System

Abstract

A system is provided.SOLUTION: A system, comprising: means for local residents to input their own profile information and skill sets; means for companies to register recruiting information; means for comparing the profile information and the recruiting information of the companies using an artificial intelligence algorithm to generate matching candidates; means for notifying the local residents and the companies of the matching candidates; and means for performing trend prediction for improving skills of the local residents to generate a required skill list.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] The problem that this invention aims to solve is to create an environment that provides urban jobs remotely to people who wish to live in rural areas, thereby solving the lack of employment and job-changing opportunities in rural areas. It also aims to revitalize the labor market throughout Japan by solving the labor shortage problem faced by urban companies and supporting the securing of human resources who can flexibly respond to conditions. [Means for solving the problem]

[0005] The present invention solves the above problems by providing a system including the following means.

[0006] A system including a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates, a means for notifying local residents and companies of the matching candidates, and a means for predicting trends for improving the skills of local residents and generating a list of required skills allows people to achieve high productivity and a rich work-life balance while living in rural areas. Furthermore, by storing the information input by local residents and companies in a database and sending notifications via email or in-application notifications, real-time matching is possible.

[0007] "Profile information" refers to information that local residents register about themselves, including their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0008] A "skill set" is a collection of skills and abilities that a user possesses, and specifically refers to specialized knowledge and skills such as programming, design, marketing, and clerical work.

[0009] "Recruitment information" is information describing the details of jobs offered by companies, including job type, job content, required skill set, salary, work location, working style, etc.

[0010] "Artificial Intelligence Algorithm" means the program logic used to compare a user's profile information and company job postings to generate optimal match candidates.

[0011] "Matching candidates" are combinations generated by an artificial intelligence algorithm that are likely to match a user's skill set with a company's job requirements.

[0012] "Trend forecasting" is a function that predicts skills that are expected to be in demand in the future based on market demand and technological advances.

[0013] "Database" means an information management system for storing information entered by users and businesses.

[0014] "Email" means a form of digital message sent over the Internet and used as a means of notification and communication.

[0015] "In-app notifications" are notification messages that are displayed within applications used by users and companies, and are used to deliver matching results and important information from the system in real time. [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 is a system that allows local residents to work remotely from urban areas. The program processing of this system will be explained below in natural language.

[0038] Program processing description

[0039] New user registration

[0040] User

[0041] Visit the website or application and click the "Sign Up" button.

[0042] Enter your profile information, such as your name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0043] Terminal

[0044] Perform initial validation of the entered information (checking format and required fields) to confirm that it has been entered correctly.

[0045] Send the validated information to the server.

[0046] server

[0047] The received user profile information and desired conditions are stored in a database.

[0048] Registering company job information

[0049] company

[0050] Visit the website or application and click on the "Subscribe to a Job" button.

[0051] Enter the details of the job offer, such as the job type, job content, required skill set, salary, work location, and working style.

[0052] Terminal

[0053] Perform initial validation of entered information.

[0054] Send the validated information to the server.

[0055] server

[0056] The received company job information is saved in a database.

[0057] Matching Process

[0058] server

[0059] Periodically read user and company information from the database.

[0060] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[0061] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[0062] The matching results are temporarily stored in a database.

[0063] Matching notification

[0064] server

[0065] Prepare to notify users and companies of the matching results.

[0066] Notifications are sent via user and company registered email addresses and in-app notification systems.

[0067] Terminal

[0068] Users and businesses receive notifications and review the content of the notifications.

[0069] Next steps

[0070] User

[0071] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[0072] company

[0073] Check the user's profile information and, if interested, schedule an interview or skills test.

[0074] Skills improvement support

[0075] server

[0076] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[0077] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[0078] User

[0079] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[0080] Specific examples

[0081] User A (terminal) registers and enters "3 years of experience in web development, knowledge of JavaScript (registered trademark) and Python" as profile information.

[0082] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0083] The server stores the information of User A and Company B in a database and matches them using an artificial intelligence algorithm.

[0084] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0085] This system will enable rural residents to acquire skills needed in urban areas, while achieving high productivity and a good work-life balance, thereby helping to revitalize Japan as a whole.

[0086] The processing flow will be explained below.

[0087] Step 1:

[0088] A user visits a website or application and clicks the "Sign Up" button.

[0089] Step 2:

[0090] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[0091] Step 3:

[0092] The terminal performs initial validation of the information entered (checking the format and checking for required fields) to ensure that it has been entered correctly.

[0093] Step 4:

[0094] The terminal sends the information that the validation has been completed to the server.

[0095] Step 5:

[0096] The server stores the received user profile information and desired conditions in a database.

[0097] Step 6:

[0098] A company visits their website or application and clicks the "Register a Job" button.

[0099] Step 7:

[0100] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[0101] Step 8:

[0102] The terminal performs an initial validation of the entered information.

[0103] Step 9:

[0104] The terminal sends the information that the validation has been completed to the server.

[0105] Step 10:

[0106] The server stores the received company job information in a database.

[0107] Step 11:

[0108] The server periodically reads user and company information from the database.

[0109] Step 12:

[0110] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[0111] Step 13:

[0112] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[0113] Step 14:

[0114] The server temporarily stores the matching results in a database.

[0115] Step 15:

[0116] The server prepares to notify the user and the company of the matching results.

[0117] Step 16:

[0118] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[0119] Step 17:

[0120] The device receives a notification to the user and the company, and the notification content is confirmed.

[0121] Step 18:

[0122] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[0123] Step 19:

[0124] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0125] Step 20:

[0126] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[0127] Step 20:

[0128] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[0129] Step 21:

[0130] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[0131] Example 1

[0132] 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."

[0133] To make it easier for rural residents to access jobs in urban areas, it is necessary to bridge the information gap between rural and urban areas. The current recruitment system makes it difficult for rural residents to find suitable jobs, and for companies to efficiently recruit talented personnel from remote areas. Furthermore, there are no established methods for rural residents to properly learn and acquire the skills required in urban areas, resulting in a skills gap. A comprehensive system to resolve these issues is needed.

[0134] 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.

[0135] In this invention, the server includes: a means for rural residents to input their profile information and skill set; a means for companies to register job information; a means for initially validating the input information; a means for transmitting validated information to the server; a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates; a means for notifying the matching candidates to rural residents and companies; and a means for predicting trends for improving the skills of rural residents and generating a list of required skills. This makes it easier for rural residents to access jobs in urban areas and enables companies to efficiently recruit talented people from remote locations. Furthermore, since rural residents can appropriately learn and acquire skills required in urban areas, the skills gap can be eliminated.

[0136] "Rural residents" refers to individuals who reside in areas away from urban areas.

[0137] "Profile information" refers to personal information such as the user's name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0138] "Skill set" refers to the skills, knowledge, and specialized abilities possessed by a user.

[0139] "Company" refers to the legal entity that registers job information.

[0140] "Job information" refers to information such as the type of job offered by a company, specific job content, required skill set, salary, work location, and working style.

[0141] "Initial validation" refers to the process of verifying that the information entered is formally correct and that all required fields are filled in.

[0142] "Server" refers to a high performance computer system that processes and stores data.

[0143] "Artificial intelligence algorithm" refers to a calculation method that analyzes user profile information and company job information to generate optimal matching candidates.

[0144] "Matching candidates" refer to the combination that is evaluated as optimal after comparing user and company information.

[0145] "Notification" refers to the act of informing users and businesses of matching results and other important information.

[0146] "Trend forecasting" refers to the process of analyzing market demand and future trends and predicting future trends based on the results.

[0147] The "Skills Needed List" is a list of recommendations for rural residents to acquire skills that will be in demand in the future.

[0148] The present invention is a comprehensive system that enables rural residents to remotely access urban jobs and develop appropriate skills. The system is configured as follows.

[0149] System Configuration

[0150] The system includes multiple components that work together: a user device, a company device, and a server, which contains a database that stores relevant data and an artificial intelligence (AI) model that runs the matching algorithm.

[0151] Program processing overview

[0152] The main processing flow of the system will be specifically explained below.

[0153] New user registration

[0154] Users access the website or application using their own device and click the "New Registration" button. They then enter their profile information, such as their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0155] The terminal performs initial validation of the information entered by the user in real time, for example, checking that the email address is formatted correctly and that all required fields are filled in. If validation passes, the information is sent to the server.

[0156] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[0157] Registering company job information

[0158] Companies access the website or application using their own devices, click the "Register Job Information" button, and enter details of the job, such as job type, job description, required skill set, salary, work location, and working style.

[0159] The terminal performs an initial validation of the information entered by the company in real time, for example, ensuring that the salary range is appropriate and the required skill set is specifically described, and if validation passes, it sends this information to the server.

[0160] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[0161] Matching Process

[0162] The server periodically reads user and company information from the database. It uses a generative AI model to compare the user's profile information with the company's job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[0163] Matching notification

[0164] The server prepares to notify users and businesses of the matching results. Notifications are sent to the users' and businesses' registered email addresses or via the notification system within the application.

[0165] The terminal displays the notification received by the user and the company, who then checks the notification content and takes the next action.

[0166] Skills improvement support

[0167] The server analyzes the skills that are expected to be in demand in the future based on the user's profile information and market trend data, and uses a generative AI model to generate a list of recommendations for skill development, which are displayed on the user's dedicated dashboard.

[0168] Users can check the recommended skill list and learning resources to improve their skills, which will support their ability development.

[0169] Specific examples

[0170] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[0171] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0172] The server stores the information of User A and Company B in a database and performs matching using a generative AI model.

[0173] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0174] Prompt Sentence Examples

[0175] Below are some examples of prompts to input to the generative AI model.

[0176] "Please explain the user registration process for the remote work support system in natural language."

[0177] "Please explain in natural language the process a company goes through to register a job posting."

[0178] "Please explain in natural language the process of matching users and companies."

[0179] "Please explain in natural language the process of notifying matching results."

[0180] "Please explain in natural language the process of supporting skill development in a remote work support system."

[0181] The above is an embodiment of the present invention. This will make it easier for rural residents to access jobs in urban areas, and will enable companies to efficiently recruit talented people in remote areas. It will also enable rural residents to appropriately study and acquire the skills required in urban areas, thereby eliminating the skills gap.

[0182] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0183] New user registration

[0184] Step 1:

[0185] The user accesses the website or application using their own device and clicks the "New Registration" button. A profile entry screen appears, and the user enters their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0186] Input: User's personal information and preferences.

[0187] Output: Profile information entered into the terminal.

[0188] Step 2:

[0189] The terminal performs initial validation of the information entered by the user in real time, for example, ensuring that the email address is formatted correctly and that all required fields are filled in.

[0190] Input: The profile information entered in step 1.

[0191] Data processing: Check email address format and confirm required fields.

[0192] Output: Profile information that passes validation.

[0193] Step 3:

[0194] The terminal transmits the profile information that has passed validation to the server.

[0195] Input: Profile information that passes initial validation.

[0196] Output: The profile information sent to the server.

[0197] Step 4:

[0198] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[0199] Input: Profile information sent from the device.

[0200] Data processing: storing information in a database.

[0201] Output: Profile information stored in a database.

[0202] Registering company job information

[0203] Step 1:

[0204] Companies access the website or application using their own devices and click the "Register Job Information" button. A job information entry screen will appear, where companies can enter details such as job type, job content, required skill set, salary, work location, and working style.

[0205] Input: Job details (job type, job description, required skill set, salary, work location, working style, etc.).

[0206] Output: The job information entered into the terminal.

[0207] Step 2:

[0208] The terminal performs initial validation of the information entered by the company in real time, for example, to check the appropriateness of the salary and the specificity of the required skill set.

[0209] Input: The job information entered in step 1.

[0210] Data processing: Checking the validity of salaries and confirming the specificity of skill sets.

[0211] Output: A job that passes validation.

[0212] Step 3:

[0213] The terminal transmits the job information that has passed validation to the server.

[0214] Input: A job that passes initial validation.

[0215] Output: The job listing sent to the server.

[0216] Step 4:

[0217] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[0218] Input: Job posting submitted from device.

[0219] Data processing: storing information in a database.

[0220] Output: Job information stored in the database.

[0221] Matching Process

[0222] Step 1:

[0223] The server periodically reads user and company information from the database, a process that is performed automatically by a scheduled job.

[0224] Input: User and company information in the database.

[0225] Output: The imported user and company information.

[0226] Step 2:

[0227] The server uses a generative AI model to compare user profile information with company job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[0228] Input: User and company information imported in step 1.

[0229] Data processing: Analyzing information with a generative AI model and calculating matching scores.

[0230] Output: Match score and candidate matches.

[0231] Step 3:

[0232] The server generates the best matching candidates based on the obtained matching scores and stores them in a temporary database.

[0233] Input: Matching score and match candidates.

[0234] Data processing: storing information in a temporary database.

[0235] Output: Match candidates stored in a temporary database.

[0236] Matching notification

[0237] Step 1:

[0238] The server prepares the email addresses registered by the user and the company and the in-application notification system, generates notification content according to templates, and adds it to the queue for sending.

[0239] Input: Match candidates stored in a temporary database.

[0240] Data processing: Creating notification content and queuing it for sending.

[0241] Output: The notification content queued for sending.

[0242] Step 2:

[0243] The server sends notifications as they become ready, using an SMTP server for email notifications and calling the corresponding notification API for in-app notifications.

[0244] Input: The notification content that has been queued for sending.

[0245] Data processing: Sending notifications using an SMTP server or notification API.

[0246] Output: Notifications sent to users and businesses.

[0247] Step 3:

[0248] The device displays the notifications received by the user and the company, and the user and the company check the notification content and consider the next action.

[0249] Input: Notifications sent to users and businesses.

[0250] Output: The notification content that will be displayed on your device.

[0251] Next steps

[0252] Step 1:

[0253] Users can check the information of the matched companies, and if they are interested, they can apply for an interview with the company via the application's functions or email.

[0254] Input: Notification details and matched company information.

[0255] Output: Interview request submitted.

[0256] Step 2:

[0257] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0258] Input: Notification content and matched user information.

[0259] Output: Scheduling interviews and skills tests.

[0260] Skills improvement support

[0261] Step 1:

[0262] The server analyzes the skills that are likely to be in demand in the future based on user profile information and market trend data, using a generative AI model for this analysis.

[0263] Input: User profile information and market trend data.

[0264] Data processing: Analyzing skill demand with generative AI models.

[0265] Output: A list of skills that are expected to be in demand.

[0266] Step 2:

[0267] Based on the analysis results, the server generates a list of recommended skills for the user and displays it on the user's dashboard.

[0268] Input: A list of skills that are expected to be in demand.

[0269] Data processing: Generating a list of recommended skills for improvement.

[0270] Output: A list of recommended skills to be improved, displayed on the user's dashboard.

[0271] Step 3:

[0272] Users can review a list of recommended skills and learning resources to improve their skills, such as taking online courses or using designated study materials.

[0273] Input: A list of recommended skills displayed on the user's dashboard.

[0274] Output: Actions to improve skills (taking courses and using learning materials).

[0275] (Application example 1)

[0276] 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."

[0277] Sales activities for sales representatives and freelancers living in rural areas face the challenge of limited means of accessing corporate projects in urban areas and across the country, and limited means of efficiently managing those projects, which requires a great deal of effort and time. Matching with suitable projects is also difficult, and an efficient system is needed to enable sales representatives living in rural areas to smoothly conduct transactions with urban companies. Furthermore, there is a lack of appropriate information sources to help rural residents improve their skills.

[0278] 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.

[0279] In this invention, the server includes: a means for local residents to input their own profile information and skill set; a means for companies to register job information and project information; a means for using an artificial intelligence algorithm to compare the profile information with the company's job information and project information to generate matching candidates; a means for notifying local residents and companies of the matching candidates; a means for predicting trends for improving the skills of local residents and generating a list of necessary skills and learning resources; and a means for displaying the trend predictions and skill list on a dashboard. This allows local residents to efficiently access corporate projects and centrally manage the progress and compensation status of projects. It also provides appropriate information for skill improvement.

[0280] "Rural residents" refers to individuals who reside in rural areas and are physically separated from urban and other areas.

[0281] "Profile information" is a general term for information that indicates an individual's characteristics, such as name, address, skill set, years of experience, and work history.

[0282] A "skill set" refers to the collection of skills and knowledge that an individual possesses, and is a list of the abilities required to perform a specific job.

[0283] "Company" refers to a legal entity that provides products or services.

[0284] "Job information" is information published by a company about the requirements and conditions for jobs and positions that the company is seeking.

[0285] "Project Information" refers to the job description provided by a company, including detailed information about a specific project or job.

[0286] An "artificial intelligence algorithm" is a computational method for analyzing data and finding patterns and relationships, and uses machine learning and natural language processing to process information.

[0287] "Matching candidates" refer to proposals for highly compatible combinations based on information about the user and the company.

[0288] "Notification" means the act of communicating specific information to a designated recipient, whether via email or an in-application notification system.

[0289] "Trend forecasting" refers to the act of analyzing and predicting the skills and market trends that will be required from the present to the future.

[0290] A "skills list" is a list of skills required for a specific job or task.

[0291] "Learning resources" refers to educational materials such as textbooks and online courses that can be used to improve skills.

[0292] A "dashboard" refers to a visual interface that allows users to understand information at a glance.

[0293] "Progress management" refers to the act of managing and tracking the progress of a case or project.

[0294] "Remuneration status" refers to the act of managing the status of compensation paid for completed work or projects.

[0295] This invention is a system for supporting the sales activities of sales representatives and freelancers living in rural areas, specifically, allowing rural residents to access corporate projects in urban areas and across the country and efficiently check the progress management and compensation status of projects. An embodiment of this system is described below.

[0296] System program configuration

[0297] The system mainly consists of a server, user terminals, and enterprise terminals, and uses artificial intelligence algorithms (e.g., SciKit Learn), databases (e.g., PostgreSQL), and web servers (e.g., the Django framework) as necessary technical components.

[0298] Processing flow

[0299] 1. New user registration

[0300] The user enters their profile information and skill set.

[0301] Initial validation is performed on the terminal side and sent to the server.

[0302] The server stores the received information in a database and notifies the user that registration is complete.

[0303] 2. Registering company job information and project information

[0304] Companies enter detailed job and project information.

[0305] Initial validation is performed on the terminal side and sent to the server.

[0306] The server stores the received information in a database and notifies the company that registration is complete.

[0307] 3. Matching by AI algorithm

[0308] The server periodically reads user and company information from the database and performs a comparison.

[0309] An artificial intelligence algorithm is used to evaluate the degree of matching and generate high-scoring candidates.

[0310] The matching results are temporarily stored in a database and prepared for notification.

[0311] 4. Notification and Control

[0312] The server notifies users and companies of the matching results via email or in-app notifications.

[0313] Users can check the progress and compensation status of selected projects on a dashboard.

[0314] 5. Skills improvement support

[0315] The server analyzes market trend data and generates a list of skills and learning resources required by the user.

[0316] This is displayed on a user-specific dashboard to support self-improvement.

[0317] Specific examples

[0318] For example, suppose sales representative A, who lives in a rural area, registers and enters "3 years of B2B sales experience, online sales skills." Company B registers project information such as "online sales of a new product, required skills: B2B sales, use of web conferencing tools." The server stores the information of User A and Company B in a database, performs matching using an artificial intelligence algorithm, and generates high-scoring match candidates. The server notifies User A and Company B of the results, and User A accepts the project, thereby beginning remote sales activities. Progress management and compensation status can be checked on User A's dashboard. The server also analyzes market trends and provides resources to recommend that User A learn additional "online marketing skills."

[0319] Prompt Sentence Examples

[0320] Here are some example prompts for the generative AI model used in the job matching algorithm:

[0321] Sales Representative Profile:

[0322] Skill Set: {skill_set}

[0323] Years of experience: {years_of_experience}

[0324] Previous work experience: {job_history}

[0325] Company Project Information:

[0326] Job type: {job_type}

[0327] Job Description: {job_description}

[0328] Required Skill Set: {required_skills}

[0329] Reward: {salary}

[0330] Employment type: {employment_type}

[0331] Use the information above to match you with the most suitable sales representative.

[0332] In this way, a system can be realized that allows people living in rural areas to efficiently access corporate projects in urban areas and across the country, and to accept and proceed with appropriate projects.

[0333] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0334] Step 1:

[0335] The user enters their profile information and skill set to register as a new user. Specifically, the user accesses the application and enters information such as name, address, skill set, years of experience, and work history. Once this input is complete, the terminal validates this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the user that registration is complete.

[0336] Step 2:

[0337] Companies enter and register job information and project information. Specifically, companies log in to the application and enter detailed information such as job type, job content, required skill set, salary, work location, and working style. Once this input is complete, the terminal performs an initial validation of this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the company that registration is complete.

[0338] Step 3:

[0339] The server periodically reads user and company information from the database and runs a matching algorithm. Specifically, the server uses Python and SciKit Learn to compare user profile information with company job postings and job opportunities, scoring the degree of match. Based on the generated scores, high-scoring match candidates are generated and temporarily stored in the database. The algorithm uses machine learning models to find the best match, taking into account past matching data and trends.

[0340] Step 4:

[0341] The server notifies users and companies of high-scoring match candidates. Specifically, in preparation for the notification, the server dynamically generates the generated match candidate data and inserts it into email templates and in-application notification messages. The server uses Python's Django framework to construct the notification message and sends it to users and companies. Users and companies can then check the received notification and confirm detailed information about the match candidates.

[0342] Step 5:

[0343] Users manage the order process for projects and check progress and compensation status. Specifically, based on the project information received by users, they can check the progress and compensation status of projects on the dashboard within the application. The server links the project information with the user's progress data and continuously updates it.

[0344] Step 6:

[0345] The server analyzes market trend data and provides users with information to improve their skills. Specifically, it analyzes the received market trend data and identifies skills and knowledge that will be in high demand in the future. It uses Python to analyze the data and generates a list of skills and learning resources specifically for each user. This information is displayed on the user's dashboard and provided as reference for self-improvement.

[0346] Through these steps, we have created a system that allows sales representatives and freelancers living in rural areas to efficiently manage projects and improve their skills.

[0347] 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.

[0348] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. Below, the program processing of this system is explained in natural language.

[0349] Program processing description

[0350] New user registration

[0351] User

[0352] Visit the website or application and click the "Sign Up" button.

[0353] Enter your profile information, such as your name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[0354] The emotion engine recognizes and records the user's emotional state through facial expressions and voice input.

[0355] Terminal

[0356] Perform initial validation (format check and check for required fields) on the entered information and emotional data to ensure they are entered correctly.

[0357] Send the validated information to the server.

[0358] server

[0359] The received user profile information, desired conditions, and emotional data are stored in a database.

[0360] Registering company job information

[0361] company

[0362] Visit the website or application and click on the "Subscribe to a Job" button.

[0363] Enter the details of the job offer, such as the job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc.

[0364] Terminal

[0365] Perform initial validation of entered information.

[0366] Send the validated information to the server.

[0367] server

[0368] The received company job information is saved in a database.

[0369] Matching Process

[0370] server

[0371] User and company information and user sentiment data are periodically read from the database.

[0372] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[0373] The emotional state of the user recognized by the emotion engine is also taken into consideration to optimize matching candidates.

[0374] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[0375] The matching results are temporarily stored in a database.

[0376] Matching notification

[0377] server

[0378] Prepare to notify users and companies of the matching results.

[0379] Notifications are sent via user and company registered email addresses and in-app notification systems.

[0380] Terminal

[0381] Users and businesses receive notifications and review the content of the notifications.

[0382] Next steps

[0383] User

[0384] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[0385] company

[0386] Check the user's profile information and, if interested, schedule an interview or skills test.

[0387] Skills improvement support

[0388] server

[0389] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[0390] The skill list is prioritized based on the user's emotional state as recognized by the emotion engine.

[0391] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[0392] User

[0393] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[0394] Specific examples

[0395] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[0396] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0397] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[0398] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0399] This system allows rural residents to acquire the skills required in urban areas, while also taking emotional data into account to achieve optimal matching, thereby achieving high productivity and a rich work-life balance.

[0400] The processing flow will be explained below.

[0401] Step 1:

[0402] A user visits a website or application and clicks the "Sign Up" button.

[0403] Step 2:

[0404] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[0405] Step 3:

[0406] The device activates an emotion engine to recognize and record the user's emotional state through facial expressions and voice input.

[0407] Step 4:

[0408] The device performs initial validation (format checks and checks for required fields) of the entered information and emotional data to confirm that it has been entered correctly.

[0409] Step 5:

[0410] The terminal sends the information that the validation has been completed to the server.

[0411] Step 6:

[0412] The server stores the received user profile information, desired conditions, and emotional data in a database.

[0413] Step 7:

[0414] A company visits their website or application and clicks the "Register a Job" button.

[0415] Step 8:

[0416] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[0417] Step 9:

[0418] The terminal performs an initial validation of the entered information.

[0419] Step 10:

[0420] The terminal sends the information that the validation has been completed to the server.

[0421] Step 11:

[0422] The server stores the received company job information in a database.

[0423] Step 12:

[0424] The server periodically reads user and company information and user emotion data from the database.

[0425] Step 13:

[0426] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[0427] Step 14:

[0428] The server also takes into consideration the emotional state of the user recognized by the emotion engine and optimizes the matching candidates.

[0429] Step 15:

[0430] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[0431] Step 16:

[0432] The server temporarily stores the matching results in a database.

[0433] Step 17:

[0434] The server prepares to notify users and companies of the matching results.

[0435] Step 18:

[0436] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[0437] Step 19:

[0438] The device receives a notification to the user and the company, and the notification content is confirmed.

[0439] Step 20:

[0440] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[0441] Step 21:

[0442] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0443] Step 22:

[0444] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[0445] Step 23:

[0446] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[0447] Step 24:

[0448] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[0449] Step 25:

[0450] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[0451] Specific examples

[0452] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent to the server.

[0453] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0454] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[0455] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0456] Example 2

[0457] 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."

[0458] When rural residents perform remote work for urban jobs, there are problems such as inappropriate matching and incompatible matches due to a lack of consideration of emotional states. Furthermore, there is a lack of effective support for rural residents to improve their skills, making it difficult for them to improve their competitiveness in the market.

[0459] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for recognizing the emotional state of residents using an emotion engine, a means for comparing the profile information, the emotional state, and the job information of the companies using an artificial intelligence algorithm to generate matching candidates, a means for notifying local residents and companies of the matching candidates, and a means for predicting trends for improving the skills of local residents and generating a list of required skills. This enables local residents to perform appropriate matching taking into account their emotional state and to effectively improve their skills.

[0460] "Rural residents" refers to individuals who reside in areas other than urban areas.

[0461] "Profile information" refers to personal information such as a user's name, address, email address, telephone number, skill set, years of experience, work history, desired work style, and desired industry and job type.

[0462] A "skill set" refers to a collection of specific skills and knowledge that a user possesses, and examples include programming languages ​​(JavaScript, Python, etc.).

[0463] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state through facial expressions and voice.

[0464] "Artificial intelligence algorithm" refers to the calculation procedures and models used to compare profile information with company job listings and generate optimal matching candidates.

[0465] "Matching candidates" refer to optimal combinations of users and companies generated based on profile information and company recruitment information.

[0466] "Database" refers to a structured collection of information within a computer system for storing profile information, job listings, emotional data, etc.

[0467] "Trend forecasting" refers to a method of analyzing market trends and predicting skills that are likely to be in high demand in the future.

[0468] A "skill list" refers to a list of skills and knowledge that local residents should learn to improve their skills.

[0469] "Notification" means information or communication sent to a user or business via email or within an application.

[0470] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. This system consists of the following elements.

[0471] 1. Register a new user:

[0472] A user accesses a website or application, clicks the "Sign Up" button, and then enters profile information such as their name, address, email address, phone number, skill set (e.g., JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), and desired industry and job type.

[0473] The emotion engine recognizes the user's emotional state in real time through facial expressions and voice input, and collects emotional data.

[0474] The device performs initial validation (format check and confirmation of required fields) on the information and emotion data collected to confirm that it has been entered correctly. After that, the validated information is sent to the server.

[0475] The server stores the received user profile information, desired conditions, and emotional data in a database.

[0476] 2. Company job postings:

[0477] Companies access their website or application, click the "Submit Job Information" button, and then enter details about the job, such as job type, job description, required skill set (e.g., JavaScript, Python), salary, work location, and working style.

[0478] The terminal performs an initial validation of the entered information to ensure it is entered correctly.

[0479] The validated information is sent to the server, and the company's job information received by the server is saved in the database.

[0480] 3. Matching Process:

[0481] The server periodically reads user and company information and sentiment data from the database.

[0482] The server uses an artificial intelligence algorithm to compare the user's profile information with company job listings, and also optimizes matching candidates by taking into account the user's emotional state as recognized by an emotion engine.

[0483] The server evaluates the degree of match between each user and company, and generates high-scoring match candidates, which are temporarily stored in a database.

[0484] 4. Match Notification:

[0485] The server prepares to notify users and companies of the matching results, using the registered email addresses of users and companies or the in-application notification system.

[0486] The device receives the notification and the user and company confirm the notification content.

[0487] 5. Next steps:

[0488] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[0489] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0490] 6. Skills development support:

[0491] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[0492] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[0493] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[0494] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[0495] Specific examples

[0496] A specific example is shown below.

[0497] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[0498] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0499] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[0500] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0501] Prompt Sentence Examples

[0502] Here are some example prompts for input using a generative AI model:

[0503] User A registers and enters "3 years of web development experience, knowledge of JavaScript and Python" as profile information. The emotion engine collects the user's emotional data. Company B posts a job posting with "Remote full-stack web developer wanted, required skills: JavaScript, Python." The server performs matching based on this information, and the system notifies User A and Company B of the results. Please explain the process.

[0504]

[0505] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0506] Step 1:

[0507] Accessing the Website or Application

[0508] A user visits a website or application and clicks the "Sign Up" button. Input: The URL accessed through a web browser. Output: The sign up form is displayed.

[0509] Step 2:

[0510] Enter your profile information

[0511] Users enter profile information such as their name, address, email address, phone number, skill set (e.g. JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc. Input: Data entered manually by the user. Output: Data entered into the form.

[0512] Step 3:

[0513] Collecting Emotional Data

[0514] While the user is entering their profile information, the device uses an emotion engine to recognize the user's emotional state in real time from their facial expressions and voice, and collects emotional data. Input: User's facial expressions and voice. Output: Recognized emotional data.

[0515] Step 4:

[0516] Information Validation

[0517] The device performs initial validation (format check and confirmation of required fields) on the collected profile information and emotion data to ensure they have been entered correctly. Input: Data and emotion data entered by the user. Output: Validated data.

[0518] Step 5:

[0519] Sending data

[0520] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[0521] Step 6:

[0522] Data storage

[0523] The server stores the received user profile information, desired conditions, and emotion data in a database. Input: Data sent from the device. Output: Data stored in the database.

[0524] Step 7:

[0525] Registering company job information

[0526] A company visits a website or application and clicks the "Submit a Job" button. Input: The URL accessed through a web browser. Output: The job submission form is displayed.

[0527] Step 8:

[0528] Enter job information

[0529] Companies enter detailed job information such as job type, job description, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc. Input: Data entered manually by the company. Output: Data entered into the form.

[0530] Step 9:

[0531] Information Validation

[0532] The terminal performs an initial validation of the entered information to ensure it is entered correctly. Input: Data entered by the company. Output: Validated data.

[0533] Step 10:

[0534] Sending data

[0535] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[0536] Step 11:

[0537] Data storage

[0538] The server stores the received company job information in a database. Input: Data sent from the device. Output: Data stored in the database.

[0539] Step 12:

[0540] Loading data

[0541] The server periodically reads user and company information and sentiment data from the database. Input: Information stored in the database. Output: Read data.

[0542] Step 13:

[0543] Comparing information

[0544] The server uses an artificial intelligence algorithm to compare the user's profile information with the company's job listings. Input: The data loaded. Output: The comparison result data.

[0545] Step 14:

[0546] Considering emotional data

[0547] The server also takes into account the user's emotional state recognized by the emotion engine to optimize the matching candidates. Input: Recognized emotion data. Output: Optimized matching candidates.

[0548] Step 15:

[0549] Evaluating potential matches

[0550] The server evaluates the match degree of each user and company and generates high-scoring match candidates. Input: Optimized match candidates. Output: High-scoring match candidates.

[0551] Step 16:

[0552] Saving matching results

[0553] The server temporarily stores the matching results in a database. Input: High-scoring matching candidates. Output: Matching results temporarily stored in the database.

[0554] Step 17:

[0555] Preparation for notification

[0556] The server prepares to notify users and companies of the matching results. Input: Temporarily saved matching results. Output: Notification arrangement data.

[0557] Step 18:

[0558] Sending notifications

[0559] The server sends notifications using the user's and company's registered email address or the in-application notification system. Input: Notification arrangement data. Output: Sent notification.

[0560] Step 19:

[0561] Receive notifications

[0562] The device receives notifications and allows users and businesses to confirm the notification content. Input: Sent notification. Output: Confirmed notification content.

[0563] Step 20:

[0564] Applying for an interview

[0565] The user checks the information of the matched companies, and if they are interested, they apply for an interview with the company via the application or email. Input: Confirmed notification content. Output: Interview application data.

[0566] Step 21:

[0567] Arranging interview dates

[0568] Companies will review your profile information and, if interested, schedule an interview or skill test. Input: Reviewed profile information. Output: Arranged interview date.

[0569] Step 22:

[0570] Generate a skill list

[0571] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data. Input: User profile information and market trend data. Output: Analyzed skill list.

[0572] Step 23:

[0573] Prioritizing the Skill List

[0574] The server changes the priority of the skill list based on the user's emotional state recognized by the emotion engine. Input: User's emotional data and skill list. Output: Prioritized skill list.

[0575] Step 24:

[0576] View the recommendation list

[0577] The server generates a list of recommendations for skilling and displays it on the user's personal dashboard. Input: A prioritized list of skills. Output: A list of recommendations displayed on the dashboard.

[0578] Step 25:

[0579] Skill Up Implementation

[0580] Users check the recommended skill list and learning resources (online courses, links to teaching materials, etc.) to improve their skills. Input: Recommendation list displayed on the dashboard. Output: Skill improvement execution data.

[0581] (Application example 2)

[0582] 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."

[0583] Remote work, a new form of work, is becoming more common in modern work, but there is a lack of appropriate matching and skill development support for rural residents when they access urban companies and projects. Furthermore, there is a need for matching that takes into account the emotional state of residents, rather than simply matching skills. The purpose of this invention is to solve these issues and enable rural residents to be appropriately matched with urban companies remotely, resulting in high productivity and satisfaction.

[0584] The identification process by the identification 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 a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates, a means for notifying local residents and companies of the matching candidates, a means for predicting trends for improving the skills of local residents and generating a list of required skills, a means for recognizing and recording the emotional state of local residents using an emotion engine, a means for optimally matching projects taking the emotional state into consideration, and a means for local residents to check project information in a virtual store and provide skill-up resources. This allows local residents to be optimally matched with urban companies and projects, and by considering emotional data, remote work can be realized with high productivity and satisfaction.

[0585] "Profile information" refers to personal information of local residents, including their skill sets, past work history, and desired industry and occupation.

[0586] "Skill set" refers to the collection of technical abilities and knowledge possessed by local residents, specifically programming languages ​​and specific job skills.

[0587] The "Emotion Engine" is a system that recognizes and records the user's emotional state through facial expressions and voice.

[0588] An "artificial intelligence algorithm" is a calculation method that compares input profile information with job information and generates optimal matching candidates.

[0589] "Matching candidates" are people or projects whose skills and job requirements match those of local residents and companies.

[0590] A "virtual store" refers to an online platform that operates in a virtual space, rather than a real physical store.

[0591] "Trend forecasting" is the process of analyzing and predicting current market trends and future skill demands.

[0592] The "database" is a system that stores and manages input information and emotional data from local residents and businesses.

[0593] "Notification" refers to the act of informing local residents and businesses of matching results and other important information.

[0594] "Skill-up resources" refers to learning materials, online courses, and related information that rural residents can use to improve their skills.

[0595] The system that realizes this invention allows residents of rural areas to remotely access companies and projects in urban areas and receive appropriate matching and skill development support. The program processing of this system will be explained in detail below.

[0596] Program generation and processing content

[0597] New user registration

[0598] Device: The user registers using a smartphone or head-mounted display, entering profile information such as name, address, skill set, past work experience, and desired industry and job type.

[0599] Emotion engine: When inputting, the emotion engine recognizes and records the user's emotional state through facial expressions and voice. This emotional data is also sent to the server. Specific software used is "Affectiva Emotion AI" and "Microsoft (registered trademark) Azure (registered trademark) Cognitive Services."

[0600] Server: Profile information and emotion data are stored in a database using MySQL (registered trademark) and GOOGLE FI (registered trademark) rebase.

[0601] Registering company project information

[0602] Companies: Register project information through the virtual store's website or app, including job title, job description, required skill set, salary, etc.

[0603] Terminal: Performs initial validation of registered information and sends it to the server.

[0604] Server: Stores the company's project information in a database.

[0605] Matching Process

[0606] Server: Uses an artificial intelligence (AI) algorithm to compare profile information with company project information. The emotion engine recognizes the user's emotional state and generates optimal matching candidates. Specifically, it uses Tensorflow (registered trademark) and PyTorch.

[0607] Server: Notifies local residents and businesses of potential matches via email or in-app notifications.

[0608] Skills improvement support

[0609] Server: Based on user profile information and sentiment data, predicts skills that will be in demand in the future, and generates skill development lists and learning resources that users can view in a virtual store.

[0610] Users: Check out the recommended skill list and learning resources (e.g., online courses) to improve their skills.

[0611] Specific examples

[0612] User A uses a smartphone to register information such as "3 years of web development experience, Python" and records a self-introduction along with a happy expression. Company B registers "Remote web development project, required skills: Python." The server then combines the emotion data and skill information to perform matching and notifies User A and Company B.

[0613] Prompt Sentence Examples

[0614] User A (smartphone):

[0615] New Registration

[0616] Name: Tanaka

[0617] Experience: 3 years of web development experience, Python

[0618] Desired job type: Remote work

[0619] Desired industry: IT

[0620] Expression: Joy

[0621] Company B (virtual store app):

[0622] New project information registration

[0623] Job Title: Web Development

[0624] Required skills: Python

[0625] Salary: 3,000 yen per hour

[0626] This system allows local residents to be matched with the most suitable projects taking into account their emotional state, enabling them to achieve high productivity and satisfaction through remote work.

[0627] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0628] Step 1:

[0629] New user registration

[0630] Input: The user uses a smartphone or head-mounted display to enter profile information (name, address, skill set, past work experience, desired industry and job type, etc.) on the new registration screen.

[0631] Processing: During input, an emotion engine (e.g., Affectiva Emotion AI or Microsoft Azure Cognitive Services) recognizes and records the user's emotional state through facial expressions and voice in real time. This data is sent from the device to a server.

[0632] Output: Profile information and emotion data are stored on the server.

[0633] Step 2:

[0634] Registering company project information

[0635] Input: Companies use the virtual store's website or application to register project information (job type, job description, required skill set, salary, working hours, etc.).

[0636] Processing: During registration, the device performs initial validation of the data (format checks, required fields checks) and sends the validated information to the server.

[0637] Output: Project information is saved to the server database.

[0638] Step 3:

[0639] Matching Process

[0640] Input: The server periodically retrieves user profile information, emotion data, and company project information from the database.

[0641] Processing: The server uses artificial intelligence (AI) algorithms (e.g., TensorFlow or PyTorch) to compare the user's profile information with the company's project information, and generates optimal matching candidates taking into account the user's emotional state as recognized by the emotion engine.

[0642] Output: A list of potential matches is generated and temporarily stored on the server.

[0643] Step 4:

[0644] Notification of matching results

[0645] Input: The server retrieves a list of potential matches and prepares to notify local residents and businesses.

[0646] Processing: The server selects a notification method (email or in-app notification) and sends the matching results, including details about the project and next steps.

[0647] Output: Local residents and businesses receive and review the notification.

[0648] Step 5:

[0649] Skills improvement support

[0650] Input: The server periodically retrieves user profile information and sentiment data, as well as market trend data.

[0651] Processing: The server uses trend prediction algorithms to analyze skills that are likely to be in demand in the future, creates a prioritized skill list based on sentiment data, and generates learning resources (online courses and learning links).

[0652] Output: Skilling resources are displayed on a dashboard for local residents.

[0653] Step 6:

[0654] Project Initiation Procedures

[0655] Input: Local residents receive notifications and begin the application process for projects they're interested in. Companies similarly schedule interviews and skill tests for interested users.

[0656] Processing: The terminal provides an interface for application procedures and interview arrangements, and sends that information to the server.

[0657] Output: The project officially begins, with users and companies collaborating through remote work.

[0658] In this way, each step is carried out in a sequential manner, enabling quick and effective matching between users and companies. Furthermore, ongoing support for skill development improves users' productivity and satisfaction with remote work.

[0659] 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.

[0660] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0661] 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.

[0662] [Second embodiment]

[0663] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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).

[0669] 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. 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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."

[0675] The present invention is a system that allows local residents to work remotely from urban areas. The program processing of this system will be explained below in natural language.

[0676] Program processing description

[0677] New user registration

[0678] User

[0679] Visit the website or application and click the "Sign Up" button.

[0680] Enter your profile information, such as your name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0681] Terminal

[0682] Perform initial validation of the entered information (checking format and required fields) to confirm that it has been entered correctly.

[0683] Send the validated information to the server.

[0684] server

[0685] The received user profile information and desired conditions are stored in a database.

[0686] Registering company job information

[0687] company

[0688] Visit the website or application and click on the "Subscribe to a Job" button.

[0689] Enter the details of the job offer, such as the job type, job content, required skill set, salary, work location, and working style.

[0690] Terminal

[0691] Perform initial validation of entered information.

[0692] Send the validated information to the server.

[0693] server

[0694] The received company job information is saved in a database.

[0695] Matching Process

[0696] server

[0697] Periodically read user and company information from the database.

[0698] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[0699] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[0700] The matching results are temporarily stored in a database.

[0701] Matching notification

[0702] server

[0703] Prepare to notify users and companies of the matching results.

[0704] Notifications are sent via user and company registered email addresses and in-app notification systems.

[0705] Terminal

[0706] Users and businesses receive notifications and review the content of the notifications.

[0707] Next steps

[0708] User

[0709] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[0710] company

[0711] Check the user's profile information and, if interested, schedule an interview or skills test.

[0712] Skills improvement support

[0713] server

[0714] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[0715] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[0716] User

[0717] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[0718] Specific examples

[0719] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[0720] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0721] The server stores the information of User A and Company B in a database and matches them using an artificial intelligence algorithm.

[0722] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0723] This system will enable rural residents to acquire skills needed in urban areas, while achieving high productivity and a good work-life balance, thereby helping to revitalize Japan as a whole.

[0724] The processing flow will be explained below.

[0725] Step 1:

[0726] A user visits a website or application and clicks the "Sign Up" button.

[0727] Step 2:

[0728] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[0729] Step 3:

[0730] The terminal performs initial validation of the information entered (checking the format and checking for required fields) to ensure that it has been entered correctly.

[0731] Step 4:

[0732] The terminal sends the information that the validation has been completed to the server.

[0733] Step 5:

[0734] The server stores the received user profile information and desired conditions in a database.

[0735] Step 6:

[0736] A company visits their website or application and clicks the "Register a Job" button.

[0737] Step 7:

[0738] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[0739] Step 8:

[0740] The terminal performs an initial validation of the entered information.

[0741] Step 9:

[0742] The terminal sends the information that the validation has been completed to the server.

[0743] Step 10:

[0744] The server stores the received company job information in a database.

[0745] Step 11:

[0746] The server periodically reads user and company information from the database.

[0747] Step 12:

[0748] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[0749] Step 13:

[0750] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[0751] Step 14:

[0752] The server temporarily stores the matching results in a database.

[0753] Step 15:

[0754] The server prepares to notify the user and the company of the matching results.

[0755] Step 16:

[0756] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[0757] Step 17:

[0758] The device receives a notification to the user and the company, and the notification content is confirmed.

[0759] Step 18:

[0760] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[0761] Step 19:

[0762] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0763] Step 20:

[0764] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[0765] Step 20:

[0766] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[0767] Step 21:

[0768] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[0769] Example 1

[0770] 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."

[0771] To make it easier for rural residents to access jobs in urban areas, it is necessary to bridge the information gap between rural and urban areas. The current recruitment system makes it difficult for rural residents to find suitable jobs, and for companies to efficiently recruit talented personnel from remote areas. Furthermore, there are no established methods for rural residents to properly learn and acquire the skills required in urban areas, resulting in a skills gap. A comprehensive system to resolve these issues is needed.

[0772] 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.

[0773] In this invention, the server includes: a means for rural residents to input their profile information and skill set; a means for companies to register job information; a means for initially validating the input information; a means for transmitting validated information to the server; a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates; a means for notifying the matching candidates to rural residents and companies; and a means for predicting trends for improving the skills of rural residents and generating a list of required skills. This makes it easier for rural residents to access jobs in urban areas and enables companies to efficiently recruit talented people from remote locations. Furthermore, since rural residents can appropriately learn and acquire skills required in urban areas, the skills gap can be eliminated.

[0774] "Rural residents" refers to individuals who reside in areas away from urban areas.

[0775] "Profile information" refers to personal information such as the user's name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0776] "Skill set" refers to the skills, knowledge, and specialized abilities possessed by a user.

[0777] "Company" refers to the legal entity that registers job information.

[0778] "Job information" refers to information such as the type of job offered by a company, specific job content, required skill set, salary, work location, and working style.

[0779] "Initial validation" refers to the process of verifying that the information entered is formally correct and that all required fields are filled in.

[0780] "Server" refers to a high performance computer system that processes and stores data.

[0781] "Artificial intelligence algorithm" refers to a calculation method that analyzes user profile information and company job information to generate optimal matching candidates.

[0782] "Matching candidates" refer to the combination that is evaluated as optimal after comparing user and company information.

[0783] "Notification" refers to the act of informing users and businesses of matching results and other important information.

[0784] "Trend forecasting" refers to the process of analyzing market demand and future trends and predicting future trends based on the results.

[0785] The "Skills Needed List" is a list of recommendations for rural residents to acquire skills that will be in demand in the future.

[0786] The present invention is a comprehensive system that enables rural residents to remotely access urban jobs and develop appropriate skills. The system is configured as follows.

[0787] System Configuration

[0788] The system includes multiple components that work together: a user device, a company device, and a server, which contains a database that stores relevant data and an artificial intelligence (AI) model that runs the matching algorithm.

[0789] Program processing overview

[0790] The main processing flow of the system will be specifically explained below.

[0791] New user registration

[0792] Users access the website or application using their own device and click the "New Registration" button. They then enter their profile information, such as their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0793] The terminal performs initial validation of the information entered by the user in real time, for example, checking that the email address is formatted correctly and that all required fields are filled in. If validation passes, the information is sent to the server.

[0794] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[0795] Registering company job information

[0796] Companies access the website or application using their own devices, click the "Register Job Information" button, and enter details of the job, such as job type, job description, required skill set, salary, work location, and working style.

[0797] The terminal performs an initial validation of the information entered by the company in real time, for example, ensuring that the salary range is appropriate and the required skill set is specifically described, and if validation passes, it sends this information to the server.

[0798] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[0799] Matching Process

[0800] The server periodically reads user and company information from the database. It uses a generative AI model to compare the user's profile information with the company's job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[0801] Matching notification

[0802] The server prepares to notify users and businesses of the matching results. Notifications are sent to the users' and businesses' registered email addresses or via the notification system within the application.

[0803] The terminal displays the notification received by the user and the company, who then checks the notification content and takes the next action.

[0804] Skills improvement support

[0805] The server analyzes the skills that are expected to be in demand in the future based on the user's profile information and market trend data, and uses a generative AI model to generate a list of recommendations for skill development, which are displayed on the user's dedicated dashboard.

[0806] Users can check the recommended skill list and learning resources to improve their skills, which will support their ability development.

[0807] Specific examples

[0808] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[0809] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[0810] The server stores the information of User A and Company B in a database and performs matching using a generative AI model.

[0811] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[0812] Prompt Sentence Examples

[0813] Below are some examples of prompts to input to the generative AI model.

[0814] "Please explain the user registration process for the remote work support system in natural language."

[0815] "Please explain in natural language the process a company goes through to register a job posting."

[0816] "Please explain in natural language the process of matching users and companies."

[0817] "Please explain in natural language the process of notifying matching results."

[0818] "Please explain in natural language the process of supporting skill development in a remote work support system."

[0819] The above is an embodiment of the present invention. This will make it easier for rural residents to access jobs in urban areas, and will enable companies to efficiently recruit talented people in remote areas. It will also enable rural residents to appropriately study and acquire the skills required in urban areas, thereby eliminating the skills gap.

[0820] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0821] New user registration

[0822] Step 1:

[0823] The user accesses the website or application using their own device and clicks the "New Registration" button. A profile entry screen appears, and the user enters their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[0824] Input: User's personal information and preferences.

[0825] Output: Profile information entered into the terminal.

[0826] Step 2:

[0827] The terminal performs initial validation of the information entered by the user in real time, for example, ensuring that the email address is formatted correctly and that all required fields are filled in.

[0828] Input: The profile information entered in step 1.

[0829] Data processing: Check email address format and confirm required fields.

[0830] Output: Profile information that passes validation.

[0831] Step 3:

[0832] The terminal transmits the profile information that has passed validation to the server.

[0833] Input: Profile information that passes initial validation.

[0834] Output: The profile information sent to the server.

[0835] Step 4:

[0836] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[0837] Input: Profile information sent from the device.

[0838] Data processing: storing information in a database.

[0839] Output: Profile information stored in a database.

[0840] Registering company job information

[0841] Step 1:

[0842] Companies access the website or application using their own devices and click the "Register Job Information" button. A job information entry screen will appear, where companies can enter details such as job type, job content, required skill set, salary, work location, and working style.

[0843] Input: Job details (job type, job description, required skill set, salary, work location, working style, etc.).

[0844] Output: The job information entered into the terminal.

[0845] Step 2:

[0846] The terminal performs initial validation of the information entered by the company in real time, for example, to check the appropriateness of the salary and the specificity of the required skill set.

[0847] Input: The job information entered in step 1.

[0848] Data processing: Checking the validity of salaries and confirming the specificity of skill sets.

[0849] Output: A job that passes validation.

[0850] Step 3:

[0851] The terminal transmits the job information that has passed validation to the server.

[0852] Input: A job that passes initial validation.

[0853] Output: The job listing sent to the server.

[0854] Step 4:

[0855] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[0856] Input: Job posting submitted from device.

[0857] Data processing: storing information in a database.

[0858] Output: Job information stored in the database.

[0859] Matching Process

[0860] Step 1:

[0861] The server periodically reads user and company information from the database, a process that is performed automatically by a scheduled job.

[0862] Input: User and company information in the database.

[0863] Output: The imported user and company information.

[0864] Step 2:

[0865] The server uses a generative AI model to compare user profile information with company job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[0866] Input: User and company information imported in step 1.

[0867] Data processing: Analyzing information with a generative AI model and calculating matching scores.

[0868] Output: Match score and candidate matches.

[0869] Step 3:

[0870] The server generates the best matching candidates based on the obtained matching scores and stores them in a temporary database.

[0871] Input: Matching score and match candidates.

[0872] Data processing: storing information in a temporary database.

[0873] Output: Match candidates stored in a temporary database.

[0874] Matching notification

[0875] Step 1:

[0876] The server prepares the email addresses registered by the user and the company and the in-application notification system, generates notification content according to templates, and adds it to the queue for sending.

[0877] Input: Match candidates stored in a temporary database.

[0878] Data processing: Creating notification content and queuing it for sending.

[0879] Output: The notification content queued for sending.

[0880] Step 2:

[0881] The server sends notifications as they become ready, using an SMTP server for email notifications and calling the corresponding notification API for in-app notifications.

[0882] Input: The notification content that has been queued for sending.

[0883] Data processing: Sending notifications using an SMTP server or notification API.

[0884] Output: Notifications sent to users and businesses.

[0885] Step 3:

[0886] The device displays the notifications received by the user and the company, and the user and the company check the notification content and consider the next action.

[0887] Input: Notifications sent to users and businesses.

[0888] Output: The notification content that will be displayed on your device.

[0889] Next steps

[0890] Step 1:

[0891] Users can check the information of the matched companies, and if they are interested, they can apply for an interview with the company via the application's functions or email.

[0892] Input: Notification details and matched company information.

[0893] Output: Interview request submitted.

[0894] Step 2:

[0895] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[0896] Input: Notification content and matched user information.

[0897] Output: Scheduling interviews and skills tests.

[0898] Skills improvement support

[0899] Step 1:

[0900] The server analyzes the skills that are likely to be in demand in the future based on user profile information and market trend data, using a generative AI model for this analysis.

[0901] Input: User profile information and market trend data.

[0902] Data processing: Analyzing skill demand with generative AI models.

[0903] Output: A list of skills that are expected to be in demand.

[0904] Step 2:

[0905] Based on the analysis results, the server generates a list of recommended skills for the user and displays it on the user's dashboard.

[0906] Input: A list of skills that are expected to be in demand.

[0907] Data processing: Generating a list of recommended skills for improvement.

[0908] Output: A list of recommended skills to be improved, displayed on the user's dashboard.

[0909] Step 3:

[0910] Users can review a list of recommended skills and learning resources to improve their skills, such as taking online courses or using designated study materials.

[0911] Input: A list of recommended skills displayed on the user's dashboard.

[0912] Output: Actions to improve skills (taking courses and using learning materials).

[0913] (Application example 1)

[0914] 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."

[0915] Sales activities for sales representatives and freelancers living in rural areas face the challenge of limited means of accessing corporate projects in urban areas and across the country, and limited means of efficiently managing those projects, which requires a great deal of effort and time. Matching with suitable projects is also difficult, and an efficient system is needed to enable sales representatives living in rural areas to smoothly conduct transactions with urban companies. Furthermore, there is a lack of appropriate information sources to help rural residents improve their skills.

[0916] 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.

[0917] In this invention, the server includes: a means for local residents to input their own profile information and skill set; a means for companies to register job information and project information; a means for using an artificial intelligence algorithm to compare the profile information with the company's job information and project information to generate matching candidates; a means for notifying local residents and companies of the matching candidates; a means for predicting trends for improving the skills of local residents and generating a list of necessary skills and learning resources; and a means for displaying the trend predictions and skill list on a dashboard. This allows local residents to efficiently access corporate projects and centrally manage the progress and compensation status of projects. It also provides appropriate information for skill improvement.

[0918] "Rural residents" refers to individuals who reside in rural areas and are physically separated from urban and other areas.

[0919] "Profile information" is a general term for information that indicates an individual's characteristics, such as name, address, skill set, years of experience, and work history.

[0920] A "skill set" refers to the collection of skills and knowledge that an individual possesses, and is a list of the abilities required to perform a specific job.

[0921] "Company" refers to a legal entity that provides products or services.

[0922] "Job information" is information published by a company about the requirements and conditions for jobs and positions that the company is seeking.

[0923] "Project Information" refers to the job description provided by a company, including detailed information about a specific project or job.

[0924] An "artificial intelligence algorithm" is a computational method for analyzing data and finding patterns and relationships, and uses machine learning and natural language processing to process information.

[0925] "Matching candidates" refer to proposals for highly compatible combinations based on information about the user and the company.

[0926] "Notification" means the act of communicating specific information to a designated recipient, whether via email or an in-application notification system.

[0927] "Trend forecasting" refers to the act of analyzing and predicting the skills and market trends that will be required from the present to the future.

[0928] A "skills list" is a list of skills required for a specific job or task.

[0929] "Learning resources" refers to educational materials such as textbooks and online courses that can be used to improve skills.

[0930] A "dashboard" refers to a visual interface that allows users to understand information at a glance.

[0931] "Progress management" refers to the act of managing and tracking the progress of a case or project.

[0932] "Remuneration status" refers to the act of managing the status of compensation paid for completed work or projects.

[0933] This invention is a system for supporting the sales activities of sales representatives and freelancers living in rural areas, specifically, allowing rural residents to access corporate projects in urban areas and across the country and efficiently check the progress management and compensation status of projects. An embodiment of this system is described below.

[0934] System program configuration

[0935] The system mainly consists of a server, user terminals, and enterprise terminals, and uses artificial intelligence algorithms (e.g., SciKit Learn), databases (e.g., PostgreSQL), and web servers (e.g., the Django framework) as necessary technical components.

[0936] Processing flow

[0937] 1. New user registration

[0938] The user enters their profile information and skill set.

[0939] Initial validation is performed on the terminal side and sent to the server.

[0940] The server stores the received information in a database and notifies the user that registration is complete.

[0941] 2. Registering company job information and project information

[0942] Companies enter detailed job and project information.

[0943] Initial validation is performed on the terminal side and sent to the server.

[0944] The server stores the received information in a database and notifies the company that registration is complete.

[0945] 3. Matching by AI algorithm

[0946] The server periodically reads user and company information from the database and performs a comparison.

[0947] An artificial intelligence algorithm is used to evaluate the degree of matching and generate high-scoring candidates.

[0948] The matching results are temporarily stored in a database and prepared for notification.

[0949] 4. Notification and Control

[0950] The server notifies users and companies of the matching results via email or in-app notifications.

[0951] Users can check the progress and compensation status of selected projects on a dashboard.

[0952] 5. Skills improvement support

[0953] The server analyzes market trend data and generates a list of skills and learning resources required by the user.

[0954] This is displayed on a user-specific dashboard to support self-improvement.

[0955] Specific examples

[0956] For example, suppose sales representative A, who lives in a rural area, registers and enters "3 years of B2B sales experience, online sales skills." Company B registers project information such as "online sales of a new product, required skills: B2B sales, use of web conferencing tools." The server stores the information of User A and Company B in a database, performs matching using an artificial intelligence algorithm, and generates high-scoring match candidates. The server notifies User A and Company B of the results, and User A accepts the project, thereby beginning remote sales activities. Progress management and compensation status can be checked on User A's dashboard. The server also analyzes market trends and provides resources to recommend that User A learn additional "online marketing skills."

[0957] Prompt Sentence Examples

[0958] Here are some example prompts for the generative AI model used in the job matching algorithm:

[0959] Sales Representative Profile:

[0960] Skill Set: {skill_set}

[0961] Years of experience: {years_of_experience}

[0962] Previous work experience: {job_history}

[0963] Company Project Information:

[0964] Job type: {job_type}

[0965] Job Description: {job_description}

[0966] Required Skill Set: {required_skills}

[0967] Reward: {salary}

[0968] Employment type: {employment_type}

[0969] Use the information above to match you with the most suitable sales representative.

[0970] In this way, a system can be realized that allows people living in rural areas to efficiently access corporate projects in urban areas and across the country, and to accept and proceed with appropriate projects.

[0971] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0972] Step 1:

[0973] The user enters their profile information and skill set to register as a new user. Specifically, the user accesses the application and enters information such as name, address, skill set, years of experience, and work history. Once this input is complete, the terminal validates this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the user that registration is complete.

[0974] Step 2:

[0975] Companies enter and register job information and project information. Specifically, companies log in to the application and enter detailed information such as job type, job content, required skill set, salary, work location, and working style. Once this input is complete, the terminal performs an initial validation of this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the company that registration is complete.

[0976] Step 3:

[0977] The server periodically reads user and company information from the database and runs a matching algorithm. Specifically, the server uses Python and SciKit Learn to compare user profile information with company job postings and job opportunities, scoring the degree of match. Based on the generated scores, high-scoring match candidates are generated and temporarily stored in the database. The algorithm uses machine learning models to find the best match, taking into account past matching data and trends.

[0978] Step 4:

[0979] The server notifies users and companies of high-scoring match candidates. Specifically, in preparation for the notification, the server dynamically generates the generated match candidate data and inserts it into email templates and in-application notification messages. The server uses Python's Django framework to construct the notification message and sends it to users and companies. Users and companies can then check the received notification and confirm detailed information about the match candidates.

[0980] Step 5:

[0981] Users manage the order process for projects and check progress and compensation status. Specifically, based on the project information received by users, they can check the progress and compensation status of projects on the dashboard within the application. The server links the project information with the user's progress data and continuously updates it.

[0982] Step 6:

[0983] The server analyzes market trend data and provides users with information to improve their skills. Specifically, it analyzes the received market trend data and identifies skills and knowledge that will be in high demand in the future. It uses Python to analyze the data and generates a list of skills and learning resources specifically for each user. This information is displayed on the user's dashboard and provided as reference for self-improvement.

[0984] Through these steps, we have created a system that allows sales representatives and freelancers living in rural areas to efficiently manage projects and improve their skills.

[0985] 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.

[0986] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. Below, the program processing of this system is explained in natural language.

[0987] Program processing description

[0988] New user registration

[0989] User

[0990] Visit the website or application and click the "Sign Up" button.

[0991] Enter your profile information, such as your name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[0992] The emotion engine recognizes and records the user's emotional state through facial expressions and voice input.

[0993] Terminal

[0994] Perform initial validation (format check and check for required fields) on the entered information and emotional data to ensure they are entered correctly.

[0995] Send the validated information to the server.

[0996] server

[0997] The received user profile information, desired conditions, and emotional data are stored in a database.

[0998] Registering company job information

[0999] company

[1000] Visit the website or application and click on the "Subscribe to a Job" button.

[1001] Enter the details of the job offer, such as the job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc.

[1002] Terminal

[1003] Perform initial validation of entered information.

[1004] Send the validated information to the server.

[1005] server

[1006] The received company job information is saved in a database.

[1007] Matching Process

[1008] server

[1009] User and company information and user sentiment data are periodically read from the database.

[1010] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[1011] The emotional state of the user recognized by the emotion engine is also taken into consideration to optimize matching candidates.

[1012] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[1013] The matching results are temporarily stored in a database.

[1014] Matching notification

[1015] server

[1016] Prepare to notify users and companies of the matching results.

[1017] Notifications are sent via user and company registered email addresses and in-app notification systems.

[1018] Terminal

[1019] Users and businesses receive notifications and review the content of the notifications.

[1020] Next steps

[1021] User

[1022] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[1023] company

[1024] Check the user's profile information and, if interested, schedule an interview or skills test.

[1025] Skills improvement support

[1026] server

[1027] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[1028] The skill list is prioritized based on the user's emotional state as recognized by the emotion engine.

[1029] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[1030] User

[1031] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[1032] Specific examples

[1033] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[1034] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1035] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1036] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1037] This system allows rural residents to acquire the skills required in urban areas, while also taking emotional data into account to achieve optimal matching, thereby achieving high productivity and a rich work-life balance.

[1038] The processing flow will be explained below.

[1039] Step 1:

[1040] A user visits a website or application and clicks the "Sign Up" button.

[1041] Step 2:

[1042] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[1043] Step 3:

[1044] The device activates an emotion engine to recognize and record the user's emotional state through facial expressions and voice input.

[1045] Step 4:

[1046] The device performs initial validation (format checks and checks for required fields) of the entered information and emotional data to confirm that it has been entered correctly.

[1047] Step 5:

[1048] The terminal sends the information that the validation has been completed to the server.

[1049] Step 6:

[1050] The server stores the received user profile information, desired conditions, and emotional data in a database.

[1051] Step 7:

[1052] A company visits their website or application and clicks the "Register a Job" button.

[1053] Step 8:

[1054] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[1055] Step 9:

[1056] The terminal performs an initial validation of the entered information.

[1057] Step 10:

[1058] The terminal sends the information that the validation has been completed to the server.

[1059] Step 11:

[1060] The server stores the received company job information in a database.

[1061] Step 12:

[1062] The server periodically reads user and company information and user emotion data from the database.

[1063] Step 13:

[1064] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[1065] Step 14:

[1066] The server also takes into consideration the emotional state of the user recognized by the emotion engine and optimizes the matching candidates.

[1067] Step 15:

[1068] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[1069] Step 16:

[1070] The server temporarily stores the matching results in a database.

[1071] Step 17:

[1072] The server prepares to notify users and companies of the matching results.

[1073] Step 18:

[1074] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[1075] Step 19:

[1076] The device receives a notification to the user and the company, and the notification content is confirmed.

[1077] Step 20:

[1078] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[1079] Step 21:

[1080] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1081] Step 22:

[1082] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[1083] Step 23:

[1084] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[1085] Step 24:

[1086] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[1087] Step 25:

[1088] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[1089] Specific examples

[1090] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent to the server.

[1091] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1092] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1093] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1094] Example 2

[1095] 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."

[1096] When rural residents perform remote work for urban jobs, there are problems such as inappropriate matching and incompatible matches due to a lack of consideration of emotional states. Furthermore, there is a lack of effective support for rural residents to improve their skills, making it difficult for them to improve their competitiveness in the market.

[1097] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for recognizing the emotional state of residents using an emotion engine, a means for comparing the profile information, the emotional state, and the job information of the companies using an artificial intelligence algorithm to generate matching candidates, a means for notifying local residents and companies of the matching candidates, and a means for predicting trends for improving the skills of local residents and generating a list of required skills. This enables local residents to perform appropriate matching taking into account their emotional state and to effectively improve their skills.

[1098] "Rural residents" refers to individuals who reside in areas other than urban areas.

[1099] "Profile information" refers to personal information such as a user's name, address, email address, telephone number, skill set, years of experience, work history, desired work style, and desired industry and job type.

[1100] A "skill set" refers to a collection of specific skills and knowledge that a user possesses, and examples include programming languages ​​(JavaScript, Python, etc.).

[1101] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state through facial expressions and voice.

[1102] "Artificial intelligence algorithm" refers to the calculation procedures and models used to compare profile information with company job listings and generate optimal matching candidates.

[1103] "Matching candidates" refer to optimal combinations of users and companies generated based on profile information and company recruitment information.

[1104] "Database" refers to a structured collection of information within a computer system for storing profile information, job listings, emotional data, etc.

[1105] "Trend forecasting" refers to a method of analyzing market trends and predicting skills that are likely to be in high demand in the future.

[1106] A "skill list" refers to a list of skills and knowledge that local residents should learn to improve their skills.

[1107] "Notification" means information or communication sent to a user or business via email or within an application.

[1108] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. This system consists of the following elements.

[1109] 1. Register a new user:

[1110] A user accesses a website or application, clicks the "Sign Up" button, and then enters profile information such as their name, address, email address, phone number, skill set (e.g., JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), and desired industry and job type.

[1111] The emotion engine recognizes the user's emotional state in real time through facial expressions and voice input, and collects emotional data.

[1112] The device performs initial validation (format check and confirmation of required fields) on the information and emotion data collected to confirm that it has been entered correctly. After that, the validated information is sent to the server.

[1113] The server stores the received user profile information, desired conditions, and emotional data in a database.

[1114] 2. Company job postings:

[1115] Companies access their website or application, click the "Submit Job Information" button, and then enter details about the job, such as job type, job description, required skill set (e.g., JavaScript, Python), salary, work location, and working style.

[1116] The terminal performs an initial validation of the entered information to ensure it is entered correctly.

[1117] The validated information is sent to the server, and the company's job information received by the server is saved in the database.

[1118] 3. Matching Process:

[1119] The server periodically reads user and company information and sentiment data from the database.

[1120] The server uses an artificial intelligence algorithm to compare the user's profile information with company job listings, and also optimizes matching candidates by taking into account the user's emotional state as recognized by an emotion engine.

[1121] The server evaluates the degree of match between each user and company, and generates high-scoring match candidates, which are temporarily stored in a database.

[1122] 4. Match Notification:

[1123] The server prepares to notify users and companies of the matching results, using the registered email addresses of users and companies or the in-application notification system.

[1124] The device receives the notification and the user and company confirm the notification content.

[1125] 5. Next steps:

[1126] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[1127] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1128] 6. Skills development support:

[1129] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[1130] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[1131] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[1132] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[1133] Specific examples

[1134] A specific example is shown below.

[1135] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[1136] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1137] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1138] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1139] Prompt Sentence Examples

[1140] Here are some example prompts for input using a generative AI model:

[1141] User A registers and enters "3 years of web development experience, knowledge of JavaScript and Python" as profile information. The emotion engine collects the user's emotional data. Company B posts a job posting with "Remote full-stack web developer wanted, required skills: JavaScript, Python." The server performs matching based on this information, and the system notifies User A and Company B of the results. Please explain the process.

[1142]

[1143] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1144] Step 1:

[1145] Accessing the Website or Application

[1146] A user visits a website or application and clicks the "Sign Up" button. Input: The URL accessed through a web browser. Output: The sign up form is displayed.

[1147] Step 2:

[1148] Enter your profile information

[1149] Users enter profile information such as their name, address, email address, phone number, skill set (e.g. JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc. Input: Data entered manually by the user. Output: Data entered into the form.

[1150] Step 3:

[1151] Collecting Emotional Data

[1152] While the user is entering their profile information, the device uses an emotion engine to recognize the user's emotional state in real time from their facial expressions and voice, and collects emotional data. Input: User's facial expressions and voice. Output: Recognized emotional data.

[1153] Step 4:

[1154] Information Validation

[1155] The device performs initial validation (format check and confirmation of required fields) on the collected profile information and emotion data to ensure they have been entered correctly. Input: Data and emotion data entered by the user. Output: Validated data.

[1156] Step 5:

[1157] Sending data

[1158] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[1159] Step 6:

[1160] Data storage

[1161] The server stores the received user profile information, desired conditions, and emotion data in a database. Input: Data sent from the device. Output: Data stored in the database.

[1162] Step 7:

[1163] Registering company job information

[1164] A company visits a website or application and clicks the "Submit a Job" button. Input: The URL accessed through a web browser. Output: The job submission form is displayed.

[1165] Step 8:

[1166] Enter job information

[1167] Companies enter detailed job information such as job type, job description, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc. Input: Data entered manually by the company. Output: Data entered into the form.

[1168] Step 9:

[1169] Information Validation

[1170] The terminal performs an initial validation of the entered information to ensure it is entered correctly. Input: Data entered by the company. Output: Validated data.

[1171] Step 10:

[1172] Sending data

[1173] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[1174] Step 11:

[1175] Data storage

[1176] The server stores the received company job information in a database. Input: Data sent from the device. Output: Data stored in the database.

[1177] Step 12:

[1178] Loading data

[1179] The server periodically reads user and company information and sentiment data from the database. Input: Information stored in the database. Output: Read data.

[1180] Step 13:

[1181] Comparing information

[1182] The server uses an artificial intelligence algorithm to compare the user's profile information with the company's job listings. Input: The data loaded. Output: The comparison result data.

[1183] Step 14:

[1184] Considering emotional data

[1185] The server also takes into account the user's emotional state recognized by the emotion engine to optimize the matching candidates. Input: Recognized emotion data. Output: Optimized matching candidates.

[1186] Step 15:

[1187] Evaluating potential matches

[1188] The server evaluates the match degree of each user and company and generates high-scoring match candidates. Input: Optimized match candidates. Output: High-scoring match candidates.

[1189] Step 16:

[1190] Saving matching results

[1191] The server temporarily stores the matching results in a database. Input: High-scoring matching candidates. Output: Matching results temporarily stored in the database.

[1192] Step 17:

[1193] Preparation for notification

[1194] The server prepares to notify users and companies of the matching results. Input: Temporarily saved matching results. Output: Notification arrangement data.

[1195] Step 18:

[1196] Sending notifications

[1197] The server sends notifications using the user's and company's registered email address or the in-application notification system. Input: Notification arrangement data. Output: Sent notification.

[1198] Step 19:

[1199] Receive notifications

[1200] The device receives notifications and allows users and businesses to confirm the notification content. Input: Sent notification. Output: Confirmed notification content.

[1201] Step 20:

[1202] Applying for an interview

[1203] The user checks the information of the matched companies, and if they are interested, they apply for an interview with the company via the application or email. Input: Confirmed notification content. Output: Interview application data.

[1204] Step 21:

[1205] Arranging interview dates

[1206] Companies will review your profile information and, if interested, schedule an interview or skill test. Input: Reviewed profile information. Output: Arranged interview date.

[1207] Step 22:

[1208] Generate a skill list

[1209] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data. Input: User profile information and market trend data. Output: Analyzed skill list.

[1210] Step 23:

[1211] Prioritizing the Skill List

[1212] The server changes the priority of the skill list based on the user's emotional state recognized by the emotion engine. Input: User's emotional data and skill list. Output: Prioritized skill list.

[1213] Step 24:

[1214] View the recommendation list

[1215] The server generates a list of recommendations for skilling and displays it on the user's personal dashboard. Input: A prioritized list of skills. Output: A list of recommendations displayed on the dashboard.

[1216] Step 25:

[1217] Skill Up Implementation

[1218] Users check the recommended skill list and learning resources (online courses, links to teaching materials, etc.) to improve their skills. Input: Recommendation list displayed on the dashboard. Output: Skill improvement execution data.

[1219] (Application example 2)

[1220] 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."

[1221] Remote work, a new form of work, is becoming more common in modern work, but there is a lack of appropriate matching and skill development support for rural residents when they access urban companies and projects. Furthermore, there is a need for matching that takes into account the emotional state of residents, rather than simply matching skills. The purpose of this invention is to solve these issues and enable rural residents to be appropriately matched with urban companies remotely, resulting in high productivity and satisfaction.

[1222] The identification process by the identification 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 a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates, a means for notifying local residents and companies of the matching candidates, a means for predicting trends for improving the skills of local residents and generating a list of required skills, a means for recognizing and recording the emotional state of local residents using an emotion engine, a means for optimally matching projects taking the emotional state into consideration, and a means for local residents to check project information in a virtual store and provide skill-up resources. This allows local residents to be optimally matched with urban companies and projects, and by considering emotional data, remote work can be realized with high productivity and satisfaction.

[1223] "Profile information" refers to personal information of local residents, including their skill sets, past work history, and desired industry and occupation.

[1224] "Skill set" refers to the collection of technical abilities and knowledge possessed by local residents, specifically programming languages ​​and specific job skills.

[1225] The "Emotion Engine" is a system that recognizes and records the user's emotional state through facial expressions and voice.

[1226] An "artificial intelligence algorithm" is a calculation method that compares input profile information with job information and generates optimal matching candidates.

[1227] "Matching candidates" are people or projects whose skills and job requirements match those of local residents and companies.

[1228] A "virtual store" refers to an online platform that operates in a virtual space, rather than a real physical store.

[1229] "Trend forecasting" is the process of analyzing and predicting current market trends and future skill demands.

[1230] The "database" is a system that stores and manages input information and emotional data from local residents and businesses.

[1231] "Notification" refers to the act of informing local residents and businesses of matching results and other important information.

[1232] "Skill-up resources" refers to learning materials, online courses, and related information that rural residents can use to improve their skills.

[1233] The system that realizes this invention allows residents of rural areas to remotely access companies and projects in urban areas and receive appropriate matching and skill development support. The program processing of this system will be explained in detail below.

[1234] Program generation and processing content

[1235] New user registration

[1236] Device: The user registers using a smartphone or head-mounted display, entering profile information such as name, address, skill set, past work experience, and desired industry and job type.

[1237] Emotion engine: When inputting, the emotion engine recognizes and records the user's emotional state through facial expressions and voice. This emotional data is also sent to the server. Specific software used is "Affectiva Emotion AI" and "Microsoft Azure Cognitive Services."

[1238] Server: Profile information and emotion data are stored in a database using MySQL or Google Firebase.

[1239] Registering company project information

[1240] Companies: Register project information through the virtual store's website or app, including job title, job description, required skill set, salary, etc.

[1241] Terminal: Performs initial validation of registered information and sends it to the server.

[1242] Server: Stores the company's project information in a database.

[1243] Matching Process

[1244] Server: Using an artificial intelligence (AI) algorithm, it compares profile information with company project information. It generates optimal matching candidates by taking into account the user's emotional state as recognized by the emotion engine. Specifically, it uses "TensorFlow" and "PyTorch."

[1245] Server: Notifies local residents and businesses of potential matches via email or in-app notifications.

[1246] Skills improvement support

[1247] Server: Based on user profile information and sentiment data, predicts skills that will be in demand in the future, and generates skill development lists and learning resources that users can view in a virtual store.

[1248] Users: Check out the recommended skill list and learning resources (e.g., online courses) to improve their skills.

[1249] Specific examples

[1250] User A uses a smartphone to register information such as "3 years of web development experience, Python" and records a self-introduction along with a happy expression. Company B registers "Remote web development project, required skills: Python." The server then combines the emotion data and skill information to perform matching and notifies User A and Company B.

[1251] Prompt Sentence Examples

[1252] User A (smartphone):

[1253] New Registration

[1254] Name: Tanaka

[1255] Experience: 3 years of web development experience, Python

[1256] Desired job type: Remote work

[1257] Desired industry: IT

[1258] Expression: Joy

[1259] Company B (virtual store app):

[1260] New project information registration

[1261] Job Title: Web Development

[1262] Required skills: Python

[1263] Salary: 3,000 yen per hour

[1264] This system allows local residents to be matched with the most suitable projects taking into account their emotional state, enabling them to achieve high productivity and satisfaction through remote work.

[1265] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1266] Step 1:

[1267] New user registration

[1268] Input: The user uses a smartphone or head-mounted display to enter profile information (name, address, skill set, past work experience, desired industry and job type, etc.) on the new registration screen.

[1269] Processing: During input, an emotion engine (e.g., Affectiva Emotion AI or Microsoft Azure Cognitive Services) recognizes and records the user's emotional state through facial expressions and voice in real time. This data is sent from the device to a server.

[1270] Output: Profile information and emotion data are stored on the server.

[1271] Step 2:

[1272] Registering company project information

[1273] Input: Companies use the virtual store's website or application to register project information (job type, job description, required skill set, salary, working hours, etc.).

[1274] Processing: During registration, the device performs initial validation of the data (format checks, required fields checks) and sends the validated information to the server.

[1275] Output: Project information is saved to the server database.

[1276] Step 3:

[1277] Matching Process

[1278] Input: The server periodically retrieves user profile information, emotion data, and company project information from the database.

[1279] Processing: The server uses artificial intelligence (AI) algorithms (e.g., TensorFlow or PyTorch) to compare the user's profile information with the company's project information, and generates optimal matching candidates taking into account the user's emotional state as recognized by the emotion engine.

[1280] Output: A list of potential matches is generated and temporarily stored on the server.

[1281] Step 4:

[1282] Notification of matching results

[1283] Input: The server retrieves a list of potential matches and prepares to notify local residents and businesses.

[1284] Processing: The server selects a notification method (email or in-app notification) and sends the matching results, including details about the project and next steps.

[1285] Output: Local residents and businesses receive and review the notification.

[1286] Step 5:

[1287] Skills improvement support

[1288] Input: The server periodically retrieves user profile information and sentiment data, as well as market trend data.

[1289] Processing: The server uses trend prediction algorithms to analyze skills that are likely to be in demand in the future, creates a prioritized skill list based on sentiment data, and generates learning resources (online courses and learning links).

[1290] Output: Skilling resources are displayed on a dashboard for local residents.

[1291] Step 6:

[1292] Project Initiation Procedures

[1293] Input: Local residents receive notifications and begin the application process for projects they're interested in. Companies similarly schedule interviews and skill tests for interested users.

[1294] Processing: The terminal provides an interface for application procedures and interview arrangements, and sends that information to the server.

[1295] Output: The project officially begins, with users and companies collaborating through remote work.

[1296] In this way, each step is carried out in a sequential manner, enabling quick and effective matching between users and companies. Furthermore, ongoing support for skill development improves users' productivity and satisfaction with remote work.

[1297] 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.

[1298] 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.

[1299] 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.

[1300] [Third embodiment]

[1301] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1302] 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.

[1303] 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).

[1304] 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.

[1305] 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.

[1306] 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).

[1307] 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. 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.

[1308] 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.

[1309] 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.

[1310] 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.

[1311] 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.

[1312] 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."

[1313] The present invention is a system that allows local residents to work remotely from urban areas. The program processing of this system will be explained below in natural language.

[1314] Program processing description

[1315] New user registration

[1316] User

[1317] Visit the website or application and click the "Sign Up" button.

[1318] Enter your profile information, such as your name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[1319] Terminal

[1320] Perform initial validation of the entered information (checking format and required fields) to confirm that it has been entered correctly.

[1321] Send the validated information to the server.

[1322] server

[1323] The received user profile information and desired conditions are stored in a database.

[1324] Registering company job information

[1325] company

[1326] Visit the website or application and click on the "Subscribe to a Job" button.

[1327] Enter the details of the job offer, such as the job type, job content, required skill set, salary, work location, and working style.

[1328] Terminal

[1329] Perform initial validation of entered information.

[1330] Send the validated information to the server.

[1331] server

[1332] The received company job information is saved in a database.

[1333] Matching Process

[1334] server

[1335] Periodically read user and company information from the database.

[1336] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[1337] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[1338] The matching results are temporarily stored in a database.

[1339] Matching notification

[1340] server

[1341] Prepare to notify users and companies of the matching results.

[1342] Notifications are sent via user and company registered email addresses and in-app notification systems.

[1343] Terminal

[1344] Users and businesses receive notifications and review the content of the notifications.

[1345] Next steps

[1346] User

[1347] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[1348] company

[1349] Check the user's profile information and, if interested, schedule an interview or skills test.

[1350] Skills improvement support

[1351] server

[1352] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[1353] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[1354] User

[1355] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[1356] Specific examples

[1357] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[1358] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1359] The server stores the information of User A and Company B in a database and matches them using an artificial intelligence algorithm.

[1360] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1361] This system will enable rural residents to acquire skills needed in urban areas, while achieving high productivity and a good work-life balance, thereby helping to revitalize Japan as a whole.

[1362] The processing flow will be explained below.

[1363] Step 1:

[1364] A user visits a website or application and clicks the "Sign Up" button.

[1365] Step 2:

[1366] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[1367] Step 3:

[1368] The terminal performs initial validation of the information entered (checking the format and checking for required fields) to ensure that it has been entered correctly.

[1369] Step 4:

[1370] The terminal sends the information that the validation has been completed to the server.

[1371] Step 5:

[1372] The server stores the received user profile information and desired conditions in a database.

[1373] Step 6:

[1374] A company visits their website or application and clicks the "Register a Job" button.

[1375] Step 7:

[1376] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[1377] Step 8:

[1378] The terminal performs an initial validation of the entered information.

[1379] Step 9:

[1380] The terminal sends the information that the validation has been completed to the server.

[1381] Step 10:

[1382] The server stores the received company job information in a database.

[1383] Step 11:

[1384] The server periodically reads user and company information from the database.

[1385] Step 12:

[1386] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[1387] Step 13:

[1388] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[1389] Step 14:

[1390] The server temporarily stores the matching results in a database.

[1391] Step 15:

[1392] The server prepares to notify the user and the company of the matching results.

[1393] Step 16:

[1394] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[1395] Step 17:

[1396] The device receives a notification to the user and the company, and the notification content is confirmed.

[1397] Step 18:

[1398] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[1399] Step 19:

[1400] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1401] Step 20:

[1402] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[1403] Step 20:

[1404] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[1405] Step 21:

[1406] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[1407] Example 1

[1408] 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."

[1409] To make it easier for rural residents to access jobs in urban areas, it is necessary to bridge the information gap between rural and urban areas. The current recruitment system makes it difficult for rural residents to find suitable jobs, and for companies to efficiently recruit talented personnel from remote areas. Furthermore, there are no established methods for rural residents to properly learn and acquire the skills required in urban areas, resulting in a skills gap. A comprehensive system to resolve these issues is needed.

[1410] 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.

[1411] In this invention, the server includes: a means for rural residents to input their profile information and skill set; a means for companies to register job information; a means for initially validating the input information; a means for transmitting validated information to the server; a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates; a means for notifying the matching candidates to rural residents and companies; and a means for predicting trends for improving the skills of rural residents and generating a list of required skills. This makes it easier for rural residents to access jobs in urban areas and enables companies to efficiently recruit talented people from remote locations. Furthermore, since rural residents can appropriately learn and acquire skills required in urban areas, the skills gap can be eliminated.

[1412] "Rural residents" refers to individuals who reside in areas away from urban areas.

[1413] "Profile information" refers to personal information such as the user's name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[1414] "Skill set" refers to the skills, knowledge, and specialized abilities possessed by a user.

[1415] "Company" refers to the legal entity that registers job information.

[1416] "Job information" refers to information such as the type of job offered by a company, specific job content, required skill set, salary, work location, and working style.

[1417] "Initial validation" refers to the process of verifying that the information entered is formally correct and that all required fields are filled in.

[1418] "Server" refers to a high performance computer system that processes and stores data.

[1419] "Artificial intelligence algorithm" refers to a calculation method that analyzes user profile information and company job information to generate optimal matching candidates.

[1420] "Matching candidates" refer to the combination that is evaluated as optimal after comparing user and company information.

[1421] "Notification" refers to the act of informing users and businesses of matching results and other important information.

[1422] "Trend forecasting" refers to the process of analyzing market demand and future trends and predicting future trends based on the results.

[1423] The "Skills Needed List" is a list of recommendations for rural residents to acquire skills that will be in demand in the future.

[1424] The present invention is a comprehensive system that enables rural residents to remotely access urban jobs and develop appropriate skills. The system is configured as follows.

[1425] System Configuration

[1426] The system includes multiple components that work together: a user device, a company device, and a server, which contains a database that stores relevant data and an artificial intelligence (AI) model that runs the matching algorithm.

[1427] Program processing overview

[1428] The main processing flow of the system will be specifically explained below.

[1429] New user registration

[1430] Users access the website or application using their own device and click the "New Registration" button. They then enter their profile information, such as their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[1431] The terminal performs initial validation of the information entered by the user in real time, for example, checking that the email address is formatted correctly and that all required fields are filled in. If validation passes, the information is sent to the server.

[1432] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[1433] Registering company job information

[1434] Companies access the website or application using their own devices, click the "Register Job Information" button, and enter details of the job, such as job type, job description, required skill set, salary, work location, and working style.

[1435] The terminal performs an initial validation of the information entered by the company in real time, for example, ensuring that the salary range is appropriate and the required skill set is specifically described, and if validation passes, it sends this information to the server.

[1436] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[1437] Matching Process

[1438] The server periodically reads user and company information from the database. It uses a generative AI model to compare the user's profile information with the company's job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[1439] Matching notification

[1440] The server prepares to notify users and businesses of the matching results. Notifications are sent to the users' and businesses' registered email addresses or via the notification system within the application.

[1441] The terminal displays the notification received by the user and the company, who then checks the notification content and takes the next action.

[1442] Skills improvement support

[1443] The server analyzes the skills that are expected to be in demand in the future based on the user's profile information and market trend data, and uses a generative AI model to generate a list of recommendations for skill development, which are displayed on the user's dedicated dashboard.

[1444] Users can check the recommended skill list and learning resources to improve their skills, which will support their ability development.

[1445] Specific examples

[1446] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[1447] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1448] The server stores the information of User A and Company B in a database and performs matching using a generative AI model.

[1449] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1450] Prompt Sentence Examples

[1451] Below are some examples of prompts to input to the generative AI model.

[1452] "Please explain the user registration process for the remote work support system in natural language."

[1453] "Please explain in natural language the process a company goes through to register a job posting."

[1454] "Please explain in natural language the process of matching users and companies."

[1455] "Please explain in natural language the process of notifying matching results."

[1456] "Please explain in natural language the process of supporting skill development in a remote work support system."

[1457] The above is an embodiment of the present invention. This will make it easier for rural residents to access jobs in urban areas, and will enable companies to efficiently recruit talented people in remote areas. It will also enable rural residents to appropriately study and acquire the skills required in urban areas, thereby eliminating the skills gap.

[1458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1459] New user registration

[1460] Step 1:

[1461] The user accesses the website or application using their own device and clicks the "New Registration" button. A profile entry screen appears, and the user enters their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[1462] Input: User's personal information and preferences.

[1463] Output: Profile information entered into the terminal.

[1464] Step 2:

[1465] The terminal performs initial validation of the information entered by the user in real time, for example, ensuring that the email address is formatted correctly and that all required fields are filled in.

[1466] Input: The profile information entered in step 1.

[1467] Data processing: Check email address format and confirm required fields.

[1468] Output: Profile information that passes validation.

[1469] Step 3:

[1470] The terminal transmits the profile information that has passed validation to the server.

[1471] Input: Profile information that passes initial validation.

[1472] Output: The profile information sent to the server.

[1473] Step 4:

[1474] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[1475] Input: Profile information sent from the device.

[1476] Data processing: storing information in a database.

[1477] Output: Profile information stored in a database.

[1478] Registering company job information

[1479] Step 1:

[1480] Companies access the website or application using their own devices and click the "Register Job Information" button. A job information entry screen will appear, where companies can enter details such as job type, job content, required skill set, salary, work location, and working style.

[1481] Input: Job details (job type, job description, required skill set, salary, work location, working style, etc.).

[1482] Output: The job information entered into the terminal.

[1483] Step 2:

[1484] The terminal performs initial validation of the information entered by the company in real time, for example, to check the appropriateness of the salary and the specificity of the required skill set.

[1485] Input: The job information entered in step 1.

[1486] Data processing: Checking the validity of salaries and confirming the specificity of skill sets.

[1487] Output: A job that passes validation.

[1488] Step 3:

[1489] The terminal transmits the job information that has passed validation to the server.

[1490] Input: A job that passes initial validation.

[1491] Output: The job listing sent to the server.

[1492] Step 4:

[1493] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[1494] Input: Job posting submitted from device.

[1495] Data processing: storing information in a database.

[1496] Output: Job information stored in the database.

[1497] Matching Process

[1498] Step 1:

[1499] The server periodically reads user and company information from the database, a process that is performed automatically by a scheduled job.

[1500] Input: User and company information in the database.

[1501] Output: The imported user and company information.

[1502] Step 2:

[1503] The server uses a generative AI model to compare user profile information with company job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[1504] Input: User and company information imported in step 1.

[1505] Data processing: Analyzing information with a generative AI model and calculating matching scores.

[1506] Output: Match score and candidate matches.

[1507] Step 3:

[1508] The server generates the best matching candidates based on the obtained matching scores and stores them in a temporary database.

[1509] Input: Matching score and match candidates.

[1510] Data processing: storing information in a temporary database.

[1511] Output: Match candidates stored in a temporary database.

[1512] Matching notification

[1513] Step 1:

[1514] The server prepares the email addresses registered by the user and the company and the in-application notification system, generates notification content according to templates, and adds it to the queue for sending.

[1515] Input: Match candidates stored in a temporary database.

[1516] Data processing: Creating notification content and queuing it for sending.

[1517] Output: The notification content queued for sending.

[1518] Step 2:

[1519] The server sends notifications as they become ready, using an SMTP server for email notifications and calling the corresponding notification API for in-app notifications.

[1520] Input: The notification content that has been queued for sending.

[1521] Data processing: Sending notifications using an SMTP server or notification API.

[1522] Output: Notifications sent to users and businesses.

[1523] Step 3:

[1524] The device displays the notifications received by the user and the company, and the user and the company check the notification content and consider the next action.

[1525] Input: Notifications sent to users and businesses.

[1526] Output: The notification content that will be displayed on your device.

[1527] Next steps

[1528] Step 1:

[1529] Users can check the information of the matched companies, and if they are interested, they can apply for an interview with the company via the application's functions or email.

[1530] Input: Notification details and matched company information.

[1531] Output: Interview request submitted.

[1532] Step 2:

[1533] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1534] Input: Notification content and matched user information.

[1535] Output: Scheduling interviews and skills tests.

[1536] Skills improvement support

[1537] Step 1:

[1538] The server analyzes the skills that are likely to be in demand in the future based on user profile information and market trend data, using a generative AI model for this analysis.

[1539] Input: User profile information and market trend data.

[1540] Data processing: Analyzing skill demand with generative AI models.

[1541] Output: A list of skills that are expected to be in demand.

[1542] Step 2:

[1543] Based on the analysis results, the server generates a list of recommended skills for the user and displays it on the user's dashboard.

[1544] Input: A list of skills that are expected to be in demand.

[1545] Data processing: Generating a list of recommended skills for improvement.

[1546] Output: A list of recommended skills to be improved, displayed on the user's dashboard.

[1547] Step 3:

[1548] Users can review a list of recommended skills and learning resources to improve their skills, such as taking online courses or using designated study materials.

[1549] Input: A list of recommended skills displayed on the user's dashboard.

[1550] Output: Actions to improve skills (taking courses and using learning materials).

[1551] (Application example 1)

[1552] 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."

[1553] Sales activities for sales representatives and freelancers living in rural areas face the challenge of limited means of accessing corporate projects in urban areas and across the country, and limited means of efficiently managing those projects, which requires a great deal of effort and time. Matching with suitable projects is also difficult, and an efficient system is needed to enable sales representatives living in rural areas to smoothly conduct transactions with urban companies. Furthermore, there is a lack of appropriate information sources to help rural residents improve their skills.

[1554] 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.

[1555] In this invention, the server includes: a means for local residents to input their own profile information and skill set; a means for companies to register job information and project information; a means for using an artificial intelligence algorithm to compare the profile information with the company's job information and project information to generate matching candidates; a means for notifying local residents and companies of the matching candidates; a means for predicting trends for improving the skills of local residents and generating a list of necessary skills and learning resources; and a means for displaying the trend predictions and skill list on a dashboard. This allows local residents to efficiently access corporate projects and centrally manage the progress and compensation status of projects. It also provides appropriate information for skill improvement.

[1556] "Rural residents" refers to individuals who reside in rural areas and are physically separated from urban and other areas.

[1557] "Profile information" is a general term for information that indicates an individual's characteristics, such as name, address, skill set, years of experience, and work history.

[1558] A "skill set" refers to the collection of skills and knowledge that an individual possesses, and is a list of the abilities required to perform a specific job.

[1559] "Company" refers to a legal entity that provides products or services.

[1560] "Job information" is information published by a company about the requirements and conditions for jobs and positions that the company is seeking.

[1561] "Project Information" refers to the job description provided by a company, including detailed information about a specific project or job.

[1562] An "artificial intelligence algorithm" is a computational method for analyzing data and finding patterns and relationships, and uses machine learning and natural language processing to process information.

[1563] "Matching candidates" refer to proposals for highly compatible combinations based on information about the user and the company.

[1564] "Notification" means the act of communicating specific information to a designated recipient, whether via email or an in-application notification system.

[1565] "Trend forecasting" refers to the act of analyzing and predicting the skills and market trends that will be required from the present to the future.

[1566] A "skills list" is a list of skills required for a specific job or task.

[1567] "Learning resources" refers to educational materials such as textbooks and online courses that can be used to improve skills.

[1568] A "dashboard" refers to a visual interface that allows users to understand information at a glance.

[1569] "Progress management" refers to the act of managing and tracking the progress of a case or project.

[1570] "Remuneration status" refers to the act of managing the status of compensation paid for completed work or projects.

[1571] This invention is a system for supporting the sales activities of sales representatives and freelancers living in rural areas, specifically, allowing rural residents to access corporate projects in urban areas and across the country and efficiently check the progress management and compensation status of projects. An embodiment of this system is described below.

[1572] System program configuration

[1573] The system mainly consists of a server, user terminals, and enterprise terminals, and uses artificial intelligence algorithms (e.g., SciKit Learn), databases (e.g., PostgreSQL), and web servers (e.g., the Django framework) as necessary technical components.

[1574] Processing flow

[1575] 1. New user registration

[1576] The user enters their profile information and skill set.

[1577] Initial validation is performed on the terminal side and sent to the server.

[1578] The server stores the received information in a database and notifies the user that registration is complete.

[1579] 2. Registering company job information and project information

[1580] Companies enter detailed job and project information.

[1581] Initial validation is performed on the terminal side and sent to the server.

[1582] The server stores the received information in a database and notifies the company that registration is complete.

[1583] 3. Matching by AI algorithm

[1584] The server periodically reads user and company information from the database and performs a comparison.

[1585] An artificial intelligence algorithm is used to evaluate the degree of matching and generate high-scoring candidates.

[1586] The matching results are temporarily stored in a database and prepared for notification.

[1587] 4. Notification and Control

[1588] The server notifies users and companies of the matching results via email or in-app notifications.

[1589] Users can check the progress and compensation status of selected projects on a dashboard.

[1590] 5. Skills improvement support

[1591] The server analyzes market trend data and generates a list of skills and learning resources required by the user.

[1592] This is displayed on a user-specific dashboard to support self-improvement.

[1593] Specific examples

[1594] For example, suppose sales representative A, who lives in a rural area, registers and enters "3 years of B2B sales experience, online sales skills." Company B registers project information such as "online sales of a new product, required skills: B2B sales, use of web conferencing tools." The server stores the information of User A and Company B in a database, performs matching using an artificial intelligence algorithm, and generates high-scoring match candidates. The server notifies User A and Company B of the results, and User A accepts the project, thereby beginning remote sales activities. Progress management and compensation status can be checked on User A's dashboard. The server also analyzes market trends and provides resources to recommend that User A learn additional "online marketing skills."

[1595] Prompt Sentence Examples

[1596] Here are some example prompts for the generative AI model used in the job matching algorithm:

[1597] Sales Representative Profile:

[1598] Skill Set: {skill_set}

[1599] Years of experience: {years_of_experience}

[1600] Previous work experience: {job_history}

[1601] Company Project Information:

[1602] Job type: {job_type}

[1603] Job Description: {job_description}

[1604] Required Skill Set: {required_skills}

[1605] Reward: {salary}

[1606] Employment type: {employment_type}

[1607] Use the information above to match you with the most suitable sales representative.

[1608] In this way, a system can be realized that allows people living in rural areas to efficiently access corporate projects in urban areas and across the country, and to accept and proceed with appropriate projects.

[1609] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1610] Step 1:

[1611] The user enters their profile information and skill set to register as a new user. Specifically, the user accesses the application and enters information such as name, address, skill set, years of experience, and work history. Once this input is complete, the terminal validates this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the user that registration is complete.

[1612] Step 2:

[1613] Companies enter and register job information and project information. Specifically, companies log in to the application and enter detailed information such as job type, job content, required skill set, salary, work location, and working style. Once this input is complete, the terminal performs an initial validation of this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the company that registration is complete.

[1614] Step 3:

[1615] The server periodically reads user and company information from the database and runs a matching algorithm. Specifically, the server uses Python and SciKit Learn to compare user profile information with company job postings and job opportunities, scoring the degree of match. Based on the generated scores, high-scoring match candidates are generated and temporarily stored in the database. The algorithm uses machine learning models to find the best match, taking into account past matching data and trends.

[1616] Step 4:

[1617] The server notifies users and companies of high-scoring match candidates. Specifically, in preparation for the notification, the server dynamically generates the generated match candidate data and inserts it into email templates and in-application notification messages. The server uses Python's Django framework to construct the notification message and sends it to users and companies. Users and companies can then check the received notification and confirm detailed information about the match candidates.

[1618] Step 5:

[1619] Users manage the order process for projects and check progress and compensation status. Specifically, based on the project information received by users, they can check the progress and compensation status of projects on the dashboard within the application. The server links the project information with the user's progress data and continuously updates it.

[1620] Step 6:

[1621] The server analyzes market trend data and provides users with information to improve their skills. Specifically, it analyzes the received market trend data and identifies skills and knowledge that will be in high demand in the future. It uses Python to analyze the data and generates a list of skills and learning resources specifically for each user. This information is displayed on the user's dashboard and provided as reference for self-improvement.

[1622] Through these steps, we have created a system that allows sales representatives and freelancers living in rural areas to efficiently manage projects and improve their skills.

[1623] 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.

[1624] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. Below, the program processing of this system is explained in natural language.

[1625] Program processing description

[1626] New user registration

[1627] User

[1628] Visit the website or application and click the "Sign Up" button.

[1629] Enter your profile information, such as your name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[1630] The emotion engine recognizes and records the user's emotional state through facial expressions and voice input.

[1631] Terminal

[1632] Perform initial validation (format check and check for required fields) on the entered information and emotional data to ensure they are entered correctly.

[1633] Send the validated information to the server.

[1634] server

[1635] The received user profile information, desired conditions, and emotional data are stored in a database.

[1636] Registering company job information

[1637] company

[1638] Visit the website or application and click on the "Subscribe to a Job" button.

[1639] Enter the details of the job offer, such as the job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc.

[1640] Terminal

[1641] Perform initial validation of entered information.

[1642] Send the validated information to the server.

[1643] server

[1644] The received company job information is saved in a database.

[1645] Matching Process

[1646] server

[1647] User and company information and user sentiment data are periodically read from the database.

[1648] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[1649] The emotional state of the user recognized by the emotion engine is also taken into consideration to optimize matching candidates.

[1650] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[1651] The matching results are temporarily stored in a database.

[1652] Matching notification

[1653] server

[1654] Prepare to notify users and companies of the matching results.

[1655] Notifications are sent via user and company registered email addresses and in-app notification systems.

[1656] Terminal

[1657] Users and businesses receive notifications and review the content of the notifications.

[1658] Next steps

[1659] User

[1660] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[1661] company

[1662] Check the user's profile information and, if interested, schedule an interview or skills test.

[1663] Skills improvement support

[1664] server

[1665] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[1666] The skill list is prioritized based on the user's emotional state as recognized by the emotion engine.

[1667] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[1668] User

[1669] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[1670] Specific examples

[1671] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[1672] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1673] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1674] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1675] This system allows rural residents to acquire the skills required in urban areas, while also taking emotional data into account to achieve optimal matching, thereby achieving high productivity and a rich work-life balance.

[1676] The processing flow will be explained below.

[1677] Step 1:

[1678] A user visits a website or application and clicks the "Sign Up" button.

[1679] Step 2:

[1680] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[1681] Step 3:

[1682] The device activates an emotion engine to recognize and record the user's emotional state through facial expressions and voice input.

[1683] Step 4:

[1684] The device performs initial validation (format checks and checks for required fields) of the entered information and emotional data to confirm that it has been entered correctly.

[1685] Step 5:

[1686] The terminal sends the information that the validation has been completed to the server.

[1687] Step 6:

[1688] The server stores the received user profile information, desired conditions, and emotional data in a database.

[1689] Step 7:

[1690] A company visits their website or application and clicks the "Register a Job" button.

[1691] Step 8:

[1692] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[1693] Step 9:

[1694] The terminal performs an initial validation of the entered information.

[1695] Step 10:

[1696] The terminal sends the information that the validation has been completed to the server.

[1697] Step 11:

[1698] The server stores the received company job information in a database.

[1699] Step 12:

[1700] The server periodically reads user and company information and user emotion data from the database.

[1701] Step 13:

[1702] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[1703] Step 14:

[1704] The server also takes into consideration the emotional state of the user recognized by the emotion engine and optimizes the matching candidates.

[1705] Step 15:

[1706] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[1707] Step 16:

[1708] The server temporarily stores the matching results in a database.

[1709] Step 17:

[1710] The server prepares to notify users and companies of the matching results.

[1711] Step 18:

[1712] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[1713] Step 19:

[1714] The device receives a notification to the user and the company, and the notification content is confirmed.

[1715] Step 20:

[1716] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[1717] Step 21:

[1718] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1719] Step 22:

[1720] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[1721] Step 23:

[1722] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[1723] Step 24:

[1724] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[1725] Step 25:

[1726] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[1727] Specific examples

[1728] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent to the server.

[1729] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1730] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1731] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1732] Example 2

[1733] 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."

[1734] When rural residents perform remote work for urban jobs, there are problems such as inappropriate matching and incompatible matches due to a lack of consideration of emotional states. Furthermore, there is a lack of effective support for rural residents to improve their skills, making it difficult for them to improve their competitiveness in the market.

[1735] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for recognizing the emotional state of residents using an emotion engine, a means for comparing the profile information, the emotional state, and the job information of the companies using an artificial intelligence algorithm to generate matching candidates, a means for notifying local residents and companies of the matching candidates, and a means for predicting trends for improving the skills of local residents and generating a list of required skills. This enables local residents to perform appropriate matching taking into account their emotional state and to effectively improve their skills.

[1736] "Rural residents" refers to individuals who reside in areas other than urban areas.

[1737] "Profile information" refers to personal information such as a user's name, address, email address, telephone number, skill set, years of experience, work history, desired work style, and desired industry and job type.

[1738] A "skill set" refers to a collection of specific skills and knowledge that a user possesses, and examples include programming languages ​​(JavaScript, Python, etc.).

[1739] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state through facial expressions and voice.

[1740] "Artificial intelligence algorithm" refers to the calculation procedures and models used to compare profile information with company job listings and generate optimal matching candidates.

[1741] "Matching candidates" refer to optimal combinations of users and companies generated based on profile information and company recruitment information.

[1742] "Database" refers to a structured collection of information within a computer system for storing profile information, job listings, emotional data, etc.

[1743] "Trend forecasting" refers to a method of analyzing market trends and predicting skills that are likely to be in high demand in the future.

[1744] A "skill list" refers to a list of skills and knowledge that local residents should learn to improve their skills.

[1745] "Notification" means information or communication sent to a user or business via email or within an application.

[1746] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. This system consists of the following elements.

[1747] 1. Register a new user:

[1748] A user accesses a website or application, clicks the "Sign Up" button, and then enters profile information such as their name, address, email address, phone number, skill set (e.g., JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), and desired industry and job type.

[1749] The emotion engine recognizes the user's emotional state in real time through facial expressions and voice input, and collects emotional data.

[1750] The device performs initial validation (format check and confirmation of required fields) on the information and emotion data collected to confirm that it has been entered correctly. After that, the validated information is sent to the server.

[1751] The server stores the received user profile information, desired conditions, and emotional data in a database.

[1752] 2. Company job postings:

[1753] Companies access their website or application, click the "Submit Job Information" button, and then enter details about the job, such as job type, job description, required skill set (e.g., JavaScript, Python), salary, work location, and working style.

[1754] The terminal performs an initial validation of the entered information to ensure it is entered correctly.

[1755] The validated information is sent to the server, and the company's job information received by the server is saved in the database.

[1756] 3. Matching Process:

[1757] The server periodically reads user and company information and sentiment data from the database.

[1758] The server uses an artificial intelligence algorithm to compare the user's profile information with company job listings, and also optimizes matching candidates by taking into account the user's emotional state as recognized by an emotion engine.

[1759] The server evaluates the degree of match between each user and company, and generates high-scoring match candidates, which are temporarily stored in a database.

[1760] 4. Match Notification:

[1761] The server prepares to notify users and companies of the matching results, using the registered email addresses of users and companies or the in-application notification system.

[1762] The device receives the notification and the user and company confirm the notification content.

[1763] 5. Next steps:

[1764] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[1765] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[1766] 6. Skills development support:

[1767] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[1768] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[1769] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[1770] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[1771] Specific examples

[1772] A specific example is shown below.

[1773] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[1774] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1775] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[1776] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[1777] Prompt Sentence Examples

[1778] Here are some example prompts for input using a generative AI model:

[1779] User A registers and enters "3 years of web development experience, knowledge of JavaScript and Python" as profile information. The emotion engine collects the user's emotional data. Company B posts a job posting with "Remote full-stack web developer wanted, required skills: JavaScript, Python." The server performs matching based on this information, and the system notifies User A and Company B of the results. Please explain the process.

[1780]

[1781] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1782] Step 1:

[1783] Accessing the Website or Application

[1784] A user visits a website or application and clicks the "Sign Up" button. Input: The URL accessed through a web browser. Output: The sign up form is displayed.

[1785] Step 2:

[1786] Enter your profile information

[1787] Users enter profile information such as their name, address, email address, phone number, skill set (e.g. JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc. Input: Data entered manually by the user. Output: Data entered into the form.

[1788] Step 3:

[1789] Collecting Emotional Data

[1790] While the user is entering their profile information, the device uses an emotion engine to recognize the user's emotional state in real time from their facial expressions and voice, and collects emotional data. Input: User's facial expressions and voice. Output: Recognized emotional data.

[1791] Step 4:

[1792] Information Validation

[1793] The device performs initial validation (format check and confirmation of required fields) on the collected profile information and emotion data to ensure they have been entered correctly. Input: Data and emotion data entered by the user. Output: Validated data.

[1794] Step 5:

[1795] Sending data

[1796] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[1797] Step 6:

[1798] Data storage

[1799] The server stores the received user profile information, desired conditions, and emotion data in a database. Input: Data sent from the device. Output: Data stored in the database.

[1800] Step 7:

[1801] Registering company job information

[1802] A company visits a website or application and clicks the "Submit a Job" button. Input: The URL accessed through a web browser. Output: The job submission form is displayed.

[1803] Step 8:

[1804] Enter job information

[1805] Companies enter detailed job information such as job type, job description, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc. Input: Data entered manually by the company. Output: Data entered into the form.

[1806] Step 9:

[1807] Information Validation

[1808] The terminal performs an initial validation of the entered information to ensure it is entered correctly. Input: Data entered by the company. Output: Validated data.

[1809] Step 10:

[1810] Sending data

[1811] The terminal sends the information that validation has been completed to the server. Input: Validated data. Output: Data transmission to the server is complete.

[1812] Step 11:

[1813] Data storage

[1814] The server stores the received company job information in a database. Input: Data sent from the device. Output: Data stored in the database.

[1815] Step 12:

[1816] Loading data

[1817] The server periodically reads user and company information and sentiment data from the database. Input: Information stored in the database. Output: Read data.

[1818] Step 13:

[1819] Comparing information

[1820] The server uses an artificial intelligence algorithm to compare the user's profile information with the company's job listings. Input: The data loaded. Output: The comparison result data.

[1821] Step 14:

[1822] Considering emotional data

[1823] The server also takes into account the user's emotional state recognized by the emotion engine to optimize the matching candidates. Input: Recognized emotion data. Output: Optimized matching candidates.

[1824] Step 15:

[1825] Evaluating potential matches

[1826] The server evaluates the match degree of each user and company and generates high-scoring match candidates. Input: Optimized match candidates. Output: High-scoring match candidates.

[1827] Step 16:

[1828] Saving matching results

[1829] The server temporarily stores the matching results in a database. Input: High-scoring matching candidates. Output: Matching results temporarily stored in the database.

[1830] Step 17:

[1831] Preparation for notification

[1832] The server prepares to notify users and companies of the matching results. Input: Temporarily saved matching results. Output: Notification arrangement data.

[1833] Step 18:

[1834] Sending notifications

[1835] The server sends notifications using the user's and company's registered email address or the in-application notification system. Input: Notification arrangement data. Output: Sent notification.

[1836] Step 19:

[1837] Receive notifications

[1838] The device receives notifications and allows users and businesses to confirm the notification content. Input: Sent notification. Output: Confirmed notification content.

[1839] Step 20:

[1840] Applying for an interview

[1841] The user checks the information of the matched companies, and if they are interested, they apply for an interview with the company via the application or email. Input: Confirmed notification content. Output: Interview application data.

[1842] Step 21:

[1843] Arranging interview dates

[1844] Companies will review your profile information and, if interested, schedule an interview or skill test. Input: Reviewed profile information. Output: Arranged interview date.

[1845] Step 22:

[1846] Generate a skill list

[1847] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data. Input: User profile information and market trend data. Output: Analyzed skill list.

[1848] Step 23:

[1849] Prioritizing the Skill List

[1850] The server changes the priority of the skill list based on the user's emotional state recognized by the emotion engine. Input: User's emotional data and skill list. Output: Prioritized skill list.

[1851] Step 24:

[1852] View the recommendation list

[1853] The server generates a list of recommendations for skilling and displays it on the user's personal dashboard. Input: A prioritized list of skills. Output: A list of recommendations displayed on the dashboard.

[1854] Step 25:

[1855] Skill Up Implementation

[1856] Users check the recommended skill list and learning resources (online courses, links to teaching materials, etc.) to improve their skills. Input: Recommendation list displayed on the dashboard. Output: Skill improvement execution data.

[1857] (Application example 2)

[1858] 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."

[1859] Remote work, a new form of work, is becoming more common in modern work, but there is a lack of appropriate matching and skill development support for rural residents when they access urban companies and projects. Furthermore, there is a need for matching that takes into account the emotional state of residents, rather than simply matching skills. The purpose of this invention is to solve these issues and enable rural residents to be appropriately matched with urban companies remotely, resulting in high productivity and satisfaction.

[1860] The identification process by the identification 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 a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates, a means for notifying local residents and companies of the matching candidates, a means for predicting trends for improving the skills of local residents and generating a list of required skills, a means for recognizing and recording the emotional state of local residents using an emotion engine, a means for optimally matching projects taking the emotional state into consideration, and a means for local residents to check project information in a virtual store and provide skill-up resources. This allows local residents to be optimally matched with urban companies and projects, and by considering emotional data, remote work can be realized with high productivity and satisfaction.

[1861] "Profile information" refers to personal information of local residents, including their skill sets, past work history, and desired industry and occupation.

[1862] "Skill set" refers to the collection of technical abilities and knowledge possessed by local residents, specifically programming languages ​​and specific job skills.

[1863] The "Emotion Engine" is a system that recognizes and records the user's emotional state through facial expressions and voice.

[1864] An "artificial intelligence algorithm" is a calculation method that compares input profile information with job information and generates optimal matching candidates.

[1865] "Matching candidates" are people or projects whose skills and job requirements match those of local residents and companies.

[1866] A "virtual store" refers to an online platform that operates in a virtual space, rather than a real physical store.

[1867] "Trend forecasting" is the process of analyzing and predicting current market trends and future skill demands.

[1868] The "database" is a system that stores and manages input information and emotional data from local residents and businesses.

[1869] "Notification" refers to the act of informing local residents and businesses of matching results and other important information.

[1870] "Skill-up resources" refers to learning materials, online courses, and related information that rural residents can use to improve their skills.

[1871] The system that realizes this invention allows residents of rural areas to remotely access companies and projects in urban areas and receive appropriate matching and skill development support. The program processing of this system will be explained in detail below.

[1872] Program generation and processing content

[1873] New user registration

[1874] Device: The user registers using a smartphone or head-mounted display, entering profile information such as name, address, skill set, past work experience, and desired industry and job type.

[1875] Emotion engine: When inputting, the emotion engine recognizes and records the user's emotional state through facial expressions and voice. This emotional data is also sent to the server. Specific software used is "Affectiva Emotion AI" and "Microsoft Azure Cognitive Services."

[1876] Server: Profile information and emotion data are stored in a database using MySQL or Google Firebase.

[1877] Registering company project information

[1878] Companies: Register project information through the virtual store's website or app, including job title, job description, required skill set, salary, etc.

[1879] Terminal: Performs initial validation of registered information and sends it to the server.

[1880] Server: Stores the company's project information in a database.

[1881] Matching Process

[1882] Server: Using an artificial intelligence (AI) algorithm, it compares profile information with company project information. It generates optimal matching candidates by taking into account the user's emotional state as recognized by the emotion engine. Specifically, it uses "TensorFlow" and "PyTorch."

[1883] Server: Notifies local residents and businesses of potential matches via email or in-app notifications.

[1884] Skills improvement support

[1885] Server: Based on user profile information and sentiment data, predicts skills that will be in demand in the future, and generates skill development lists and learning resources that users can view in a virtual store.

[1886] Users: Check out the recommended skill list and learning resources (e.g., online courses) to improve their skills.

[1887] Specific examples

[1888] User A uses a smartphone to register information such as "3 years of web development experience, Python" and records a self-introduction along with a happy expression. Company B registers "Remote web development project, required skills: Python." The server then combines the emotion data and skill information to perform matching and notifies User A and Company B.

[1889] Prompt Sentence Examples

[1890] User A (smartphone):

[1891] New Registration

[1892] Name: Tanaka

[1893] Experience: 3 years of web development experience, Python

[1894] Desired job type: Remote work

[1895] Desired industry: IT

[1896] Expression: Joy

[1897] Company B (virtual store app):

[1898] New project information registration

[1899] Job Title: Web Development

[1900] Required skills: Python

[1901] Salary: 3,000 yen per hour

[1902] This system allows local residents to be matched with the most suitable projects taking into account their emotional state, enabling them to achieve high productivity and satisfaction through remote work.

[1903] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1904] Step 1:

[1905] New user registration

[1906] Input: The user uses a smartphone or head-mounted display to enter profile information (name, address, skill set, past work experience, desired industry and job type, etc.) on the new registration screen.

[1907] Processing: During input, an emotion engine (e.g., Affectiva Emotion AI or Microsoft Azure Cognitive Services) recognizes and records the user's emotional state through facial expressions and voice in real time. This data is sent from the device to a server.

[1908] Output: Profile information and emotion data are stored on the server.

[1909] Step 2:

[1910] Registering company project information

[1911] Input: Companies use the virtual store's website or application to register project information (job type, job description, required skill set, salary, working hours, etc.).

[1912] Processing: During registration, the device performs initial validation of the data (format checks, required fields checks) and sends the validated information to the server.

[1913] Output: Project information is saved to the server database.

[1914] Step 3:

[1915] Matching Process

[1916] Input: The server periodically retrieves user profile information, emotion data, and company project information from the database.

[1917] Processing: The server uses artificial intelligence (AI) algorithms (e.g., TensorFlow or PyTorch) to compare the user's profile information with the company's project information, and generates optimal matching candidates taking into account the user's emotional state as recognized by the emotion engine.

[1918] Output: A list of potential matches is generated and temporarily stored on the server.

[1919] Step 4:

[1920] Notification of matching results

[1921] Input: The server retrieves a list of potential matches and prepares to notify local residents and businesses.

[1922] Processing: The server selects a notification method (email or in-app notification) and sends the matching results, including details about the project and next steps.

[1923] Output: Local residents and businesses receive and review the notification.

[1924] Step 5:

[1925] Skills improvement support

[1926] Input: The server periodically retrieves user profile information and sentiment data, as well as market trend data.

[1927] Processing: The server uses trend prediction algorithms to analyze skills that are likely to be in demand in the future, creates a prioritized skill list based on sentiment data, and generates learning resources (online courses and learning links).

[1928] Output: Skilling resources are displayed on a dashboard for local residents.

[1929] Step 6:

[1930] Project Initiation Procedures

[1931] Input: Local residents receive notifications and begin the application process for projects they're interested in. Companies similarly schedule interviews and skill tests for interested users.

[1932] Processing: The terminal provides an interface for application procedures and interview arrangements, and sends that information to the server.

[1933] Output: The project officially begins, with users and companies collaborating through remote work.

[1934] In this way, each step is carried out in a sequential manner, enabling quick and effective matching between users and companies. Furthermore, ongoing support for skill development improves users' productivity and satisfaction with remote work.

[1935] 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.

[1936] 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.

[1937] 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.

[1938] [Fourth embodiment]

[1939] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1940] 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.

[1941] 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).

[1942] 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.

[1943] 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.

[1944] 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).

[1945] 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. 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.

[1946] 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.

[1947] 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.

[1948] 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.

[1949] 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.

[1950] 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.

[1951] 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."

[1952] The present invention is a system that allows local residents to work remotely from urban areas. The program processing of this system will be explained below in natural language.

[1953] Program processing description

[1954] New user registration

[1955] User

[1956] Visit the website or application and click the "Sign Up" button.

[1957] Enter your profile information, such as your name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[1958] Terminal

[1959] Perform initial validation of the entered information (checking format and required fields) to confirm that it has been entered correctly.

[1960] Send the validated information to the server.

[1961] server

[1962] The received user profile information and desired conditions are stored in a database.

[1963] Registering company job information

[1964] company

[1965] Visit the website or application and click on the "Subscribe to a Job" button.

[1966] Enter the details of the job offer, such as the job type, job content, required skill set, salary, work location, and working style.

[1967] Terminal

[1968] Perform initial validation of entered information.

[1969] Send the validated information to the server.

[1970] server

[1971] The received company job information is saved in a database.

[1972] Matching Process

[1973] server

[1974] Periodically read user and company information from the database.

[1975] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[1976] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[1977] The matching results are temporarily stored in a database.

[1978] Matching notification

[1979] server

[1980] Prepare to notify users and companies of the matching results.

[1981] Notifications are sent via user and company registered email addresses and in-app notification systems.

[1982] Terminal

[1983] Users and businesses receive notifications and review the content of the notifications.

[1984] Next steps

[1985] User

[1986] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[1987] company

[1988] Check the user's profile information and, if interested, schedule an interview or skills test.

[1989] Skills improvement support

[1990] server

[1991] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[1992] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[1993] User

[1994] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[1995] Specific examples

[1996] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[1997] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[1998] The server stores the information of User A and Company B in a database and matches them using an artificial intelligence algorithm.

[1999] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[2000] This system will enable rural residents to acquire skills needed in urban areas, while achieving high productivity and a good work-life balance, thereby helping to revitalize Japan as a whole.

[2001] The processing flow will be explained below.

[2002] Step 1:

[2003] A user visits a website or application and clicks the "Sign Up" button.

[2004] Step 2:

[2005] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[2006] Step 3:

[2007] The terminal performs initial validation of the information entered (checking the format and checking for required fields) to ensure that it has been entered correctly.

[2008] Step 4:

[2009] The terminal sends the information that the validation has been completed to the server.

[2010] Step 5:

[2011] The server stores the received user profile information and desired conditions in a database.

[2012] Step 6:

[2013] A company visits their website or application and clicks the "Register a Job" button.

[2014] Step 7:

[2015] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[2016] Step 8:

[2017] The terminal performs an initial validation of the entered information.

[2018] Step 9:

[2019] The terminal sends the information that the validation has been completed to the server.

[2020] Step 10:

[2021] The server stores the received company job information in a database.

[2022] Step 11:

[2023] The server periodically reads user and company information from the database.

[2024] Step 12:

[2025] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[2026] Step 13:

[2027] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[2028] Step 14:

[2029] The server temporarily stores the matching results in a database.

[2030] Step 15:

[2031] The server prepares to notify the user and the company of the matching results.

[2032] Step 16:

[2033] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[2034] Step 17:

[2035] The device receives a notification to the user and the company, and the notification content is confirmed.

[2036] Step 18:

[2037] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[2038] Step 19:

[2039] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[2040] Step 20:

[2041] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[2042] Step 20:

[2043] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[2044] Step 21:

[2045] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[2046] Example 1

[2047] 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."

[2048] To make it easier for rural residents to access jobs in urban areas, it is necessary to bridge the information gap between rural and urban areas. The current recruitment system makes it difficult for rural residents to find suitable jobs, and for companies to efficiently recruit talented personnel from remote areas. Furthermore, there are no established methods for rural residents to properly learn and acquire the skills required in urban areas, resulting in a skills gap. A comprehensive system to resolve these issues is needed.

[2049] 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.

[2050] In this invention, the server includes: a means for rural residents to input their profile information and skill set; a means for companies to register job information; a means for initially validating the input information; a means for transmitting validated information to the server; a means for using an artificial intelligence algorithm to compare the profile information with the job information of the companies and generate matching candidates; a means for notifying the matching candidates to rural residents and companies; and a means for predicting trends for improving the skills of rural residents and generating a list of required skills. This makes it easier for rural residents to access jobs in urban areas and enables companies to efficiently recruit talented people from remote locations. Furthermore, since rural residents can appropriately learn and acquire skills required in urban areas, the skills gap can be eliminated.

[2051] "Rural residents" refers to individuals who reside in areas away from urban areas.

[2052] "Profile information" refers to personal information such as the user's name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[2053] "Skill set" refers to the skills, knowledge, and specialized abilities possessed by a user.

[2054] "Company" refers to the legal entity that registers job information.

[2055] "Job information" refers to information such as the type of job offered by a company, specific job content, required skill set, salary, work location, and working style.

[2056] "Initial validation" refers to the process of verifying that the information entered is formally correct and that all required fields are filled in.

[2057] "Server" refers to a high performance computer system that processes and stores data.

[2058] "Artificial intelligence algorithm" refers to a calculation method that analyzes user profile information and company job information to generate optimal matching candidates.

[2059] "Matching candidates" refer to the combination that is evaluated as optimal after comparing user and company information.

[2060] "Notification" refers to the act of informing users and businesses of matching results and other important information.

[2061] "Trend forecasting" refers to the process of analyzing market demand and future trends and predicting future trends based on the results.

[2062] The "Skills Needed List" is a list of recommendations for rural residents to acquire skills that will be in demand in the future.

[2063] The present invention is a comprehensive system that enables rural residents to remotely access urban jobs and develop appropriate skills. The system is configured as follows.

[2064] System Configuration

[2065] The system includes multiple components that work together: a user device, a company device, and a server, which contains a database that stores relevant data and an artificial intelligence (AI) model that runs the matching algorithm.

[2066] Program processing overview

[2067] The main processing flow of the system will be specifically explained below.

[2068] New user registration

[2069] Users access the website or application using their own device and click the "New Registration" button. They then enter their profile information, such as their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[2070] The terminal performs initial validation of the information entered by the user in real time, for example, checking that the email address is formatted correctly and that all required fields are filled in. If validation passes, the information is sent to the server.

[2071] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[2072] Registering company job information

[2073] Companies access the website or application using their own devices, click the "Register Job Information" button, and enter details of the job, such as job type, job description, required skill set, salary, work location, and working style.

[2074] The terminal performs an initial validation of the information entered by the company in real time, for example, ensuring that the salary range is appropriate and the required skill set is specifically described, and if validation passes, it sends this information to the server.

[2075] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[2076] Matching Process

[2077] The server periodically reads user and company information from the database. It uses a generative AI model to compare the user's profile information with the company's job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[2078] Matching notification

[2079] The server prepares to notify users and businesses of the matching results. Notifications are sent to the users' and businesses' registered email addresses or via the notification system within the application.

[2080] The terminal displays the notification received by the user and the company, who then checks the notification content and takes the next action.

[2081] Skills improvement support

[2082] The server analyzes the skills that are expected to be in demand in the future based on the user's profile information and market trend data, and uses a generative AI model to generate a list of recommendations for skill development, which are displayed on the user's dedicated dashboard.

[2083] Users can check the recommended skill list and learning resources to improve their skills, which will support their ability development.

[2084] Specific examples

[2085] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information.

[2086] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[2087] The server stores the information of User A and Company B in a database and performs matching using a generative AI model.

[2088] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[2089] Prompt Sentence Examples

[2090] Below are some examples of prompts to input to the generative AI model.

[2091] "Please explain the user registration process for the remote work support system in natural language."

[2092] "Please explain in natural language the process a company goes through to register a job posting."

[2093] "Please explain in natural language the process of matching users and companies."

[2094] "Please explain in natural language the process of notifying matching results."

[2095] "Please explain in natural language the process of supporting skill development in a remote work support system."

[2096] The above is an embodiment of the present invention. This will make it easier for rural residents to access jobs in urban areas, and will enable companies to efficiently recruit talented people in remote areas. It will also enable rural residents to appropriately study and acquire the skills required in urban areas, thereby eliminating the skills gap.

[2097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2098] New user registration

[2099] Step 1:

[2100] The user accesses the website or application using their own device and clicks the "New Registration" button. A profile entry screen appears, and the user enters their name, address, email address, phone number, skill set, years of experience, past work history, desired work style, industry, and job type.

[2101] Input: User's personal information and preferences.

[2102] Output: Profile information entered into the terminal.

[2103] Step 2:

[2104] The terminal performs initial validation of the information entered by the user in real time, for example, ensuring that the email address is formatted correctly and that all required fields are filled in.

[2105] Input: The profile information entered in step 1.

[2106] Data processing: Check email address format and confirm required fields.

[2107] Output: Profile information that passes validation.

[2108] Step 3:

[2109] The terminal transmits the profile information that has passed validation to the server.

[2110] Input: Profile information that passes initial validation.

[2111] Output: The profile information sent to the server.

[2112] Step 4:

[2113] The server stores the received user profile information and desired conditions in a database, thereby completing the new user registration.

[2114] Input: Profile information sent from the device.

[2115] Data processing: storing information in a database.

[2116] Output: Profile information stored in a database.

[2117] Registering company job information

[2118] Step 1:

[2119] Companies access the website or application using their own devices and click the "Register Job Information" button. A job information entry screen will appear, where companies can enter details such as job type, job content, required skill set, salary, work location, and working style.

[2120] Input: Job details (job type, job description, required skill set, salary, work location, working style, etc.).

[2121] Output: The job information entered into the terminal.

[2122] Step 2:

[2123] The terminal performs initial validation of the information entered by the company in real time, for example, to check the appropriateness of the salary and the specificity of the required skill set.

[2124] Input: The job information entered in step 1.

[2125] Data processing: Checking the validity of salaries and confirming the specificity of skill sets.

[2126] Output: A job that passes validation.

[2127] Step 3:

[2128] The terminal transmits the job information that has passed validation to the server.

[2129] Input: A job that passes initial validation.

[2130] Output: The job listing sent to the server.

[2131] Step 4:

[2132] The server stores the received company's job information in a database, thereby completing the registration of the company's job information.

[2133] Input: Job posting submitted from device.

[2134] Data processing: storing information in a database.

[2135] Output: Job information stored in the database.

[2136] Matching Process

[2137] Step 1:

[2138] The server periodically reads user and company information from the database, a process that is performed automatically by a scheduled job.

[2139] Input: User and company information in the database.

[2140] Output: The imported user and company information.

[2141] Step 2:

[2142] The server uses a generative AI model to compare user profile information with company job listings. This AI model evaluates the degree of match between each user and company based on the user's skill set, experience, and desired conditions, and the company's job listings, and generates high-scoring match candidates.

[2143] Input: User and company information imported in step 1.

[2144] Data processing: Analyzing information with a generative AI model and calculating matching scores.

[2145] Output: Match score and candidate matches.

[2146] Step 3:

[2147] The server generates the best matching candidates based on the obtained matching scores and stores them in a temporary database.

[2148] Input: Matching score and match candidates.

[2149] Data processing: storing information in a temporary database.

[2150] Output: Match candidates stored in a temporary database.

[2151] Matching notification

[2152] Step 1:

[2153] The server prepares the email addresses registered by the user and the company and the in-application notification system, generates notification content according to templates, and adds it to the queue for sending.

[2154] Input: Match candidates stored in a temporary database.

[2155] Data processing: Creating notification content and queuing it for sending.

[2156] Output: The notification content queued for sending.

[2157] Step 2:

[2158] The server sends notifications as they become ready, using an SMTP server for email notifications and calling the corresponding notification API for in-app notifications.

[2159] Input: The notification content that has been queued for sending.

[2160] Data processing: Sending notifications using an SMTP server or notification API.

[2161] Output: Notifications sent to users and businesses.

[2162] Step 3:

[2163] The device displays the notifications received by the user and the company, and the user and the company check the notification content and consider the next action.

[2164] Input: Notifications sent to users and businesses.

[2165] Output: The notification content that will be displayed on your device.

[2166] Next steps

[2167] Step 1:

[2168] Users can check the information of the matched companies, and if they are interested, they can apply for an interview with the company via the application's functions or email.

[2169] Input: Notification details and matched company information.

[2170] Output: Interview request submitted.

[2171] Step 2:

[2172] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[2173] Input: Notification content and matched user information.

[2174] Output: Scheduling interviews and skills tests.

[2175] Skills improvement support

[2176] Step 1:

[2177] The server analyzes the skills that are likely to be in demand in the future based on user profile information and market trend data, using a generative AI model for this analysis.

[2178] Input: User profile information and market trend data.

[2179] Data processing: Analyzing skill demand with generative AI models.

[2180] Output: A list of skills that are expected to be in demand.

[2181] Step 2:

[2182] Based on the analysis results, the server generates a list of recommended skills for the user and displays it on the user's dashboard.

[2183] Input: A list of skills that are expected to be in demand.

[2184] Data processing: Generating a list of recommended skills for improvement.

[2185] Output: A list of recommended skills to be improved, displayed on the user's dashboard.

[2186] Step 3:

[2187] Users can review a list of recommended skills and learning resources to improve their skills, such as taking online courses or using designated study materials.

[2188] Input: A list of recommended skills displayed on the user's dashboard.

[2189] Output: Actions to improve skills (taking courses and using learning materials).

[2190] (Application example 1)

[2191] 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."

[2192] Sales activities for sales representatives and freelancers living in rural areas face the challenge of limited means of accessing corporate projects in urban areas and across the country, and limited means of efficiently managing those projects, which requires a great deal of effort and time. Matching with suitable projects is also difficult, and an efficient system is needed to enable sales representatives living in rural areas to smoothly conduct transactions with urban companies. Furthermore, there is a lack of appropriate information sources to help rural residents improve their skills.

[2193] 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.

[2194] In this invention, the server includes: a means for local residents to input their own profile information and skill set; a means for companies to register job information and project information; a means for using an artificial intelligence algorithm to compare the profile information with the company's job information and project information to generate matching candidates; a means for notifying local residents and companies of the matching candidates; a means for predicting trends for improving the skills of local residents and generating a list of necessary skills and learning resources; and a means for displaying the trend predictions and skill list on a dashboard. This allows local residents to efficiently access corporate projects and centrally manage the progress and compensation status of projects. It also provides appropriate information for skill improvement.

[2195] "Rural residents" refers to individuals who reside in rural areas and are physically separated from urban and other areas.

[2196] "Profile information" is a general term for information that indicates an individual's characteristics, such as name, address, skill set, years of experience, and work history.

[2197] A "skill set" refers to the collection of skills and knowledge that an individual possesses, and is a list of the abilities required to perform a specific job.

[2198] "Company" refers to a legal entity that provides products or services.

[2199] "Job information" is information published by a company about the requirements and conditions for jobs and positions that the company is seeking.

[2200] "Project Information" refers to the job description provided by a company, including detailed information about a specific project or job.

[2201] An "artificial intelligence algorithm" is a computational method for analyzing data and finding patterns and relationships, and uses machine learning and natural language processing to process information.

[2202] "Matching candidates" refer to proposals for highly compatible combinations based on information about the user and the company.

[2203] "Notification" means the act of communicating specific information to a designated recipient, whether via email or an in-application notification system.

[2204] "Trend forecasting" refers to the act of analyzing and predicting the skills and market trends that will be required from the present to the future.

[2205] A "skills list" is a list of skills required for a specific job or task.

[2206] "Learning resources" refers to educational materials such as textbooks and online courses that can be used to improve skills.

[2207] A "dashboard" refers to a visual interface that allows users to understand information at a glance.

[2208] "Progress management" refers to the act of managing and tracking the progress of a case or project.

[2209] "Remuneration status" refers to the act of managing the status of compensation paid for completed work or projects.

[2210] This invention is a system for supporting the sales activities of sales representatives and freelancers living in rural areas, specifically, allowing rural residents to access corporate projects in urban areas and across the country and efficiently check the progress management and compensation status of projects. An embodiment of this system is described below.

[2211] System program configuration

[2212] The system mainly consists of a server, user terminals, and enterprise terminals, and uses artificial intelligence algorithms (e.g., SciKit Learn), databases (e.g., PostgreSQL), and web servers (e.g., the Django framework) as necessary technical components.

[2213] Processing flow

[2214] 1. New user registration

[2215] The user enters their profile information and skill set.

[2216] Initial validation is performed on the terminal side and sent to the server.

[2217] The server stores the received information in a database and notifies the user that registration is complete.

[2218] 2. Registering company job information and project information

[2219] Companies enter detailed job and project information.

[2220] Initial validation is performed on the terminal side and sent to the server.

[2221] The server stores the received information in a database and notifies the company that registration is complete.

[2222] 3. Matching by AI algorithm

[2223] The server periodically reads user and company information from the database and performs a comparison.

[2224] An artificial intelligence algorithm is used to evaluate the degree of matching and generate high-scoring candidates.

[2225] The matching results are temporarily stored in a database and prepared for notification.

[2226] 4. Notification and Control

[2227] The server notifies users and companies of the matching results via email or in-app notifications.

[2228] Users can check the progress and compensation status of selected projects on a dashboard.

[2229] 5. Skills improvement support

[2230] The server analyzes market trend data and generates a list of skills and learning resources required by the user.

[2231] This is displayed on a user-specific dashboard to support self-improvement.

[2232] Specific examples

[2233] For example, suppose sales representative A, who lives in a rural area, registers and enters "3 years of B2B sales experience, online sales skills." Company B registers project information such as "online sales of a new product, required skills: B2B sales, use of web conferencing tools." The server stores the information of User A and Company B in a database, performs matching using an artificial intelligence algorithm, and generates high-scoring match candidates. The server notifies User A and Company B of the results, and User A accepts the project, thereby beginning remote sales activities. Progress management and compensation status can be checked on User A's dashboard. The server also analyzes market trends and provides resources to recommend that User A learn additional "online marketing skills."

[2234] Prompt Sentence Examples

[2235] Here are some example prompts for the generative AI model used in the job matching algorithm:

[2236] Sales Representative Profile:

[2237] Skill Set: {skill_set}

[2238] Years of experience: {years_of_experience}

[2239] Previous work experience: {job_history}

[2240] Company Project Information:

[2241] Job type: {job_type}

[2242] Job Description: {job_description}

[2243] Required Skill Set: {required_skills}

[2244] Reward: {salary}

[2245] Employment type: {employment_type}

[2246] Use the information above to match you with the most suitable sales representative.

[2247] In this way, a system can be realized that allows people living in rural areas to efficiently access corporate projects in urban areas and across the country, and to accept and proceed with appropriate projects.

[2248] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2249] Step 1:

[2250] The user enters their profile information and skill set to register as a new user. Specifically, the user accesses the application and enters information such as name, address, skill set, years of experience, and work history. Once this input is complete, the terminal validates this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the user that registration is complete.

[2251] Step 2:

[2252] Companies enter and register job information and project information. Specifically, companies log in to the application and enter detailed information such as job type, job content, required skill set, salary, work location, and working style. Once this input is complete, the terminal performs an initial validation of this data. After checking the format and confirming required fields, if validation is successful, it is sent to the server. The server saves the received information in a database and notifies the company that registration is complete.

[2253] Step 3:

[2254] The server periodically reads user and company information from the database and runs a matching algorithm. Specifically, the server uses Python and SciKit Learn to compare user profile information with company job postings and job opportunities, scoring the degree of match. Based on the generated scores, high-scoring match candidates are generated and temporarily stored in the database. The algorithm uses machine learning models to find the best match, taking into account past matching data and trends.

[2255] Step 4:

[2256] The server notifies users and companies of high-scoring match candidates. Specifically, in preparation for the notification, the server dynamically generates the generated match candidate data and inserts it into email templates and in-application notification messages. The server uses Python's Django framework to construct the notification message and sends it to users and companies. Users and companies can then check the received notification and confirm detailed information about the match candidates.

[2257] Step 5:

[2258] Users manage the order process for projects and check progress and compensation status. Specifically, based on the project information received by users, they can check the progress and compensation status of projects on the dashboard within the application. The server links the project information with the user's progress data and continuously updates it.

[2259] Step 6:

[2260] The server analyzes market trend data and provides users with information to improve their skills. Specifically, it analyzes the received market trend data and identifies skills and knowledge that will be in high demand in the future. It uses Python to analyze the data and generates a list of skills and learning resources specifically for each user. This information is displayed on the user's dashboard and provided as reference for self-improvement.

[2261] Through these steps, we have created a system that allows sales representatives and freelancers living in rural areas to efficiently manage projects and improve their skills.

[2262] 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.

[2263] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. Below, the program processing of this system is explained in natural language.

[2264] Program processing description

[2265] New user registration

[2266] User

[2267] Visit the website or application and click the "Sign Up" button.

[2268] Enter your profile information, such as your name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[2269] The emotion engine recognizes and records the user's emotional state through facial expressions and voice input.

[2270] Terminal

[2271] Perform initial validation (format check and check for required fields) on the entered information and emotional data to ensure they are entered correctly.

[2272] Send the validated information to the server.

[2273] server

[2274] The received user profile information, desired conditions, and emotional data are stored in a database.

[2275] Registering company job information

[2276] company

[2277] Visit the website or application and click on the "Subscribe to a Job" button.

[2278] Enter the details of the job offer, such as the job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, working style, etc.

[2279] Terminal

[2280] Perform initial validation of entered information.

[2281] Send the validated information to the server.

[2282] server

[2283] The received company job information is saved in a database.

[2284] Matching Process

[2285] server

[2286] User and company information and user sentiment data are periodically read from the database.

[2287] It uses artificial intelligence algorithms to compare users' profile information with company job listings.

[2288] The emotional state of the user recognized by the emotion engine is also taken into consideration to optimize matching candidates.

[2289] The degree of match between each user and company is evaluated, and high-scoring matching candidates are generated.

[2290] The matching results are temporarily stored in a database.

[2291] Matching notification

[2292] server

[2293] Prepare to notify users and companies of the matching results.

[2294] Notifications are sent via user and company registered email addresses and in-app notification systems.

[2295] Terminal

[2296] Users and businesses receive notifications and review the content of the notifications.

[2297] Next steps

[2298] User

[2299] Check the information of the matched companies, and if you are interested, apply for an interview with the company via application or email.

[2300] company

[2301] Check the user's profile information and, if interested, schedule an interview or skills test.

[2302] Skills improvement support

[2303] server

[2304] Based on user profile information and market trend data, we analyze skills that are expected to be in demand in the future.

[2305] The skill list is prioritized based on the user's emotional state as recognized by the emotion engine.

[2306] Generate a list of recommendations for skill development and display it on a personal dashboard for each user.

[2307] User

[2308] Check out the recommended skills list and learning resources (online courses, links to learning materials, etc.) to improve your skills.

[2309] Specific examples

[2310] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[2311] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[2312] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[2313] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[2314] This system allows rural residents to acquire the skills required in urban areas, while also taking emotional data into account to achieve optimal matching, thereby achieving high productivity and a rich work-life balance.

[2315] The processing flow will be explained below.

[2316] Step 1:

[2317] A user visits a website or application and clicks the "Sign Up" button.

[2318] Step 2:

[2319] The user enters their profile information, such as name, address, email address, phone number, skill set (JavaScript, Python, etc.), years of experience, past work history, desired work style (remote work, full-time, etc.), desired industry and job type, etc.

[2320] Step 3:

[2321] The device activates an emotion engine to recognize and record the user's emotional state through facial expressions and voice input.

[2322] Step 4:

[2323] The device performs initial validation (format checks and checks for required fields) of the entered information and emotional data to confirm that it has been entered correctly.

[2324] Step 5:

[2325] The terminal sends the information that the validation has been completed to the server.

[2326] Step 6:

[2327] The server stores the received user profile information, desired conditions, and emotional data in a database.

[2328] Step 7:

[2329] A company visits their website or application and clicks the "Register a Job" button.

[2330] Step 8:

[2331] Companies enter details of job openings, such as job type, job content, required skill set (e.g. JavaScript, Python), salary, work location, and working style.

[2332] Step 9:

[2333] The terminal performs an initial validation of the entered information.

[2334] Step 10:

[2335] The terminal sends the information that the validation has been completed to the server.

[2336] Step 11:

[2337] The server stores the received company job information in a database.

[2338] Step 12:

[2339] The server periodically reads user and company information and user emotion data from the database.

[2340] Step 13:

[2341] The server uses artificial intelligence algorithms to compare the user's profile information with company job listings.

[2342] Step 14:

[2343] The server also takes into consideration the emotional state of the user recognized by the emotion engine and optimizes the matching candidates.

[2344] Step 15:

[2345] The server evaluates the degree of match between each user and company and generates high-scoring match candidates.

[2346] Step 16:

[2347] The server temporarily stores the matching results in a database.

[2348] Step 17:

[2349] The server prepares to notify users and companies of the matching results.

[2350] Step 18:

[2351] The server sends notifications using the user's and company's registered email address or the in-application notification system.

[2352] Step 19:

[2353] The device receives a notification to the user and the company, and the notification content is confirmed.

[2354] Step 20:

[2355] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[2356] Step 21:

[2357] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[2358] Step 22:

[2359] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[2360] Step 23:

[2361] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[2362] Step 24:

[2363] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[2364] Step 25:

[2365] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[2366] Specific examples

[2367] User A (device) registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent to the server.

[2368] Company B (terminal) posts a job posting with the following: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[2369] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[2370] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[2371] Example 2

[2372] 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."

[2373] When rural residents perform remote work for urban jobs, there are problems such as inappropriate matching and incompatible matches due to a lack of consideration of emotional states. Furthermore, there is a lack of effective support for rural residents to improve their skills, making it difficult for them to improve their competitiveness in the market.

[2374] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for local residents to input their own profile information and skill sets, a means for companies to register job information, a means for recognizing the emotional state of residents using an emotion engine, a means for comparing the profile information, the emotional state, and the job information of the companies using an artificial intelligence algorithm to generate matching candidates, a means for notifying local residents and companies of the matching candidates, and a means for predicting trends for improving the skills of local residents and generating a list of required skills. This enables local residents to perform appropriate matching taking into account their emotional state and to effectively improve their skills.

[2375] "Rural residents" refers to individuals who reside in areas other than urban areas.

[2376] "Profile information" refers to personal information such as a user's name, address, email address, telephone number, skill set, years of experience, work history, desired work style, and desired industry and job type.

[2377] A "skill set" refers to a collection of specific skills and knowledge that a user possesses, and examples include programming languages ​​(JavaScript, Python, etc.).

[2378] "Emotion engine" refers to technology for recognizing and analyzing a user's emotional state through facial expressions and voice.

[2379] "Artificial intelligence algorithm" refers to the calculation procedures and models used to compare profile information with company job listings and generate optimal matching candidates.

[2380] "Matching candidates" refer to optimal combinations of users and companies generated based on profile information and company recruitment information.

[2381] "Database" refers to a structured collection of information within a computer system for storing profile information, job listings, emotional data, etc.

[2382] "Trend forecasting" refers to a method of analyzing market trends and predicting skills that are likely to be in high demand in the future.

[2383] A "skill list" refers to a list of skills and knowledge that local residents should learn to improve their skills.

[2384] "Notification" means information or communication sent to a user or business via email or within an application.

[2385] This invention is a system that allows rural residents to work remotely from urban areas, and by combining it with an emotion engine that recognizes the user's emotions, it achieves more appropriate matching. This system consists of the following elements.

[2386] 1. Register a new user:

[2387] A user accesses a website or application, clicks the "Sign Up" button, and then enters profile information such as their name, address, email address, phone number, skill set (e.g., JavaScript, Python), years of experience, past work history, desired work style (remote work, full-time, etc.), and desired industry and job type.

[2388] The emotion engine recognizes the user's emotional state in real time through facial expressions and voice input, and collects emotional data.

[2389] The device performs initial validation (format check and confirmation of required fields) on the information and emotion data collected to confirm that it has been entered correctly. After that, the validated information is sent to the server.

[2390] The server stores the received user profile information, desired conditions, and emotional data in a database.

[2391] 2. Company job postings:

[2392] Companies access their website or application, click the "Submit Job Information" button, and then enter details about the job, such as job type, job description, required skill set (e.g., JavaScript, Python), salary, work location, and working style.

[2393] The terminal performs an initial validation of the entered information to ensure it is entered correctly.

[2394] The validated information is sent to the server, and the company's job information received by the server is saved in the database.

[2395] 3. Matching Process:

[2396] The server periodically reads user and company information and sentiment data from the database.

[2397] The server uses an artificial intelligence algorithm to compare the user's profile information with company job listings, and also optimizes matching candidates by taking into account the user's emotional state as recognized by an emotion engine.

[2398] The server evaluates the degree of match between each user and company, and generates high-scoring match candidates, which are temporarily stored in a database.

[2399] 4. Match Notification:

[2400] The server prepares to notify users and companies of the matching results, using the registered email addresses of users and companies or the in-application notification system.

[2401] The device receives the notification and the user and company confirm the notification content.

[2402] 5. Next steps:

[2403] Users can check the information of the matched companies and, if they are interested, apply for an interview with the company via an application or email.

[2404] Companies will review the user's profile information and, if interested, schedule an interview or skills test.

[2405] 6. Skills development support:

[2406] The server analyzes skills that are expected to be in demand in the future based on user profile information and market trend data.

[2407] The server changes the priority of the skill list based on the emotional state of the user recognized by the emotion engine.

[2408] The server generates a list of recommendations for skill development and displays it on the user's personal dashboard.

[2409] Users can check out recommended skill lists and learning resources (online courses, links to educational materials, etc.) to improve their skills.

[2410] Specific examples

[2411] A specific example is shown below.

[2412] User A registers and enters "3 years of experience in web development, knowledge of JavaScript and Python" as profile information. While entering the information, emotion data recognized by the emotion engine is also sent.

[2413] Company B posts a job posting with the following description: "Looking for a remote full-stack web developer. Required skills: JavaScript, Python."

[2414] The server stores information and emotional data of User A and Company B in a database, and performs matching using an artificial intelligence algorithm and an emotion engine.

[2415] The server notifies User A and Company B of the matching results, and User A and Company B then finalize employment through an interview or other process.

[2416] Prompt Sentence Examples

[2417] Here are some example prompts for input using a generative AI model:

[2418] User A registers and enters "3 years of web development experience, knowledge of JavaScript and Python" as profile information. The emotion engine collects the user's emotional data. Company B posts a job posting with "Remote full-stack web developer wanted, required skills: JavaScript, ...

Claims

1. A means for local residents to enter their profile information and skill sets; A means for companies to register job information, means for comparing the profile information with job information of the companies using an artificial intelligence algorithm to generate matching candidates; means for notifying local residents and businesses of said potential matches; A means for forecasting trends and generating a list of required skills for improving the skills of local residents; A system including:

2. 10. The system of claim 1, further comprising means for storing information entered by local residents and businesses in a database.

3. The system of claim 1 , further comprising means for notifying local residents and businesses using email or in-application notifications.

Images