device.

[0948] Input: Job posting and job seeker resume

[0949] Data processing: Prompt generation and input to the AI ​​model

[0950] Output: Optimized job listings

[0951] Specific behavior:

[0952] Generate prompt statement

[0953] Sending prompts to the generation AI

[0954] Parsing output from generative AI models

[0955] Sending optimized job information to job seekers' devices

[0956] Step 4: Emotion Recognition with the Emotion Engine

[0957] The emotion engine analyzes the emotions expressed by job seekers when they input or interact with the system, and sends the results to the server. The input data is the job seeker's facial expressions and tone of voice, which are analyzed and output as emotional information. The server then integrates this emotional information with other data.

[0958] Input: Job seeker's facial expressions and tone of voice

[0959] Data processing: Sentiment analysis

[0960] Output: Parsed emotion data

[0961] Specific behavior:

[0962] Capture facial and voice data

[0963] Analysis by emotion engine

[0964] Generating emotion data and sending it to the server

[0965] Step 5: Identify missing information on your resume and ask questions

[0966] The server analyzes the uploaded resume and identifies missing information. The conversational AI interactively asks questions based on the missing information and collects information. The emotion engine adjusts the content and timing of the questions based on the emotional information obtained.

[0967] Input: Uploaded resume

[0968] Data processing: Resume analysis and identification of missing information

[0969] Output: A list of missing information and any additional information collected.

[0970] Specific behavior:

[0971] Resume analysis

[0972] Identifying missing information

[0973] Conversational AI generates and sends questions

[0974] Collect job seeker responses and update resumes

[0975] Step 6: Submit your optimized resume to employers

[0976] The server saves the revised resume in a database and notifies the company's terminal, allowing the company to view the revised resume and contact the job seeker.

[0977] Input: Revised resume

[0978] Data processing: storing in database and notifying companies

[0979] Output: Company confirmation of revised resume

[0980] Specific behavior:

[0981] Save the revised resume to the database

[0982] Notifications to corporate devices

[0983] Allowing companies to view your revised resume and establish contact

[0984] (Application example 2)

[0985] 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."

[0986] Current job and job seeker information matching systems have limitations in optimizing and complementing information, making it difficult to accurately match job seekers and companies. It is also difficult to understand customer needs in real time and recommend optimal products in physical stores. Therefore, it is necessary to achieve more efficient and effective matching and product recommendations.

[0987] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for identifying missing information in resumes, conversational AI means for hearing the missing information from job seekers, means for correcting resumes based on the acquired information, means for providing the corrected resumes to companies, means for acquiring product information, emotion analysis means for recognizing customer emotions, recommendation engine means for recommending products based on emotions, and interactive AI means for interacting with customers. This enables highly accurate matching of job information with job seeker resumes, and also realizes product recommendations based on customer needs in physical stores.

[0988] The "means for obtaining job information" refers to a device or program that allows the server to obtain detailed information such as job content, required skills, work location, and salary offered by companies.

[0989] The "means for obtaining a job seeker's resume" refers to a device or program that allows a job seeker to upload a resume containing information about their work experience, educational background, skills, qualifications, etc. to a server.

[0990] A "generative AI means" is a device or program that uses artificial intelligence to compare job postings with resumes and optimize the job postings based on the job seeker's interests and aptitudes.

[0991] "Means for providing job seekers with generated job information" refers to a device or program for transmitting job information optimized by the generating AI means to job seekers and making it viewable.

[0992] The "analysis means for identifying missing information in a resume" is a device or program for analyzing a resume and identifying missing information.

[0993] A "conversational AI means for gathering missing information from job seekers" is a device or program that uses artificial intelligence to interactively ask job seekers questions based on the missing information and gather information.

[0994] "Means for amending a resume based on acquired information" refers to a device or program for amending or supplementing the contents of a resume based on information acquired by a conversational AI means.

[0995] "Means for providing revised resumes to employers" refers to a device or program that notifies employers of revised or supplemented resumes and makes them available for viewing.

[0996] The "means for acquiring product information" refers to a device or program that allows the server to acquire information about products available in-store or online.

[0997] The "emotion analysis means for recognizing customer emotions" is a device or program for analyzing video data from a camera in smart glasses or a head-mounted display and recognizing the emotional state of a customer.

[0998] The "recommendation engine means for recommending products based on emotions" is a device or program for recommending products that a customer is interested in based on the results of emotion analysis.

[0999] "Interactive AI means for interacting with customers" refers to a device or program that uses artificial intelligence to interactively respond to customer questions in real time.

[1000] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Furthermore, by combining this system with an emotion engine that recognizes user emotions, the accuracy of product recommendations in physical stores can also be improved. The following describes in detail the embodiments of the present invention.

[1001] Overall system configuration

[1002] The system consists of a server, job seekers' devices, company devices, and customers' hardware in physical stores (smart glasses, head-mounted displays, etc.). The server optimizes and complements information using the following main means:

[1003] Acquiring and storing job information

[1004] The server connects to the company's job database, retrieves the latest job listings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[1005] Acquiring and storing job seekers' resumes

[1006] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[1007] Job Optimization with Generative AI

[1008] The server initializes the generation AI and analyzes the job postings and resumes. Based on the analysis results, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[1009] Emotion recognition by emotion engine

[1010] The emotion engine is installed on the devices (smart glasses, head-mounted displays, etc.) of job seekers and customers in brick-and-mortar stores. It analyzes emotions from facial expressions and other data via the device's camera and sends this emotional information to a server. The emotion analysis data is used to optimize job search and shopping experiences.

[1011] Specific examples

[1012] For example, consider the case where Job Seeker A uploads his / her resume to the system. The server analyzes the resume and identifies missing information, such as "experience in digital marketing." The emotion engine analyzes Job Seeker A's stress level and finds that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A replies, "I've been using it for three years," this information is added to his / her resume.

[1013] Acquisition and provision of product information in physical stores

[1014] The server connects to the store's product database, retrieves the latest product information, inventory information, and sale information, and stores it in the database. When a customer wearing smart glasses or a head-mounted display looks at products in the store, the camera analyzes the customer's line of sight and sends the information to the server.

[1015] Emotion-based product recommendations

[1016] The emotion engine analyzes customer facial expression data to identify products they are interested in. Generative AI uses that information to recommend related products. This process improves customer satisfaction because customers are presented with product suggestions based on their interests.

[1017] Prompt Sentence Examples

[1018] "When a customer points a product at the camera, use an emotion engine to analyze whether they are interested in that product, and if they are, generate a program that displays recommendations for related products."

[1019] The above is a specific embodiment of the present invention. By using this system, effective and efficient matching and recommendations can be achieved in both recruitment and job-seeking activities, as well as in the in-store shopping experience.

[1020] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1021] Step 1:

[1022] Acquiring and saving job information: Connect to the company's job database and acquire the latest job information. The server automatically acquires job information (job description, required skills, work location, salary, etc.) and saves it in the database. The input is the company's job database, and the output is the job information saved in the server's database.

[1023] Step 2:

[1024] Acquiring and storing job seeker resumes: Job seekers upload their resumes to the system using their own devices. The server receives the resumes and stores them in a database in a parsable format. The input is the job seeker's resume, and the output is the resume stored in the server's database.

[1025] Step 3:

[1026] Optimization of job postings using generation AI: The server initializes the generation AI, which compares and analyzes job postings and resumes. Based on the analysis results, the generation AI optimizes job postings to match the interests and aptitudes of job seekers and generates customized job postings. The input is the job posting and resume, and the output is the optimized job postings.

[1027] Step 4:

[1028] Providing optimized job information: The server sends the job information optimized by the generation AI to the job seeker's device, where it can be viewed by the job seeker. The input is the optimized job information, and the output is customized job information displayed on the job seeker's device.

[1029] Step 5:

[1030] Identifying missing information in a resume: The server analyzes the job seeker's resume and identifies the missing information. The input is the job seeker's resume, and the output is a list of missing information.

[1031] Step 6:

[1032] Hearing for missing information: Conversational AI interactively asks questions to job seekers based on the identified missing information to collect information. An emotion engine analyzes the job seeker's emotional state and adjusts the content and timing of the questions. The input is a list of missing information and the job seeker's response, and the output is the collected additional information.

[1033] Step 7:

[1034] Resume Modification: The server modifies the job seeker's resume based on the additional information collected. The input is the additional information collected, and the output is the modified resume.

[1035] Step 8:

[1036] Providing the revised resume to the company: The server saves the revised resume in the database and notifies the relevant company. The company can check the revised resume and contact the job seeker. The input is the revised resume, and the output is the revised resume notified to the company.

[1037] Step 9:

[1038] Obtaining product information: The server connects to the product database of the physical store, obtains the latest product information, stock information, and sale information, and stores it in the database. The input is the product database of the physical store, and the output is the product information stored in the server's database.

[1039] Step 10:

[1040] Customer emotion analysis: Customer facial expression data is collected through the camera in smart glasses or head-mounted displays and analyzed using an emotion engine. The input is the customer facial expression data, and the output is the customer emotion analysis results.

[1041] Step 11:

[1042] Emotion-based product recommendation: Based on the results of emotion analysis, the generative AI recommends related products. The recommendation engine selects the most suitable products from the product database and proposes them to the customer. The input is the result of the customer's emotion analysis, and the output is recommended product information.

[1043] Step 12:

[1044] Interacting with customers: Conversational AI responds interactively to customer questions and feedback, providing product information and related information. The input is the customer's question, and the output is the response from the conversational AI.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] [Third embodiment]

[1049] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1050] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1051] 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).

[1052] 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.

[1053] 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.

[1054] 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).

[1055] 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.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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."

[1061] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[1062] Overall overview

[1063] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[1064] Acquiring and storing job information

[1065] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1066] Acquiring and storing job seekers' resumes

[1067] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1068] Job Optimization with Generative AI

[1069] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[1070] Identifying and interviewing missing information on resumes

[1071] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1072] Specific examples

[1073] When job seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "experience in digital marketing." When the conversational AI asks job seeker A, "Tell us about your digital marketing skills," job seeker A responds, "I have three years of experience using Google Analytics." The server then corrects the resume based on the information obtained.

[1074] Providing optimized resumes to companies

[1075] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1076] System Overview

[1077] This system processes the following steps in a single sequence: acquiring job information, acquiring job seeker resumes, optimizing the job information using generation AI, gathering missing information using conversational AI, and providing the optimized resumes to companies. This can significantly improve the accuracy of matching job seekers and companies.

[1078] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1079] The processing flow will be explained below.

[1080] Step 1: Get job information

[1081] The server establishes a connection to the company's job database.

[1082] The server runs a query to get the latest job listings.

[1083] The acquired job information is saved in the server database.

[1084] Step 2: Obtaining job seeker resumes

[1085] The user uploads a resume file to the system from their own device.

[1086] The server receives the resume file and stores it in a database.

[1087] Step 3: Initializing the generated AI

[1088] The server loads and initializes the generative AI model.

[1089] The server begins parsing the job listings and resumes.

[1090] Step 4: Optimize your job listing

[1091] The server uses generated AI to compare job postings with resume content.

[1092] AI generates and edits job information that best suits the interests and aptitudes of job seekers.

[1093] The server sends the optimized job information to the job seeker's device.

[1094] Step 5: Identify missing information on your resume

[1095] The server analyzes the content of the received resume.

[1096] The server identifies the missing information based on the analysis results.

[1097] Step 6: Initializing the conversational AI

[1098] The server loads and initializes the conversational AI.

[1099] The server uses conversational AI to set questions to obtain missing information.

[1100] Step 7: Hearing

[1101] The user initiates a dialogue with the conversational AI.

[1102] Conversational AI asks users questions about missing information.

[1103] Users provide answers, and the conversational AI collects that information and, if necessary, obtains recommendations from stakeholders.

[1104] Step 8: Edit your resume

[1105] The server automatically updates the resume based on the new information obtained.

[1106] The modified resume is saved in the database.

[1107] Step 9: Notify the company

[1108] The server sends the modified resume to the company's database.

[1109] Companies will receive notifications to review the optimized resume and contact the job seeker.

[1110] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[1111] Example 1

[1112] 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."

[1113] The current recruitment system has a low accuracy in matching job seekers with companies, and the job information that job seekers apply for often does not match their own skills or experience. It is also difficult to efficiently collect information missing from job seekers' resumes, resulting in ineffective job searches. Companies also face the problem of not being able to hire the right people because they make hiring decisions based on incomplete resumes.

[1114] 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.

[1115] In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for analyzing uploaded resumes and identifying missing information, conversational AI means for hearing from job seekers about the missing information, means for correcting resumes based on the acquired missing information, and means for notifying and providing the corrected resumes to companies. This effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and enabling more efficient job and recruitment activities.

[1116] The "means for acquiring job information" is a function that enables the server to acquire information about job offers, such as job content, required skills, work location, and salary, provided by companies.

[1117] The "means for obtaining a job seeker's resume" is a function that enables the server to receive a job seeker's resume that lists their work experience, educational background, skills, qualifications, etc.

[1118] "Generative AI means" refers to an artificial intelligence function that analyzes job postings and job seekers' resumes and edits job postings to match the interests and aptitudes of job seekers in order to optimize job postings.

[1119] The "means for providing generated job information to job seekers" is a function for transmitting optimized job information to the job seeker's terminal so that the job seeker can view it.

[1120] "Analysis means" is a function for analyzing the uploaded resume of a job seeker and identifying missing information.

[1121] "Conversational AI tools" are artificial intelligence functions that interactively collect identified missing information from job seekers.

[1122] The "means for correcting a resume based on the acquired missing information" is a function for correcting a resume using the missing information collected from a job seeker.

[1123] The "means of notifying and providing the revised resume to the company" is a function for saving the revised resume in a database and notifying the company so that the resume can be checked.

[1124] MODE FOR CARRYING OUT THE INVENTION

[1125] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[1126] Overall overview

[1127] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[1128] Acquiring and storing job information

[1129] The server retrieves job information from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1130] Specific examples

[1131] When a company submits a new job posting to the server, the server analyzes the data and stores the information in a database. For example, if a company submits a job posting for a "software engineer," the server analyzes the job description and required skills and stores them in a database.

[1132] Acquiring and storing job seekers' resumes

[1133] Job seekers upload their resumes from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1134] Specific examples

[1135] When a job seeker uploads a resume, the server analyzes the data and stores it in a database. For example, if a job seeker uploads a resume for a "project manager," the server analyzes the job experience and qualifications held and stores them in a database.

[1136] Job Optimization with Generative AI

[1137] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[1138] Specific examples

[1139] The generative AI analyzes job postings for "data scientist" and optimizes them based on the job seeker's resume. For example, if a job seeker has skills in "Python" and "machine learning," the generative AI will optimize and provide job postings that utilize these skills.

[1140] Example prompt sentence:

[1141] "Analyze job postings and optimize them based on job seekers' resumes."

[1142] Identifying and interviewing missing information on resumes

[1143] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1144] Specific examples

[1145] If a job seeker uploads a resume for a "software tester," the server identifies the missing information: "Test automation experience is not listed." The conversational AI then asks the job seeker, "Tell me about your test automation experience," and the job seeker replies, "I have two years of experience in automated testing using TestNG." The server then corrects the resume based on the information obtained.

[1146] Example prompt sentence:

[1147] "Identify missing information on a job seeker's resume and collect that information."

[1148] Providing optimized resumes to companies

[1149] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1150] Specific examples

[1151] The server stores the optimized resume in a database and sends a notification to the company, which can then view the resume on the system and contact the job seeker.

[1152] Example prompt sentence:

[1153] "Please let companies know about your optimized resume so they can review it."

[1154] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1156] Processing Steps

[1157] Step 1: Get job information

[1158] input:

[1159] Job information such as job description, required skills, work location, salary, etc. sent from the company's device.

[1160] Specific behavior:

[1161] Server: The server receives job information sent as an HTTP POST request from the company's device.

[1162] Data processing / calculation:

[1163] The server parses the received job information in JSON format and extracts the necessary fields (job description, skills, location, salary, etc.).

[1164] output:

[1165] Extracted job posting data.

[1166] Step 2: Save your job posting

[1167] input:

[1168] Job posting data extracted in step 1.

[1169] Specific behavior:

[1170] Server: The server converts the job data into the appropriate database format and stores it in the database using SQL queries.

[1171] Data processing / calculation:

[1172] The server converts the JSON data into an SQL INSERT statement.

[1173] output:

[1174] Job information stored in a database.

[1175] Step 3: Upload your resume

[1176] input:

[1177] Resume file (PDF or text format) sent from the job seeker's device.

[1178] Specific behavior:

[1179] Terminal (job seeker): Job seeker uploads resume file.

[1180] Data processing / calculation:

[1181] The file is sent to the server via an HTTP POST request.

[1182] output:

[1183] Resume file received by server.

[1184] Step 4: Save your resume

[1185] input:

[1186] Resume file received in Step 3.

[1187] Specific behavior:

[1188] Server: The server parses the received resume file, extracts the text, and stores it in a database.

[1189] Data processing / calculation:

[1190] Use OCR and text analysis tools to extract text from your resume and break it down into the necessary fields.

[1191] output:

[1192] Resume information stored in a database.

[1193] Step 5: Optimizing job listings with generative AI

[1194] input:

[1195] Job information data, resume information data.

[1196] Specific behavior:

[1197] Server: The server initializes the generative AI model and provides job postings and resume information to the model.

[1198] Data processing / calculation:

[1199] Generative AI analyzes input data and optimizes job listings based on the skills and aptitudes of job seekers.

[1200] output:

[1201] Optimized job listings.

[1202] An example of hardware is using a GPU server (e.g., NVIDIA GPU).

[1203] Step 6: Optimized job postings

[1204] input:

[1205] The optimized job listing generated in step 5.

[1206] Specific behavior:

[1207] Server: The server sends the optimized job information to the job seeker's device as an HTTP response.

[1208] Data processing / calculation:

[1209] Convert job information into HTML or JSON format and send it.

[1210] output:

[1211] Optimized job listings displayed on job seekers' devices.

[1212] Step 7: Identify missing information on your resume

[1213] input:

[1214] Saved resume information.

[1215] Specific behavior:

[1216] Server: The server analyzes the stored resume information and identifies any missing information.

[1217] Data processing / calculation:

[1218] Use NLP tools to analyze the text of the resume and extract missing information.

[1219] output:

[1220] A list of missing information.

[1221] Step 8: Start the hearing

[1222] input:

[1223] List of missing information, job seeker's terminal.

[1224] Specific behavior:

[1225] Server: The server initializes the conversational AI and sends questions to the job seeker to interactively gather missing information.

[1226] Data processing / calculation:

[1227] Use a conversational AI model (e.g., Dialogflow) to generate interview questions and collect answers from job seekers.

[1228] output:

[1229] Missing information collected.

[1230] Step 9: Edit your resume

[1231] input:

[1232] Missing information collected, existing resume information.

[1233] Specific behavior:

[1234] Server: The server corrects the resume based on the missing information obtained and updates the database.

[1235] Data processing / calculation:

[1236] The retrieved information is added to the appropriate fields in the resume and the database is updated using a SQL UPDATE statement.

[1237] output:

[1238] Revised resume information.

[1239] Step 10: Submit your resume to the company

[1240] input:

[1241] Revised resume information.

[1242] Specific behavior:

[1243] Server: The server stores the modified resume in a database and sends a notification to the company.

[1244] Data processing / calculation:

[1245] Format the revised resume and notify the company via a notification system (e.g. email, HTTP request).

[1246] output:

[1247] Revised resume notified to company.

[1248] These are the specific processing steps of the system, which effectively compare and optimize job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and making job searches and recruitment more efficient.

[1249] (Application example 1)

[1250] 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."

[1251] Conventional recruitment systems have a low matching accuracy between job information provided by companies and resumes submitted by job seekers, and companies often do not clearly state the specific skills and experience they are looking for in job seekers. Mismatches also often occur because job seekers are unable to effectively promote their own skills and experience. Furthermore, in certain industries, such as virtual store operators, effective matching is difficult because job information is not optimized and insufficient information on resumes is not fully supplemented. A system that can solve these issues and improve the matching accuracy between companies and job seekers is needed.

[1252] 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.

[1253] In this invention, the server includes means for acquiring job information, means for acquiring resumes of job seekers, generation AI means for comparing the job information with the resumes and optimizing the job information, means for providing the optimized job information to the smart device, analysis means for identifying missing information in the resume, conversational AI means for interactively hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to efficiently optimize job information and complete resumes, significantly improving the accuracy of matching between companies and job seekers.

[1254] "Job information" is information about a specific job, such as the job description, required skills, work location, and salary, that a company provides to job seekers.

[1255] A resume is a document in which a job seeker lists detailed information about their work experience, educational background, skills, qualifications, etc.

[1256] "Generative AI" is a technological means of analyzing and optimizing job postings and resumes using artificial intelligence techniques.

[1257] A "smart device" is a mobile terminal that has computer functions and can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1258] "Analysis means" refers to technical means for analyzing the contents of a resume and identifying missing information.

[1259] "Conversational AI" is an artificial intelligence technology that uses natural language processing technology to converse with job seekers and collect missing information.

[1260] "Hearing" is the process in which conversational AI engages in an interactive dialogue with job seekers to collect necessary information.

[1261] This invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. This system consists of a server, job seeker terminals, and company terminals.

[1262] Overall overview

[1263] The server retrieves job postings and job seekers' resumes, optimizes the job postings using generative AI, and uses conversational AI to collect missing information from job seekers and correct their resumes.

[1264] Acquiring and storing job information

[1265] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1266] Acquiring and storing job seekers' resumes

[1267] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1268] Job Optimization with Generative AI

[1269] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The optimized job information is provided to the smart device so that the job seeker can view it.

[1270] Specific examples

[1271] Below are some example prompts that can be provided to a generative AI model:

[1272] Optimize your job listing:

[1273] Job Description: Sales Staff

[1274] Required skills: Customer service skills, communication skills

[1275] Location: Tokyo

[1276] Salary: From 1,200 yen per hour

[1277] Identifying and interviewing missing information on resumes

[1278] The server analyzes the uploaded resume and identifies missing information, including details of specific skills and experience, and then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1279] Specific examples

[1280] Below are some examples of prompts provided by conversational AI:

[1281] Please provide the missing information from your resume:

[1282] Work experience: Retail sales experience

[1283] Education: High school graduate

[1284] Tell us about your digital marketing skills

[1285] If a job seeker answers, "I have three years of experience using Google Analytics," the server will use this information to modify the resume.

[1286] Providing optimized resumes to companies

[1287] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1288] Hardware and Software Used

[1289] Hardware: Smartphones, smart glasses, head-mounted displays

[1290] Software: Python, OpenAI GPT-3, Cloud server

[1291] Data processing and calculation

[1292] The server uses a generative AI model (e.g., GPT-3) to optimize job information and create prompts. It also uses conversational AI to interact with job seekers and collect missing information, improving the accuracy of matching between companies and job seekers.

[1293] By using the above means, the present invention can efficiently optimize job information and complement resumes, significantly improving the accuracy of matching between companies and job seekers.

[1294] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1295] Processing step flow

[1296] Step 1:

[1297] The server retrieves job information from companies. Companies enter job information using their terminals and send detailed information such as job content, required skills, work location, and salary to the server. The server stores this information in a database.

[1298] Input: Job information provided by the company

[1299] Output: Job listings stored in a database

[1300] Specific operation: A company employee enters job information into a terminal and sends it to the server, which receives it and stores it in a database.

[1301] Step 2:

[1302] Job seekers upload their resumes from their own devices, and the server receives the uploaded resumes and stores them in a database.

[1303] Input: Resume uploaded by job seeker

[1304] Output: Resume saved in database

[1305] Specific operation: A job seeker uploads his / her resume to the system using a terminal. The server receives the resume and stores it in the database.

[1306] Step 3:

[1307] The server initializes the generation AI and analyzes the job postings and resumes. The generation AI optimizes the job postings based on the analysis results.

[1308] Input: Job listings and resumes stored in a database

[1309] Output: Optimized job listings

[1310] How it works: The server initializes a generative AI model (e.g., GPT-3) and inputs the job posting and resume as prompts. The generative AI analyzes this and generates an optimized job posting.

[1311] Step 4:

[1312] The server provides optimized job information to smart devices, which job seekers can view.

[1313] Input: Optimized Job Postings

[1314] Output: Optimized job listings displayed on job seekers' smart devices

[1315] Specific operation: The server sends the optimized job information to the job seeker's smart device, where the job seeker can view it.

[1316] Step 5:

[1317] The server analyzes resumes to identify missing information, and uses conversational AI to interactively gather missing information from job seekers to identify specific skills and experience details.

[1318] Input: Saved Resume

[1319] Output: Identified missing information

[1320] Specific operation: The server initializes the conversational AI, analyzes the resume content to identify missing information, generates prompts to ask questions to the job seeker, and the job seeker answers.

[1321] Step 6:

[1322] Based on the missing information collected from the job seeker, the server amends the resume and stores it in a database.

[1323] Input: Collected information

[1324] Output: Revised resume

[1325] Specific operation: The server receives the missing information, corrects the resume, and saves the corrected resume in the database.

[1326] Step 7:

[1327] The server provides the revised resume to the company, which can review it and contact the job seeker.

[1328] Input: Revised resume

[1329] Output: The revised resume delivered to the company's terminal

[1330] Specific operation: The server retrieves the revised resume from the database and sends it to the company's terminal, where the company's personnel can review it.

[1331] Summary

[1332] This series of processing steps efficiently optimizes job information and complements resumes, significantly improving the accuracy of matching between companies and job seekers.

[1333] 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.

[1334] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. It also includes a mechanism for improving the reliability of collected information and the dialogue quality of conversational AI by combining it with an emotion engine that recognizes user emotions. The following describes in detail the embodiments of the present invention.

[1335] Overall overview

[1336] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[1337] Acquiring and storing job information

[1338] The server connects to the company's job database, retrieves the latest job postings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[1339] Acquiring and storing job seekers' resumes

[1340] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[1341] Job Optimization with Generative AI

[1342] The server initializes the generation AI and analyzes the job postings and resumes. Based on the results of this analysis, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[1343] Emotion recognition by emotion engine

[1344] An emotion engine is installed on the user's device and analyzes the emotions expressed when the job seeker types or interacts with the information. This emotion information is sent to the server and integrated with other data. The emotion engine analyzes emotions and evaluates the reliability of the information provided.

[1345] Identifying and interviewing missing information on resumes

[1346] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI interactively asks questions to the job seeker and collects information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions. If necessary, it also asks related parties of the job seeker for recommended information.

[1347] Specific examples

[1348] When Job Seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "Experience in digital marketing is not listed." The emotion engine analyzes Job Seeker A's stress level and determines that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A answers, "I've been using it for three years," this information is added to his / her resume.

[1349] Providing optimized resumes to companies

[1350] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1351] System Overview

[1352] This system processes the following steps in a series: acquiring job information, acquiring job seeker resumes, optimizing the job information using generative AI, recognizing emotions using an emotion engine, gathering missing information using conversational AI, and providing the optimized resumes to companies. This process achieves highly accurate matching between job seekers and companies.

[1353] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1354] The processing flow will be explained below.

[1355] Step 1: Get job information

[1356] The server establishes a connection to the company's job database.

[1357] The server runs a query to get the latest job listings.

[1358] The server saves the acquired job information in its database.

[1359] Step 2: Obtaining job seeker resumes

[1360] The user uploads a resume file to the system from their own device.

[1361] The server receives the resume file and stores it in a database.

[1362] Step 3: Initializing the generated AI

[1363] The server loads and initializes the generative AI model.

[1364] The server begins parsing the job listings and resumes.

[1365] Step 4: Optimize your job listing

[1366] The server uses generated AI to compare job postings with resume content.

[1367] Optimize job listings to match job seekers' interests and aptitudes.

[1368] The server sends the optimized job information to the job seeker's device.

[1369] Step 5: Initializing the Emotion Engine

[1370] The user's device activates the emotion engine.

[1371] The emotion engine analyzes the user's input and emotions during the conversation and sends them to the server.

[1372] Step 6: Identify missing information on your resume

[1373] The server analyzes the content of the received resume.

[1374] Based on the analysis results, the server identifies the missing information.

[1375] Step 7: Initializing the conversational AI

[1376] The server loads and initializes the conversational AI.

[1377] Sets the questions for the server to hear.

[1378] Step 8: Integrating hearing and sentiment analysis

[1379] The user initiates a dialogue with the conversational AI.

[1380] Conversational AI asks users questions about missing information.

[1381] The emotion engine analyzes the user's emotions in real time and sends the data to the server.

[1382] Conversational AI adjusts the content and timing of questions based on emotional data.

[1383] Step 9: Get Recommendations (Optional)

[1384] In addition to identifying missing information, the conversational AI will also ask the job seeker's associates for recommendations if necessary.

[1385] The server stores the obtained recommendation information.

[1386] Step 10: Edit your resume

[1387] The server automatically modifies the resume based on the new information and recommendations it obtains.

[1388] The modified resume is saved in the database.

[1389] Step 11: Notify the company

[1390] The server sends the modified resume to the company's database.

[1391] Companies will receive notifications to review the optimized resume and contact the job seeker.

[1392] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[1393] Example 2

[1394] 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."

[1395] Conventional systems for matching job information with job seekers' resumes have had problems with low matching accuracy between job seekers and companies due to insufficient optimization of job information and identification of missing information in resumes. Furthermore, interactive interviews and optimizations are performed without taking into account the feelings of job seekers, resulting in low dialogue quality and information reliability. This has made it difficult for both job seekers and companies to carry out efficient recruitment and job search activities.

[1396] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring a job seeker's resume, generation AI means for comparing the job information with the resume and optimizing the job information, means for providing the generated job information to the job seeker, means including an emotion engine for analyzing the job seeker's emotions, analysis means for identifying missing information in the resume, conversational AI means for hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to collect and optimize information while taking the job seeker's emotions into consideration, and achieves highly accurate matching between job seekers and companies.

[1397] "Means of obtaining job information" refers to a system that accesses a company's job database and obtains detailed information such as job content, required skills, work location, and salary.

[1398] "Means for obtaining job seekers' resumes" refers to a system for receiving and storing resume data uploaded by job seekers to the system from their own devices.

[1399] "Generative AI methods" refers to artificial intelligence technologies used to analyze job postings and resumes and optimize job postings based on job seekers' interests and aptitudes.

[1400] The "means for providing the generated job information to job seekers" is a mechanism for transmitting optimized job information to the job seekers' terminals so that the job seekers can view it.

[1401] "Means including an emotion engine" refers to technology for analyzing emotions in job seeker inputs and interactions and integrating the emotion information with other data.

[1402] The "analysis means for identifying missing information in a resume" is a method by which the server analyzes an uploaded resume and identifies missing information.

[1403] "Conversational AI means for gathering missing information from job seekers" is a conversational artificial intelligence technology that asks interactive questions based on identified missing information and gathers information from job seekers.

[1404] A "resume correction method" is a system for updating and completing a resume based on the collected information.

[1405] The "means of providing the company with the revised resume" is a mechanism for storing the revised resume in the company's database and notifying the company.

[1406] The above are definitions of the important terms included in the claims of the present invention.

[1407] The present invention is a system that effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system improves the reliability of collected information and enhances the dialogue quality of conversational AI. The following describes in detail the embodiments of the present invention.

[1408] Overall overview

[1409] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[1410] Acquiring and storing job information

[1411] The server connects to the company's job database to retrieve the latest job listings and store them in the database. For example, it sends an API request to retrieve the job listings, parses the data received in JSON format, and stores it in the database. This database contains details such as job description, required skills, location, salary, etc.

[1412] Acquiring and storing job seekers' resumes

[1413] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes, determines the path to store them on the file server, and then saves the file path and other related information in the database. This operation saves information such as the job seeker's work experience, educational background, skills, and qualifications.

[1414] Job Optimization with Generative AI

[1415] The server initializes a generative AI model and analyzes job postings and resumes. Typically, OpenAI's GPT-3 is used. Based on the analysis results, the generative AI reconstructs the job postings in a format that is optimal for the job seeker. This generated job posting is then sent from the server to the job seeker's device, where it can be viewed by the job seeker.

[1416] Prompt Sentence Examples

[1417] Here are some example prompts to input to a generative AI model:

[1418] Analyze the job postings and job seekers' resumes below and optimize your job postings based on the job seekers' interests and aptitudes.

[1419] Job information:

[1420] 1. Job Description: Digital Marketing Specialist

[1421] 2. Required skills: SEO, SEM, Google Analytics

[1422] 3. Work location: Tokyo

[1423] 4. Salary: 300,000 to 400,000 yen per month

[1424] Job Seeker's Resume:

[1425] 1. Work experience: SNS management, content marketing

[1426] 2. Education: Graduated from the Faculty of Economics at XXXX University

[1427] 3. Skills: Social media management, content creation

[1428] Emotion recognition by emotion engine

[1429] An emotion engine is installed on the job seeker's device and analyzes the emotion expressed when the job seeker types or interacts with the system. For example, it uses technologies such as facial expression recognition and voice tone analysis. This emotion information is sent to a server and integrated with other data. The emotion engine analyzes the job seeker's emotional state and evaluates the reliability of the information provided.

[1430] Identifying and interviewing missing information on resumes

[1431] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI asks interactive questions to the job seeker to collect information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions.

[1432] Specific examples

[1433] When a job seeker uploads a resume, the server analyzes it and identifies missing information, such as "digital marketing experience." The emotion engine analyzes the job seeker's stress level and determines that they are relaxed. Based on this, the conversational AI asks, "Tell me about your experience with Google Analytics." If the job seeker replies, "I've been using it for three years," this information is added to the resume.

[1434] Providing optimized resumes to companies

[1435] The server saves the revised resume in a database and sends a notification to the company's terminal. The company receives the notification and can contact the job seeker, for example, by email or phone.

[1436] This series of processes will enable highly accurate matching between job seekers and companies, which is expected to make job-seeking and recruitment activities more effective and efficient.

[1437] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1438] Step 1: Retrieve and save job information

[1439] The server accesses the company's job database to retrieve the latest job listings, sends an API request, and parses the data received in JSON format. This parsed data includes the job description, required skills, location, salary, etc. The server then stores this data in a database.

[1440] Input: Job information from the company's job database (JSON format)

[1441] Data processing: Analyze JSON format data and extract necessary fields

[1442] Output: Job listings stored in a database

[1443] Specific behavior:

[1444] Creating and Sending API Requests

[1445] Parsing received JSON data

[1446] Extract required fields and generate SQL statements

[1447] Executes an insert statement into the database

[1448] Step 2: Capture and store job seeker resumes

[1449] A job seeker uploads his / her resume to the system from his / her own device. The server receives the uploaded file and determines the path to store it on the file server. Then the server stores the file path and other related information in the database.

[1450] Input: Resume file uploaded by job seeker

[1451] Data processing: receiving files and determining the save path

[1452] Output: File paths and related information stored in the database

[1453] Specific behavior:

[1454] Display the upload form

[1455] Uploading a file

[1456] The server receives the file and generates a save path.

[1457] Stores file paths and related information in a database

[1458] Step 3: Optimizing job listings with generative AI

[1459] The server initializes the generative AI model and analyzes the job posting and resume. It generates a prompt and sends it to the generative AI. This generative AI then optimizes and reconstructs the job posting based on the input data. The optimized job posting is then sent to the job seeker's device.

[1460] Input: Job posting and job seeker resume

[1461] Data processing: Prompt generation and input to the AI ​​model

[1462] Output: Optimized job listings

[1463] Specific behavior:

[1464] Generate prompt statement

[1465] Sending prompts to the generation AI

[1466] Parsing output from generative AI models

[1467] Sending optimized job information to job seekers' devices

[1468] Step 4: Emotion Recognition with the Emotion Engine

[1469] The emotion engine analyzes the emotions expressed by job seekers when they input or interact with the system, and sends the results to the server. The input data is the job seeker's facial expressions and tone of voice, which are analyzed and output as emotional information. The server then integrates this emotional information with other data.

[1470] Input: Job seeker's facial expressions and tone of voice

[1471] Data processing: Sentiment analysis

[1472] Output: Parsed emotion data

[1473] Specific behavior:

[1474] Capture facial and voice data

[1475] Analysis by emotion engine

[1476] Generating emotion data and sending it to the server

[1477] Step 5: Identify missing information on your resume and ask questions

[1478] The server analyzes the uploaded resume and identifies missing information. The conversational AI interactively asks questions based on the missing information and collects information. The emotion engine adjusts the content and timing of the questions based on the emotional information obtained.

[1479] Input: Uploaded resume

[1480] Data processing: Resume analysis and identification of missing information

[1481] Output: A list of missing information and any additional information collected.

[1482] Specific behavior:

[1483] Resume analysis

[1484] Identifying missing information

[1485] Conversational AI generates and sends questions

[1486] Collect job seeker responses and update resumes

[1487] Step 6: Submit your optimized resume to employers

[1488] The server saves the revised resume in a database and notifies the company's terminal, allowing the company to view the revised resume and contact the job seeker.

[1489] Input: Revised resume

[1490] Data processing: storing in database and notifying companies

[1491] Output: Company confirmation of revised resume

[1492] Specific behavior:

[1493] Save the revised resume to the database

[1494] Notifications to corporate devices

[1495] Allowing companies to view your revised resume and establish contact

[1496] (Application example 2)

[1497] 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."

[1498] Current job and job seeker information matching systems have limitations in optimizing and complementing information, making it difficult to accurately match job seekers and companies. It is also difficult to understand customer needs in real time and recommend optimal products in physical stores. Therefore, it is necessary to achieve more efficient and effective matching and product recommendations.

[1499] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for identifying missing information in resumes, conversational AI means for hearing the missing information from job seekers, means for correcting resumes based on the acquired information, means for providing the corrected resumes to companies, means for acquiring product information, emotion analysis means for recognizing customer emotions, recommendation engine means for recommending products based on emotions, and interactive AI means for interacting with customers. This enables highly accurate matching of job information with job seeker resumes, and also realizes product recommendations based on customer needs in physical stores.

[1500] The "means for obtaining job information" refers to a device or program that allows the server to obtain detailed information such as job content, required skills, work location, and salary offered by companies.

[1501] The "means for obtaining a job seeker's resume" refers to a device or program that allows a job seeker to upload a resume containing information about their work experience, educational background, skills, qualifications, etc. to a server.

[1502] A "generative AI means" is a device or program that uses artificial intelligence to compare job postings with resumes and optimize the job postings based on the job seeker's interests and aptitudes.

[1503] "Means for providing job seekers with generated job information" refers to a device or program for transmitting job information optimized by the generating AI means to job seekers and making it viewable.

[1504] The "analysis means for identifying missing information in a resume" is a device or program for analyzing a resume and identifying missing information.

[1505] A "conversational AI means for gathering missing information from job seekers" is a device or program that uses artificial intelligence to interactively ask job seekers questions based on the missing information and gather information.

[1506] "Means for amending a resume based on acquired information" refers to a device or program for amending or supplementing the contents of a resume based on information acquired by a conversational AI means.

[1507] "Means for providing revised resumes to employers" refers to a device or program that notifies employers of revised or supplemented resumes and makes them available for viewing.

[1508] The "means for acquiring product information" refers to a device or program that allows the server to acquire information about products available in-store or online.

[1509] The "emotion analysis means for recognizing customer emotions" is a device or program for analyzing video data from a camera in smart glasses or a head-mounted display and recognizing the emotional state of a customer.

[1510] The "recommendation engine means for recommending products based on emotions" is a device or program for recommending products that a customer is interested in based on the results of emotion analysis.

[1511] "Interactive AI means for interacting with customers" refers to a device or program that uses artificial intelligence to interactively respond to customer questions in real time.

[1512] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Furthermore, by combining this system with an emotion engine that recognizes user emotions, the accuracy of product recommendations in physical stores can also be improved. The following describes in detail the embodiments of the present invention.

[1513] Overall system configuration

[1514] The system consists of a server, job seekers' devices, company devices, and customers' hardware in physical stores (smart glasses, head-mounted displays, etc.). The server optimizes and complements information using the following main means:

[1515] Acquiring and storing job information

[1516] The server connects to the company's job database, retrieves the latest job listings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[1517] Acquiring and storing job seekers' resumes

[1518] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[1519] Job Optimization with Generative AI

[1520] The server initializes the generation AI and analyzes the job postings and resumes. Based on the analysis results, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[1521] Emotion recognition by emotion engine

[1522] The emotion engine is installed on the devices (smart glasses, head-mounted displays, etc.) of job seekers and customers in brick-and-mortar stores. It analyzes emotions from facial expressions and other data via the device's camera and sends this emotional information to a server. The emotion analysis data is used to optimize job search and shopping experiences.

[1523] Specific examples

[1524] For example, consider the case where Job Seeker A uploads his / her resume to the system. The server analyzes the resume and identifies missing information, such as "experience in digital marketing." The emotion engine analyzes Job Seeker A's stress level and finds that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A replies, "I've been using it for three years," this information is added to his / her resume.

[1525] Acquisition and provision of product information in physical stores

[1526] The server connects to the store's product database, retrieves the latest product information, inventory information, and sale information, and stores it in the database. When a customer wearing smart glasses or a head-mounted display looks at products in the store, the camera analyzes the customer's line of sight and sends the information to the server.

[1527] Emotion-based product recommendations

[1528] The emotion engine analyzes customer facial expression data to identify products they are interested in. Generative AI uses that information to recommend related products. This process improves customer satisfaction because customers are presented with product suggestions based on their interests.

[1529] Prompt Sentence Examples

[1530] "When a customer points a product at the camera, use an emotion engine to analyze whether they are interested in that product, and if they are, generate a program that displays recommendations for related products."

[1531] The above is a specific embodiment of the present invention. By using this system, effective and efficient matching and recommendations can be achieved in both recruitment and job-seeking activities, as well as in the in-store shopping experience.

[1532] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1533] Step 1:

[1534] Acquiring and saving job information: Connect to the company's job database and acquire the latest job information. The server automatically acquires job information (job description, required skills, work location, salary, etc.) and saves it in the database. The input is the company's job database, and the output is the job information saved in the server's database.

[1535] Step 2:

[1536] Acquiring and storing job seeker resumes: Job seekers upload their resumes to the system using their own devices. The server receives the resumes and stores them in a database in a parsable format. The input is the job seeker's resume, and the output is the resume stored in the server's database.

[1537] Step 3:

[1538] Optimization of job postings using generation AI: The server initializes the generation AI, which compares and analyzes job postings and resumes. Based on the analysis results, the generation AI optimizes job postings to match the interests and aptitudes of job seekers and generates customized job postings. The input is the job posting and resume, and the output is the optimized job postings.

[1539] Step 4:

[1540] Providing optimized job information: The server sends the job information optimized by the generation AI to the job seeker's device, where it can be viewed by the job seeker. The input is the optimized job information, and the output is customized job information displayed on the job seeker's device.

[1541] Step 5:

[1542] Identifying missing information in a resume: The server analyzes the job seeker's resume and identifies the missing information. The input is the job seeker's resume, and the output is a list of missing information.

[1543] Step 6:

[1544] Hearing for missing information: Conversational AI interactively asks questions to job seekers based on the identified missing information to collect information. An emotion engine analyzes the job seeker's emotional state and adjusts the content and timing of the questions. The input is a list of missing information and the job seeker's response, and the output is the collected additional information.

[1545] Step 7:

[1546] Resume Modification: The server modifies the job seeker's resume based on the additional information collected. The input is the additional information collected, and the output is the modified resume.

[1547] Step 8:

[1548] Providing the revised resume to the company: The server saves the revised resume in the database and notifies the relevant company. The company can check the revised resume and contact the job seeker. The input is the revised resume, and the output is the revised resume notified to the company.

[1549] Step 9:

[1550] Obtaining product information: The server connects to the product database of the physical store, obtains the latest product information, stock information, and sale information, and stores it in the database. The input is the product database of the physical store, and the output is the product information stored in the server's database.

[1551] Step 10:

[1552] Customer emotion analysis: Customer facial expression data is collected through the camera in smart glasses or head-mounted displays and analyzed using an emotion engine. The input is the customer facial expression data, and the output is the customer emotion analysis results.

[1553] Step 11:

[1554] Emotion-based product recommendation: Based on the results of emotion analysis, the generative AI recommends related products. The recommendation engine selects the most suitable products from the product database and proposes them to the customer. The input is the result of the customer's emotion analysis, and the output is recommended product information.

[1555] Step 12:

[1556] Interacting with customers: Conversational AI responds interactively to customer questions and feedback, providing product information and related information. The input is the customer's question, and the output is the response from the conversational AI.

[1557] 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.

[1558] 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.

[1559] 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.

[1560] [Fourth embodiment]

[1561] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1562] 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.

[1563] 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).

[1564] 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.

[1565] 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.

[1566] 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).

[1567] 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.

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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."

[1574] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[1575] Overall overview

[1576] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[1577] Acquiring and storing job information

[1578] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1579] Acquiring and storing job seekers' resumes

[1580] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1581] Job Optimization with Generative AI

[1582] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[1583] Identifying and interviewing missing information on resumes

[1584] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1585] Specific examples

[1586] When job seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "experience in digital marketing." When the conversational AI asks job seeker A, "Tell us about your digital marketing skills," job seeker A responds, "I have three years of experience using Google Analytics." The server then corrects the resume based on the information obtained.

[1587] Providing optimized resumes to companies

[1588] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1589] System Overview

[1590] This system processes the following steps in a single sequence: acquiring job information, acquiring job seeker resumes, optimizing the job information using generation AI, gathering missing information using conversational AI, and providing the optimized resumes to companies. This can significantly improve the accuracy of matching job seekers and companies.

[1591] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1592] The processing flow will be explained below.

[1593] Step 1: Get job information

[1594] The server establishes a connection to the company's job database.

[1595] The server runs a query to get the latest job listings.

[1596] The acquired job information is saved in the server database.

[1597] Step 2: Obtaining job seeker resumes

[1598] The user uploads a resume file to the system from their own device.

[1599] The server receives the resume file and stores it in a database.

[1600] Step 3: Initializing the generated AI

[1601] The server loads and initializes the generative AI model.

[1602] The server begins parsing the job listings and resumes.

[1603] Step 4: Optimize your job listing

[1604] The server uses generated AI to compare job postings with resume content.

[1605] AI generates and edits job information that best suits the interests and aptitudes of job seekers.

[1606] The server sends the optimized job information to the job seeker's device.

[1607] Step 5: Identify missing information on your resume

[1608] The server analyzes the content of the received resume.

[1609] The server identifies the missing information based on the analysis results.

[1610] Step 6: Initializing the conversational AI

[1611] The server loads and initializes the conversational AI.

[1612] The server uses conversational AI to set questions to obtain missing information.

[1613] Step 7: Hearing

[1614] The user initiates a dialogue with the conversational AI.

[1615] Conversational AI asks users questions about missing information.

[1616] Users provide answers, and the conversational AI collects that information and, if necessary, obtains recommendations from stakeholders.

[1617] Step 8: Edit your resume

[1618] The server automatically updates the resume based on the new information obtained.

[1619] The modified resume is saved in the database.

[1620] Step 9: Notify the company

[1621] The server sends the modified resume to the company's database.

[1622] Companies will receive notifications to review the optimized resume and contact the job seeker.

[1623] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[1624] Example 1

[1625] 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."

[1626] The current recruitment system has a low accuracy in matching job seekers with companies, and the job information that job seekers apply for often does not match their own skills or experience. It is also difficult to efficiently collect information missing from job seekers' resumes, resulting in ineffective job searches. Companies also face the problem of not being able to hire the right people because they make hiring decisions based on incomplete resumes.

[1627] 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.

[1628] In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for analyzing uploaded resumes and identifying missing information, conversational AI means for hearing from job seekers about the missing information, means for correcting resumes based on the acquired missing information, and means for notifying and providing the corrected resumes to companies. This effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and enabling more efficient job and recruitment activities.

[1629] The "means for acquiring job information" is a function that enables the server to acquire information about job offers, such as job content, required skills, work location, and salary, provided by companies.

[1630] The "means for obtaining a job seeker's resume" is a function that enables the server to receive a job seeker's resume that lists their work experience, educational background, skills, qualifications, etc.

[1631] "Generative AI means" refers to an artificial intelligence function that analyzes job postings and job seekers' resumes and edits job postings to match the interests and aptitudes of job seekers in order to optimize job postings.

[1632] The "means for providing generated job information to job seekers" is a function for transmitting optimized job information to the job seeker's terminal so that the job seeker can view it.

[1633] "Analysis means" is a function for analyzing the uploaded resume of a job seeker and identifying missing information.

[1634] "Conversational AI tools" are artificial intelligence functions that interactively collect identified missing information from job seekers.

[1635] The "means for correcting a resume based on the acquired missing information" is a function for correcting a resume using the missing information collected from a job seeker.

[1636] The "means of notifying and providing the revised resume to the company" is a function for saving the revised resume in a database and notifying the company so that the resume can be checked.

[1637] MODE FOR CARRYING OUT THE INVENTION

[1638] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Hereinafter, an embodiment of the present invention will be described in detail.

[1639] Overall overview

[1640] The system consists of a server, job seekers' devices, and companies' devices. The server obtains job information and job seekers' resumes and optimizes the job information using generative AI. The server also uses conversational AI to collect missing information from job seekers and correct their resumes.

[1641] Acquiring and storing job information

[1642] The server retrieves job information from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1643] Specific examples

[1644] When a company submits a new job posting to the server, the server analyzes the data and stores the information in a database. For example, if a company submits a job posting for a "software engineer," the server analyzes the job description and required skills and stores them in a database.

[1645] Acquiring and storing job seekers' resumes

[1646] Job seekers upload their resumes from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1647] Specific examples

[1648] When a job seeker uploads a resume, the server analyzes the data and stores it in a database. For example, if a job seeker uploads a resume for a "project manager," the server analyzes the job experience and qualifications held and stores them in a database.

[1649] Job Optimization with Generative AI

[1650] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The server then sends the optimized job information to the job seeker's device, where it can be viewed by the job seeker.

[1651] Specific examples

[1652] The generative AI analyzes job postings for "data scientist" and optimizes them based on the job seeker's resume. For example, if a job seeker has skills in "Python" and "machine learning," the generative AI will optimize and provide job postings that utilize these skills.

[1653] Example prompt sentence:

[1654] "Analyze job postings and optimize them based on job seekers' resumes."

[1655] Identifying and interviewing missing information on resumes

[1656] The server analyzes the uploaded resume and identifies missing information, including specific skills, experience details, recommendations, etc. The server then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1657] Specific examples

[1658] If a job seeker uploads a resume for a "software tester," the server identifies the missing information: "Test automation experience is not listed." The conversational AI then asks the job seeker, "Tell me about your test automation experience," and the job seeker replies, "I have two years of experience in automated testing using TestNG." The server then corrects the resume based on the information obtained.

[1659] Example prompt sentence:

[1660] "Identify missing information on a job seeker's resume and collect that information."

[1661] Providing optimized resumes to companies

[1662] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1663] Specific examples

[1664] The server stores the optimized resume in a database and sends a notification to the company, which can then view the resume on the system and contact the job seeker.

[1665] Example prompt sentence:

[1666] "Please let companies know about your optimized resume so they can review it."

[1667] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1668] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1669] Processing Steps

[1670] Step 1: Get job information

[1671] input:

[1672] Job information such as job description, required skills, work location, salary, etc. sent from the company's device.

[1673] Specific behavior:

[1674] Server: The server receives job information sent as an HTTP POST request from the company's device.

[1675] Data processing / calculation:

[1676] The server parses the received job information in JSON format and extracts the necessary fields (job description, skills, location, salary, etc.).

[1677] output:

[1678] Extracted job posting data.

[1679] Step 2: Save your job posting

[1680] input:

[1681] Job posting data extracted in step 1.

[1682] Specific behavior:

[1683] Server: The server converts the job data into the appropriate database format and stores it in the database using SQL queries.

[1684] Data processing / calculation:

[1685] The server converts the JSON data into an SQL INSERT statement.

[1686] output:

[1687] Job information stored in a database.

[1688] Step 3: Upload your resume

[1689] input:

[1690] Resume file (PDF or text format) sent from the job seeker's device.

[1691] Specific behavior:

[1692] Terminal (job seeker): Job seeker uploads resume file.

[1693] Data processing / calculation:

[1694] The file is sent to the server via an HTTP POST request.

[1695] output:

[1696] Resume file received by server.

[1697] Step 4: Save your resume

[1698] input:

[1699] Resume file received in Step 3.

[1700] Specific behavior:

[1701] Server: The server parses the received resume file, extracts the text, and stores it in a database.

[1702] Data processing / calculation:

[1703] Use OCR and text analysis tools to extract text from your resume and break it down into the necessary fields.

[1704] output:

[1705] Resume information stored in a database.

[1706] Step 5: Optimizing job listings with generative AI

[1707] input:

[1708] Job information data, resume information data.

[1709] Specific behavior:

[1710] Server: The server initializes the generative AI model and provides job postings and resume information to the model.

[1711] Data processing / calculation:

[1712] Generative AI analyzes input data and optimizes job listings based on the skills and aptitudes of job seekers.

[1713] output:

[1714] Optimized job listings.

[1715] An example of hardware is using a GPU server (e.g., NVIDIA GPU).

[1716] Step 6: Optimized job postings

[1717] input:

[1718] The optimized job listing generated in step 5.

[1719] Specific behavior:

[1720] Server: The server sends the optimized job information to the job seeker's device as an HTTP response.

[1721] Data processing / calculation:

[1722] Convert job information into HTML or JSON format and send it.

[1723] output:

[1724] Optimized job listings displayed on job seekers' devices.

[1725] Step 7: Identify missing information on your resume

[1726] input:

[1727] Saved resume information.

[1728] Specific behavior:

[1729] Server: The server analyzes the stored resume information and identifies any missing information.

[1730] Data processing / calculation:

[1731] Use NLP tools to analyze the text of the resume and extract missing information.

[1732] output:

[1733] A list of missing information.

[1734] Step 8: Start the hearing

[1735] input:

[1736] List of missing information, job seeker's terminal.

[1737] Specific behavior:

[1738] Server: The server initializes the conversational AI and sends questions to the job seeker to interactively gather missing information.

[1739] Data processing / calculation:

[1740] Use a conversational AI model (e.g., Dialogflow) to generate interview questions and collect answers from job seekers.

[1741] output:

[1742] Missing information collected.

[1743] Step 9: Edit your resume

[1744] input:

[1745] Missing information collected, existing resume information.

[1746] Specific behavior:

[1747] Server: The server corrects the resume based on the missing information obtained and updates the database.

[1748] Data processing / calculation:

[1749] The retrieved information is added to the appropriate fields in the resume and the database is updated using a SQL UPDATE statement.

[1750] output:

[1751] Revised resume information.

[1752] Step 10: Submit your resume to the company

[1753] input:

[1754] Revised resume information.

[1755] Specific behavior:

[1756] Server: The server stores the modified resume in a database and sends a notification to the company.

[1757] Data processing / calculation:

[1758] Format the revised resume and notify the company via a notification system (e.g. email, HTTP request).

[1759] output:

[1760] Revised resume notified to company.

[1761] These are the specific processing steps of the system, which effectively compare and optimize job information and job seeker resumes, improving the accuracy of matching between job seekers and companies and making job searches and recruitment more efficient.

[1762] (Application example 1)

[1763] 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."

[1764] Conventional recruitment systems have a low matching accuracy between job information provided by companies and resumes submitted by job seekers, and companies often do not clearly state the specific skills and experience they are looking for in job seekers. Mismatches also often occur because job seekers are unable to effectively promote their own skills and experience. Furthermore, in certain industries, such as virtual store operators, effective matching is difficult because job information is not optimized and insufficient information on resumes is not fully supplemented. A system that can solve these issues and improve the matching accuracy between companies and job seekers is needed.

[1765] 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.

[1766] In this invention, the server includes means for acquiring job information, means for acquiring resumes of job seekers, generation AI means for comparing the job information with the resumes and optimizing the job information, means for providing the optimized job information to the smart device, analysis means for identifying missing information in the resume, conversational AI means for interactively hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to efficiently optimize job information and complete resumes, significantly improving the accuracy of matching between companies and job seekers.

[1767] "Job information" is information about a specific job, such as the job description, required skills, work location, and salary, that a company provides to job seekers.

[1768] A resume is a document in which a job seeker lists detailed information about their work experience, educational background, skills, qualifications, etc.

[1769] "Generative AI" is a technological means of analyzing and optimizing job postings and resumes using artificial intelligence techniques.

[1770] A "smart device" is a mobile terminal that has computer functions and can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1771] "Analysis means" refers to technical means for analyzing the contents of a resume and identifying missing information.

[1772] "Conversational AI" is an artificial intelligence technology that uses natural language processing technology to converse with job seekers and collect missing information.

[1773] "Hearing" is the process in which conversational AI engages in an interactive dialogue with job seekers to collect necessary information.

[1774] This invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. This system consists of a server, job seeker terminals, and company terminals.

[1775] Overall overview

[1776] The server retrieves job postings and job seekers' resumes, optimizes the job postings using generative AI, and uses conversational AI to collect missing information from job seekers and correct their resumes.

[1777] Acquiring and storing job information

[1778] The server retrieves job information directly from companies and stores it in a database. Job information includes details such as job description, required skills, work location, salary, etc. The server periodically synchronizes with the company database to retrieve new job information and update old information.

[1779] Acquiring and storing job seekers' resumes

[1780] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain details of the job seeker's work experience, educational background, skills, qualifications, etc.

[1781] Job Optimization with Generative AI

[1782] The server initializes the generation AI and analyzes the acquired job information and job seeker resumes. Based on the analysis results, the generation AI optimizes the job information to match the job seeker's interests and aptitudes. The optimized job information is provided to the smart device so that the job seeker can view it.

[1783] Specific examples

[1784] Below are some example prompts that can be provided to a generative AI model:

[1785] Optimize your job listing:

[1786] Job Description: Sales Staff

[1787] Required skills: Customer service skills, communication skills

[1788] Location: Tokyo

[1789] Salary: From 1,200 yen per hour

[1790] Identifying and interviewing missing information on resumes

[1791] The server analyzes the uploaded resume and identifies missing information, including details of specific skills and experience, and then initializes a conversational AI that allows the job seeker to interactively provide the missing information.

[1792] Specific examples

[1793] Below are some examples of prompts provided by conversational AI:

[1794] Please provide the missing information from your resume:

[1795] Work experience: Retail sales experience

[1796] Education: High school graduate

[1797] Tell us about your digital marketing skills

[1798] If a job seeker answers, "I have three years of experience using Google Analytics," the server will use this information to modify the resume.

[1799] Providing optimized resumes to companies

[1800] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1801] Hardware and Software Used

[1802] Hardware: Smartphones, smart glasses, head-mounted displays

[1803] Software: Python, OpenAI GPT-3, Cloud server

[1804] Data processing and calculation

[1805] The server uses a generative AI model (e.g., GPT-3) to optimize job information and create prompts. It also uses conversational AI to interact with job seekers and collect missing information, improving the accuracy of matching between companies and job seekers.

[1806] By using the above means, the present invention can efficiently optimize job information and complement resumes, significantly improving the accuracy of matching between companies and job seekers.

[1807] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1808] Processing step flow

[1809] Step 1:

[1810] The server retrieves job information from companies. Companies enter job information using their terminals and send detailed information such as job content, required skills, work location, and salary to the server. The server stores this information in a database.

[1811] Input: Job information provided by the company

[1812] Output: Job listings stored in a database

[1813] Specific operation: A company employee enters job information into a terminal and sends it to the server, which receives it and stores it in a database.

[1814] Step 2:

[1815] Job seekers upload their resumes from their own devices, and the server receives the uploaded resumes and stores them in a database.

[1816] Input: Resume uploaded by job seeker

[1817] Output: Resume saved in database

[1818] Specific operation: A job seeker uploads his / her resume to the system using a terminal. The server receives the resume and stores it in the database.

[1819] Step 3:

[1820] The server initializes the generation AI and analyzes the job postings and resumes. The generation AI optimizes the job postings based on the analysis results.

[1821] Input: Job listings and resumes stored in a database

[1822] Output: Optimized job listings

[1823] How it works: The server initializes a generative AI model (e.g., GPT-3) and inputs the job posting and resume as prompts. The generative AI analyzes this and generates an optimized job posting.

[1824] Step 4:

[1825] The server provides optimized job information to smart devices, which job seekers can view.

[1826] Input: Optimized Job Postings

[1827] Output: Optimized job listings displayed on job seekers' smart devices

[1828] Specific operation: The server sends the optimized job information to the job seeker's smart device, where the job seeker can view it.

[1829] Step 5:

[1830] The server analyzes resumes to identify missing information, and uses conversational AI to interactively gather missing information from job seekers to identify specific skills and experience details.

[1831] Input: Saved Resume

[1832] Output: Identified missing information

[1833] Specific operation: The server initializes the conversational AI, analyzes the resume content to identify missing information, generates prompts to ask questions to the job seeker, and the job seeker answers.

[1834] Step 6:

[1835] Based on the missing information collected from the job seeker, the server amends the resume and stores it in a database.

[1836] Input: Collected information

[1837] Output: Revised resume

[1838] Specific operation: The server receives the missing information, corrects the resume, and saves the corrected resume in the database.

[1839] Step 7:

[1840] The server provides the revised resume to the company, which can review it and contact the job seeker.

[1841] Input: Revised resume

[1842] Output: The revised resume delivered to the company's terminal

[1843] Specific operation: The server retrieves the revised resume from the database and sends it to the company's terminal, where the company's personnel can review it.

[1844] Summary

[1845] This series of processing steps efficiently optimizes job information and complements resumes, significantly improving the accuracy of matching between companies and job seekers.

[1846] 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.

[1847] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. It also includes a mechanism for improving the reliability of collected information and the dialogue quality of conversational AI by combining it with an emotion engine that recognizes user emotions. The following describes in detail the embodiments of the present invention.

[1848] Overall overview

[1849] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[1850] Acquiring and storing job information

[1851] The server connects to the company's job database, retrieves the latest job postings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[1852] Acquiring and storing job seekers' resumes

[1853] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[1854] Job Optimization with Generative AI

[1855] The server initializes the generation AI and analyzes the job postings and resumes. Based on the results of this analysis, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[1856] Emotion recognition by emotion engine

[1857] An emotion engine is installed on the user's device and analyzes the emotions expressed when the job seeker types or interacts with the information. This emotion information is sent to the server and integrated with other data. The emotion engine analyzes emotions and evaluates the reliability of the information provided.

[1858] Identifying and interviewing missing information on resumes

[1859] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI interactively asks questions to the job seeker and collects information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions. If necessary, it also asks related parties of the job seeker for recommended information.

[1860] Specific examples

[1861] When Job Seeker A uploads his / her resume to the system, the server analyzes the resume and identifies missing information: "Experience in digital marketing is not listed." The emotion engine analyzes Job Seeker A's stress level and determines that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A answers, "I've been using it for three years," this information is added to his / her resume.

[1862] Providing optimized resumes to companies

[1863] The server saves the modified resume in a database and notifies the company, which can then review the optimized resume and contact the job seeker.

[1864] System Overview

[1865] This system processes the following steps in a series: acquiring job information, acquiring job seeker resumes, optimizing the job information using generative AI, recognizing emotions using an emotion engine, gathering missing information using conversational AI, and providing the optimized resumes to companies. This process achieves highly accurate matching between job seekers and companies.

[1866] The above is a specific embodiment for carrying out the present invention. By using this system, effective and efficient matching can be achieved in both recruitment and job-seeking activities.

[1867] The processing flow will be explained below.

[1868] Step 1: Get job information

[1869] The server establishes a connection to the company's job database.

[1870] The server runs a query to get the latest job listings.

[1871] The server saves the acquired job information in its database.

[1872] Step 2: Obtaining job seeker resumes

[1873] The user uploads a resume file to the system from their own device.

[1874] The server receives the resume file and stores it in a database.

[1875] Step 3: Initializing the generated AI

[1876] The server loads and initializes the generative AI model.

[1877] The server begins parsing the job listings and resumes.

[1878] Step 4: Optimize your job listing

[1879] The server uses generated AI to compare job postings with resume content.

[1880] Optimize job listings to match job seekers' interests and aptitudes.

[1881] The server sends the optimized job information to the job seeker's device.

[1882] Step 5: Initializing the Emotion Engine

[1883] The user's device activates the emotion engine.

[1884] The emotion engine analyzes the user's input and emotions during the conversation and sends them to the server.

[1885] Step 6: Identify missing information on your resume

[1886] The server analyzes the content of the received resume.

[1887] Based on the analysis results, the server identifies the missing information.

[1888] Step 7: Initializing the conversational AI

[1889] The server loads and initializes the conversational AI.

[1890] Sets the questions for the server to hear.

[1891] Step 8: Integrating hearing and sentiment analysis

[1892] The user initiates a dialogue with the conversational AI.

[1893] Conversational AI asks users questions about missing information.

[1894] The emotion engine analyzes the user's emotions in real time and sends the data to the server.

[1895] Conversational AI adjusts the content and timing of questions based on emotional data.

[1896] Step 9: Get Recommendations (Optional)

[1897] In addition to identifying missing information, the conversational AI will also ask the job seeker's associates for recommendations if necessary.

[1898] The server stores the obtained recommendation information.

[1899] Step 10: Edit your resume

[1900] The server automatically modifies the resume based on the new information and recommendations it obtains.

[1901] The modified resume is saved in the database.

[1902] Step 11: Notify the company

[1903] The server sends the modified resume to the company's database.

[1904] Companies will receive notifications to review the optimized resume and contact the job seeker.

[1905] The above is the specific processing flow of the program according to the present invention. This process achieves highly accurate matching between job seekers and companies.

[1906] Example 2

[1907] 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."

[1908] Conventional systems for matching job information with job seekers' resumes have had problems with low matching accuracy between job seekers and companies due to insufficient optimization of job information and identification of missing information in resumes. Furthermore, interactive interviews and optimizations are performed without taking into account the feelings of job seekers, resulting in low dialogue quality and information reliability. This has made it difficult for both job seekers and companies to carry out efficient recruitment and job search activities.

[1909] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring a job seeker's resume, generation AI means for comparing the job information with the resume and optimizing the job information, means for providing the generated job information to the job seeker, means including an emotion engine for analyzing the job seeker's emotions, analysis means for identifying missing information in the resume, conversational AI means for hearing the missing information from the job seeker, means for correcting the resume based on the acquired information, and means for providing the corrected resume to companies. This makes it possible to collect and optimize information while taking the job seeker's emotions into consideration, and achieves highly accurate matching between job seekers and companies.

[1910] "Means of obtaining job information" refers to a system that accesses a company's job database and obtains detailed information such as job content, required skills, work location, and salary.

[1911] "Means for obtaining job seekers' resumes" refers to a system for receiving and storing resume data uploaded by job seekers to the system from their own devices.

[1912] "Generative AI methods" refers to artificial intelligence technologies used to analyze job postings and resumes and optimize job postings based on job seekers' interests and aptitudes.

[1913] The "means for providing the generated job information to job seekers" is a mechanism for transmitting optimized job information to the job seekers' terminals so that the job seekers can view it.

[1914] "Means including an emotion engine" refers to technology for analyzing emotions in job seeker inputs and interactions and integrating the emotion information with other data.

[1915] The "analysis means for identifying missing information in a resume" is a method by which the server analyzes an uploaded resume and identifies missing information.

[1916] "Conversational AI means for gathering missing information from job seekers" is a conversational artificial intelligence technology that asks interactive questions based on identified missing information and gathers information from job seekers.

[1917] A "resume correction method" is a system for updating and completing a resume based on the collected information.

[1918] The "means of providing the company with the revised resume" is a mechanism for storing the revised resume in the company's database and notifying the company.

[1919] The above are definitions of the important terms included in the claims of the present invention.

[1920] The present invention is a system that effectively compares and optimizes job information and job seeker resumes, improving the accuracy of matching between job seekers and companies. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system improves the reliability of collected information and enhances the dialogue quality of conversational AI. The following describes in detail the embodiments of the present invention.

[1921] Overall overview

[1922] The system consists of a server, job seekers' devices, and companies' devices. The server retrieves job information and job seekers' resumes, and optimizes and complements the information using generative AI, conversational AI, and an emotion engine. Finally, optimized job information and revised resumes are provided.

[1923] Acquiring and storing job information

[1924] The server connects to the company's job database to retrieve the latest job listings and store them in the database. For example, it sends an API request to retrieve the job listings, parses the data received in JSON format, and stores it in the database. This database contains details such as job description, required skills, location, salary, etc.

[1925] Acquiring and storing job seekers' resumes

[1926] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes, determines the path to store them on the file server, and then saves the file path and other related information in the database. This operation saves information such as the job seeker's work experience, educational background, skills, and qualifications.

[1927] Job Optimization with Generative AI

[1928] The server initializes a generative AI model and analyzes job postings and resumes. Typically, OpenAI's GPT-3 is used. Based on the analysis results, the generative AI reconstructs the job postings in a format that is optimal for the job seeker. This generated job posting is then sent from the server to the job seeker's device, where it can be viewed by the job seeker.

[1929] Prompt Sentence Examples

[1930] Here are some example prompts to input to a generative AI model:

[1931] Analyze the job postings and job seekers' resumes below and optimize your job postings based on the job seekers' interests and aptitudes.

[1932] Job information:

[1933] 1. Job Description: Digital Marketing Specialist

[1934] 2. Required skills: SEO, SEM, Google Analytics

[1935] 3. Work location: Tokyo

[1936] 4. Salary: 300,000 to 400,000 yen per month

[1937] Job Seeker's Resume:

[1938] 1. Work experience: SNS management, content marketing

[1939] 2. Education: Graduated from the Faculty of Economics at XXXX University

[1940] 3. Skills: Social media management, content creation

[1941] Emotion recognition by emotion engine

[1942] An emotion engine is installed on the job seeker's device and analyzes the emotion expressed when the job seeker types or interacts with the system. For example, it uses technologies such as facial expression recognition and voice tone analysis. This emotion information is sent to a server and integrated with other data. The emotion engine analyzes the job seeker's emotional state and evaluates the reliability of the information provided.

[1943] Identifying and interviewing missing information on resumes

[1944] The server analyzes the uploaded resume and identifies missing information. Based on the identified missing information, the conversational AI asks interactive questions to the job seeker to collect information. Based on the emotional information obtained by the emotion engine, the conversational AI adjusts the content and timing of the questions.

[1945] Specific examples

[1946] When a job seeker uploads a resume, the server analyzes it and identifies missing information, such as "digital marketing experience." The emotion engine analyzes the job seeker's stress level and determines that they are relaxed. Based on this, the conversational AI asks, "Tell me about your experience with Google Analytics." If the job seeker replies, "I've been using it for three years," this information is added to the resume.

[1947] Providing optimized resumes to companies

[1948] The server saves the revised resume in a database and sends a notification to the company's terminal. The company receives the notification and can contact the job seeker, for example, by email or phone.

[1949] This series of processes will enable highly accurate matching between job seekers and companies, which is expected to make job-seeking and recruitment activities more effective and efficient.

[1950] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1951] Step 1: Retrieve and save job information

[1952] The server accesses the company's job database to retrieve the latest job listings, sends an API request, and parses the data received in JSON format. This parsed data includes the job description, required skills, location, salary, etc. The server then stores this data in a database.

[1953] Input: Job information from the company's job database (JSON format)

[1954] Data processing: Analyze JSON format data and extract necessary fields

[1955] Output: Job listings stored in a database

[1956] Specific behavior:

[1957] Creating and Sending API Requests

[1958] Parsing received JSON data

[1959] Extract required fields and generate SQL statements

[1960] Executes an insert statement into the database

[1961] Step 2: Capture and store job seeker resumes

[1962] A job seeker uploads his / her resume to the system from his / her own device. The server receives the uploaded file and determines the path to store it on the file server. Then the server stores the file path and other related information in the database.

[1963] Input: Resume file uploaded by job seeker

[1964] Data processing: receiving files and determining the save path

[1965] Output: File paths and related information stored in the database

[1966] Specific behavior:

[1967] Display the upload form

[1968] Uploading a file

[1969] The server receives the file and generates a save path.

[1970] Stores file paths and related information in a database

[1971] Step 3: Optimizing job listings with generative AI

[1972] The server initializes the generative AI model and analyzes the job posting and resume. It generates a prompt and sends it to the generative AI. This generative AI then optimizes and reconstructs the job posting based on the input data. The optimized job posting is then sent to the job seeker's device.

[1973] Input: Job posting and job seeker resume

[1974] Data processing: Prompt generation and input to the AI ​​model

[1975] Output: Optimized job listings

[1976] Specific behavior:

[1977] Generate prompt statement

[1978] Sending prompts to the generation AI

[1979] Parsing output from generative AI models

[1980] Sending optimized job information to job seekers' devices

[1981] Step 4: Emotion Recognition with the Emotion Engine

[1982] The emotion engine analyzes the emotions expressed by job seekers when they input or interact with the system, and sends the results to the server. The input data is the job seeker's facial expressions and tone of voice, which are analyzed and output as emotional information. The server then integrates this emotional information with other data.

[1983] Input: Job seeker's facial expressions and tone of voice

[1984] Data processing: Sentiment analysis

[1985] Output: Parsed emotion data

[1986] Specific behavior:

[1987] Capture facial and voice data

[1988] Analysis by emotion engine

[1989] Generating emotion data and sending it to the server

[1990] Step 5: Identify missing information on your resume and ask questions

[1991] The server analyzes the uploaded resume and identifies missing information. The conversational AI interactively asks questions based on the missing information and collects information. The emotion engine adjusts the content and timing of the questions based on the emotional information obtained.

[1992] Input: Uploaded resume

[1993] Data processing: Resume analysis and identification of missing information

[1994] Output: A list of missing information and any additional information collected.

[1995] Specific behavior:

[1996] Resume analysis

[1997] Identifying missing information

[1998] Conversational AI generates and sends questions

[1999] Collect job seeker responses and update resumes

[2000] Step 6: Submit your optimized resume to employers

[2001] The server saves the revised resume in a database and notifies the company's terminal, allowing the company to view the revised resume and contact the job seeker.

[2002] Input: Revised resume

[2003] Data processing: storing in database and notifying companies

[2004] Output: Company confirmation of revised resume

[2005] Specific behavior:

[2006] Save the revised resume to the database

[2007] Notifications to corporate devices

[2008] Allowing companies to view your revised resume and establish contact

[2009] (Application example 2)

[2010] 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."

[2011] Current job and job seeker information matching systems have limitations in optimizing and complementing information, making it difficult to accurately match job seekers and companies. It is also difficult to understand customer needs in real time and recommend optimal products in physical stores. Therefore, it is necessary to achieve more efficient and effective matching and product recommendations.

[2012] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring job information, means for acquiring job seeker resumes, generation AI means for comparing job information with resumes and optimizing the job information, means for providing the generated job information to job seekers, analysis means for identifying missing information in resumes, conversational AI means for hearing the missing information from job seekers, means for correcting resumes based on the acquired information, means for providing the corrected resumes to companies, means for acquiring product information, emotion analysis means for recognizing customer emotions, recommendation engine means for recommending products based on emotions, and interactive AI means for interacting with customers. This enables highly accurate matching of job information with job seeker resumes, and also realizes product recommendations based on customer needs in physical stores.

[2013] The "means for obtaining job information" refers to a device or program that allows the server to obtain detailed information such as job content, required skills, work location, and salary offered by companies.

[2014] The "means for obtaining a job seeker's resume" refers to a device or program that allows a job seeker to upload a resume containing information about their work experience, educational background, skills, qualifications, etc. to a server.

[2015] A "generative AI means" is a device or program that uses artificial intelligence to compare job postings with resumes and optimize the job postings based on the job seeker's interests and aptitudes.

[2016] "Means for providing job seekers with generated job information" refers to a device or program for transmitting job information optimized by the generating AI means to job seekers and making it viewable.

[2017] The "analysis means for identifying missing information in a resume" is a device or program for analyzing a resume and identifying missing information.

[2018] A "conversational AI means for gathering missing information from job seekers" is a device or program that uses artificial intelligence to interactively ask job seekers questions based on the missing information and gather information.

[2019] "Means for amending a resume based on acquired information" refers to a device or program for amending or supplementing the contents of a resume based on information acquired by a conversational AI means.

[2020] "Means for providing revised resumes to employers" refers to a device or program that notifies employers of revised or supplemented resumes and makes them available for viewing.

[2021] The "means for acquiring product information" refers to a device or program that allows the server to acquire information about products available in-store or online.

[2022] The "emotion analysis means for recognizing customer emotions" is a device or program for analyzing video data from a camera in smart glasses or a head-mounted display and recognizing the emotional state of a customer.

[2023] The "recommendation engine means for recommending products based on emotions" is a device or program for recommending products that a customer is interested in based on the results of emotion analysis.

[2024] "Interactive AI means for interacting with customers" refers to a device or program that uses artificial intelligence to interactively respond to customer questions in real time.

[2025] The present invention relates to a system that effectively compares and optimizes job information and job seeker resumes to improve the accuracy of matching between job seekers and companies. Furthermore, by combining this system with an emotion engine that recognizes user emotions, the accuracy of product recommendations in physical stores can also be improved. The following describes in detail the embodiments of the present invention.

[2026] Overall system configuration

[2027] The system consists of a server, job seekers' devices, company devices, and customers' hardware in physical stores (smart glasses, head-mounted displays, etc.). The server optimizes and complements information using the following main means:

[2028] Acquiring and storing job information

[2029] The server connects to the company's job database, retrieves the latest job listings, and stores them in the database, including details such as the job description, required skills, location, and salary.

[2030] Acquiring and storing job seekers' resumes

[2031] Job seekers upload their resumes to the system from their own devices. The server receives the uploaded resumes and stores them in a database. The resumes contain information about the job seeker's work experience, educational background, skills, qualifications, etc.

[2032] Job Optimization with Generative AI

[2033] The server initializes the generation AI and analyzes the job postings and resumes. Based on the analysis results, the generation AI optimizes the job postings to match the job seeker's interests and aptitudes. The server then sends the optimized job postings to the job seeker's device, where they can be viewed.

[2034] Emotion recognition by emotion engine

[2035] The emotion engine is installed on the devices (smart glasses, head-mounted displays, etc.) of job seekers and customers in brick-and-mortar stores. It analyzes emotions from facial expressions and other data via the device's camera and sends this emotional information to a server. The emotion analysis data is used to optimize job search and shopping experiences.

[2036] Specific examples

[2037] For example, consider the case where Job Seeker A uploads his / her resume to the system. The server analyzes the resume and identifies missing information, such as "experience in digital marketing." The emotion engine analyzes Job Seeker A's stress level and finds that he / she is relaxed. Based on this, the conversational AI asks, "Tell me about your experience using Google Analytics." If Job Seeker A replies, "I've been using it for three years," this information is added to his / her resume.

[2038] Acquisition and provision of product information in physical stores

[2039] The server connects to the store's product database, retrieves the latest product information, inventory information, and sale information, and stores it in the database. When a customer wearing smart glasses or a head-mounted display looks at products in the store, the camera analyzes the customer's line of sight and sends the information to the server.

[2040] Emotion-based product recommendations

[2041] The emotion engine analyzes customer facial expression data to identify products they are interested in. Generative AI uses that information to recommend related products. This process improves customer satisfaction because customers are presented with product suggestions based on their interests.

[2042] Prompt Sentence Examples

[2043] "When a customer points a product at the camera, use an emotion engine to analyze whether they are interested in that product, and if they are, generate a program that displays recommendations for related products."

[2044] The above is a specific embodiment of the present invention. By using this system, effective and efficient matching and recommendations can be achieved in both recruitment and job-seeking activities, as well as in the in-store shopping experience.

[2045] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2046] Step 1:

[2047] Acquiring and saving job information: Connect to the company's job database and acquire the latest job information. The server automatically acquires job information (job description, required skills, work location, salary, etc.) and saves it in the database. The input is the company's job database, and the output is the job information saved in the server's database.

[2048] Step 2:

[2049] Acquiring and storing job seeker resumes: Job seekers upload their resumes to the system using their own devices. The server receives the resumes and stores them in a database in a parsable format. The input is the job seeker's resume, and the output is the resume stored in the server's database.

[2050] Step 3:

[2051] Optimization of job postings using generation AI: The server initializes the generation AI, which compares and analyzes job postings and resumes. Based on the analysis results, the generation AI optimizes job postings to match the interests and aptitudes of job seekers and generates customized job postings. The input is the job posting and resume, and the output is the optimized job postings.

[2052] Step 4:

[2053] Providing optimized job information: The server sends the job information optimized by the generation AI to the job seeker's device, where it can be viewed by the job seeker. The input is the optimized job information, and the output is customized job information displayed on the job seeker's device.

[2054] Step 5:

[2055] Identifying missing information in a resume: The server analyzes the job seeker's resume and identifies the missing information. The input is the job seeker's resume, and the output is a list of missing information.

[2056] Step 6:

[2057] Hearing for missing information: Conversational AI interactively asks questions to job seekers based on the identified missing information to collect information. An emotion engine analyzes the job seeker's emotional state and adjusts the content and timing of the questions. The input is a list of missing information and the job seeker's response, and the output is the collected additional information.

[2058] Step 7:

[2059] Resume Modification: The server modifies the job seeker's resume based on the additional information collected. The input is the additional information collected, and the output is the modified resume.

[2060] Step 8:

[2061] Providing the revised resume to the company: The server saves the revised resume in the database and notifies the relevant company. The company can check the revised resume and contact the job seeker. The input is the revised resume, and the output is the revised resume notified to the company.

[2062] Step 9:

[2063] Obtaining product information: The server connects to the product database of the physical store, obtains the latest product information, stock information, and sale information, and stores it in the database. The input is the product database of the physical store, and the output is the product information stored in the server's database.

[2064] Step 10:

[2065] Customer emotion analysis: Customer facial expression data is collected through the camera in smart glasses or head-mounted displays and analyzed using an emotion engine. The input is the customer facial expression data, and the output is the customer emotion analysis results.

[2066] Step 11:

[2067] Emotion-based product recommendation: Based on the results of emotion analysis, the generative AI recommends related products. The recommendation engine selects the most suitable products from the product database and proposes them to the customer. The input is the result of the customer's emotion analysis, and the output is recommended product information.

[2068] Step 12:

[2069] Interacting with customers: Conversational AI responds interactively to customer questions and feedback, providing product information and related information. The input is the customer's question, and the output is the response from the conversational AI.

[2070] 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.

[2071] 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.

[2072] 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.

[2073] 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.

[2074] 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.

[2075] 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.

[2076] 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).

[2077] 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.

[2078] 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."

[2079] 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.

[2080] 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).

[2081] 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.

[2082] 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.

[2083] 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.

[2084] 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.

[2085] 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.

[2086] 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.

[2087] 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.

[2088] 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.

[2089] 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.

[2090] 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.

[2091] The following is further disclosed regarding the above embodiment.

[2092] (Claim 1)

[2093] A means of obtaining job information;

[2094] A means of obtaining job seekers' resumes;

[2095] A generative AI method for comparing job postings with resumes and optimizing job postings;

[2096] A means for providing the generated job information to job seekers;

[2097] an analytical means for identifying missing information in the resume;

[2098] A conversational AI method to gather missing information from job seekers,

[2099] A means of amending your resume based on the information obtained;

[2100] A means to provide the employer with the revised resume;

[2101] A system including:

[2102] (Claim 2)

[2103] The system according to claim 1, characterized in that the conversational AI means has a function of hearing recommendation information from people related to the job seeker.

[2104] (Claim 3)

[2105] The system according to claim 1, characterized in that the generating AI means has a function of editing the job information to increase interest of job seekers based on the results of comparing the job information with the resume.

[2106] "Example 1"

[2107] (Claim 1)

[2108] A means of obtaining job information;

[2109] A means of obtaining job seekers' resumes;

[2110] A generative AI method for comparing job postings with resumes and optimizing job postings;

[2111] A means for providing the generated job information to job seekers;

[2112] an analytical means for analyzing the uploaded resume and identifying missing information;

[2113] A conversational AI method to gather missing information from job seekers,

[2114] A means to amend your resume based on the missing information obtained;

[2115] A means of notifying and providing the employer with the revised resume;

[2116] A system including:

[2117] (Claim 2)

[2118] The system according to claim 1, characterized in that the conversational AI means has a function of hearing recommendation information from people related to the job seeker.

[2119] (Claim 3)

[2120] The system according to claim 1, characterized in that the generating AI means has a function of editing the job information to increase interest of job seekers based on the results of comparing the job information with the resume.

[2121] "Application Example 1"

[2122] New Claims

[2123] (Claim 1)

[2124] A means of obtaining job information;

[2125] A means of obtaining job se...

Claims

1. A means of obtaining job information; A means of obtaining job seekers' resumes; A generative AI method for comparing job postings with resumes and optimizing job postings; A means for providing the generated job information to job seekers; an analytical means for identifying missing information in the resume; A conversational AI method to gather missing information from job seekers, A means of amending your resume based on the information obtained; A means to provide the employer with the revised resume; A system including:

2. 2. The system according to claim 1, wherein the conversational AI means has a function of hearing recommendation information from people related to the job seeker.

3. The system according to claim 1, characterized in that the generating AI means has a function of editing the job information to increase interest from job seekers based on the results of comparing the job information with the resume.

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