System

Abstract

A system is provided.SOLUTION: This system is provided with a means for allowing a user to input a skill set or desired job change conditions, a means for receiving information inputted by the user in a server, and for storing it in a database, and a means for analyzing the stored information in the server. A system, comprising: means for selecting an optimal job opening based on a matching algorithm; means for sending, by a server, selected job opening information to a terminal of a user; means for displaying, by the terminal, the job opening information; means for selecting, by the user, the displayed job opening information; means for generating, by the server, a job change advice based on the selected job opening information and sending the job change advice to the terminal; and means for displaying, by the terminal, the job change advice.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] In conventional job-change support services, agents have biased industry knowledge, which is one of the reasons why job seekers have limited options. Furthermore, the complicated process of communicating with agents can make job-change activities less efficient. The purpose of this invention is to resolve these issues and provide comprehensive and fair support to job seekers. [Means for solving the problem]

[0005] The present invention provides a system including: a means for a user to input a skill set and desired job-changing conditions; a server for receiving the information input by the user and storing it in a database; a server for analyzing the stored information and selecting optimal job offers based on a matching algorithm; a server for transmitting the selected job offers to a user's terminal; a terminal for displaying the job offers; a user for selecting the displayed job offers; a server for generating job-changing advice based on the selected job offers and transmitting the advice to the terminal; and a terminal for displaying the job-changing advice. This allows users to find the job that best suits them from a wide range of options without relying on an agent, enabling efficient job-changing activities.

[0006] "User" refers to an individual who uses the service and inputs their skill set and desired job search conditions.

[0007] A "skill set" refers to a collection of specialized knowledge and abilities that a user possesses.

[0008] "Desired conditions for changing jobs" refers to specific conditions that a user desires in a new workplace, such as job type, work location, salary range, etc.

[0009] "Device" refers to a device such as a computer, smartphone, or tablet that a User uses to access the Service and input or view information.

[0010] "Server" refers to the central computer system that receives, stores, analyzes, and processes information sent by users.

[0011] A "database" refers to a collection of data that allows a server to store information in an organized manner and retrieve it as needed.

[0012] "Parsing" refers to the process by which the server understands and extracts meaning from the information entered by the user.

[0013] A "matching algorithm" refers to a calculation method for selecting the most suitable job information based on a user's skill set and desired conditions.

[0014] "Job Information" refers to information containing details and conditions of jobs offered by companies.

[0015] "Selection" refers to the process by which the server analyzes the job information in the database and selects the most suitable one.

[0016] "Career change advice" refers to specific interview preparation and resume writing advice tailored to the job opening selected by the user. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI to replace the work traditionally performed by job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[0039] Specific system configuration and processing explanation

[0040] User registration and information entry

[0041] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[0042] Information storage and analysis

[0043] The server receives the information entered by the user and stores it in a database. The received information is then analyzed using an analysis engine to analyze the user's skill set, work history, and desired conditions using natural language processing. Based on the analyzed information, a matching algorithm selects the most suitable job opening from the database.

[0044] Generating and displaying matching results

[0045] The server generates a job listing that best suits the user based on a matching algorithm and transmits the listing to the user's terminal, which then displays the listing to the user, allowing the user to view details of the displayed job listings.

[0046] Selection of job information and provision of countermeasures advice

[0047] The user selects the job they are most interested in from the displayed job information. The selected information is sent from the device to the server. The server then generates career change advice for the job based on this selection information. Specifically, the advice is provided tailored to the skill set required by the company, such as how to write a resume and what to emphasize in an interview.

[0048] Viewing and following advice

[0049] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[0050] Specific examples

[0051] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "project manager position at Company A." These job openings are again displayed to the user via their device, and if the user views the details and becomes interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the user via their device. For example, advice such as "Describe specific examples of successful project management" is displayed.

[0052] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, making job hunting more efficient.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[0056] Step 2:

[0057] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[0058] Step 3:

[0059] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[0060] Step 4:

[0061] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[0062] Step 5:

[0063] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[0064] Step 6:

[0065] The server sends the job listing to the terminal. The information sent is encrypted in response format.

[0066] Step 7:

[0067] The terminal displays the received job list to the user, who then clicks on the details of the job that interests them.

[0068] Step 8:

[0069] When the user selects a job offer that he or she wishes to view, the terminal transmits the selected job offer information to the server.

[0070] Step 9:

[0071] The server receives the selected job information and generates career change advice specific to the job, including tips on how to prepare for an interview and how to write a resume.

[0072] Step 10:

[0073] The server generates and sends the advice to the terminal. The advice information is encrypted.

[0074] Step 11:

[0075] The device displays the received advice to the user, who can then use this advice to prepare for specific job hunting activities.

[0076] Explanation with concrete examples

[0077] Step 1:

[0078] The user accesses the app and enters their name, email address, password, work history (e.g., "Engineer, ABC Company, 3 years"), skill set (e.g., "Java, project management"), and desired job conditions (e.g., "Project manager, Tokyo, annual salary of 6 million yen or more") on the new registration screen.

[0079] Step 2:

[0080] The terminal sends the above input information to the server.

[0081] Step 3:

[0082] The server stores the input information in a database.

[0083] Step 4:

[0084] The server runs the input information through a natural language processing engine to analyze skills and work history.

[0085] Step 5:

[0086] The server lists the most suitable job information based on the analysis results.

[0087] Step 6:

[0088] The server sends the most suitable job listings to the device.

[0089] Step 7:

[0090] The device displays a list of job listings to the user, such as "Project Manager position at Company D" or "Senior Engineer position at Company E."

[0091] Step 8:

[0092] The user selects "Project Manager position at Company D."

[0093] Step 9:

[0094] The server receives the selected job information and generates advice on interview preparation and resume writing specific to Company D.

[0095] Step 10:

[0096] The server generates job change advice and sends it to the terminal.

[0097] Step 11:

[0098] The device will display advice to the user, such as "In your interview with Company D, emphasize specific examples of successful project management" or "It is recommended that you include detailed information about your leadership experience in your resume."

[0099] Example 1

[0100] 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."

[0101] Traditional career change support services are often provided through recruitment agencies, but the quality and response speed of the services provided by these agencies vary. They also lack efficient methods for matching users with the right skills and desired conditions. Furthermore, when it comes to career change strategies, they often provide general advice, without providing specific advice tailored to individual job openings.

[0102] 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.

[0103] In this invention, the server includes a means for a user to input information, a means for receiving the information input by the user and storing it in a data storage, a means for analyzing the stored information in the server and selecting an optimal job based on a matching algorithm, a means for transmitting the selected job information to the user's device, a means for displaying the job information on the device, a means for the user to select the displayed job information, a means for generating career change advice based on the selected job in the server and transmitting it to the device, and a means for displaying the career change advice on the device. This allows users to efficiently find a job that best suits their skill set and desired conditions without relying on traditional career change agents. Furthermore, by providing specific career change advice tailored to individual job openings, the user's success rate in changing jobs can be improved.

[0104] "User" refers to an individual who uses the system to search for a new job.

[0105] "Information" refers to data entered by the user, such as skill set, desired job conditions, and work history.

[0106] "Server" refers to a computer system that receives information sent by a user, stores it in data storage, analyzes it, and provides appropriate services.

[0107] "Data Storage" refers to a data storage device or database for storing information received from a user.

[0108] A "matching algorithm" refers to a calculation method or program for selecting the most suitable job based on user information.

[0109] "Job information" refers to information about jobs stored on the server, including job type, job content, working conditions, etc.

[0110] "Device" refers to hardware such as a computer, tablet, or smartphone that a user uses to access the system.

[0111] "Career change advice" refers to advice and suggestions that are generated by the server and provided to users to help them with their job search.

[0112] "Natural language processing" refers to a computer science technique for analyzing textual information entered by a user and understanding its meaning.

[0113] A "skill set" refers to the qualifications, experience, and abilities that a company is looking for.

[0114] This invention is a job change support system that helps users efficiently find a job that suits them. This system uses advanced analytical means and matching algorithms to provide optimal job information based on the user's skill set and desired job change conditions, and also provides advice on how to change jobs.

[0115] Specifically, the system consists of the following elements:

[0116] 1. User Interface

[0117] Users enter information about themselves through a website or application, including their name, email address, password, work history, skill set, and job preferences. The information is collected using HTML forms and validated using JavaScript.

[0118] 2. Receipt and storage of information

[0119] The terminal sends the information entered by the user to the server, which then stores the received information in data storage (e.g., MySQL or PostgreSQL). This step uses encoding and encryption techniques to ensure that user information is stored safely and efficiently.

[0120] 3. Information analysis

[0121] The server analyzes the stored information using Python, PySpark, etc. Natural language processing (NLP) techniques are used for this analysis. Specifically, libraries such as SpaCy and NLTK are used to analyze the user's skill set, work history, and desired conditions through tokenization, part-of-speech tagging, and named entity recognition.

[0122] 4. Matching Algorithm

[0123] The server then applies a matching algorithm based on the analysis results, using machine learning models (e.g., SVM and decision tree algorithms) using the Scikit-learn library. Suitable job postings are selected from the database and listed.

[0124] 5. Submitting and Displaying Job Postings

[0125] The server sends the generated job listings in JSON format to the device, which receives the information and displays it on the user's screen using a front-end framework such as React or Vue.js.

[0126] 6. Job information selection and job change advice generation

[0127] The user selects the job they are interested in from the displayed job information. This selection information is also sent from the device to the server. Based on the selected job, the server uses an analysis engine written in a Python program or similar to generate career change advice tailored to the job.

[0128] 7. Advice Display

[0129] The job-changing advice sent from the server is displayed on the device, and users can refer to this advice to smoothly proceed with their specific job-changing activities.

[0130] Specific examples

[0131] For example, imagine a user has the skill of "project management" in the field of "engineering" and would like to work in "Tokyo." The user enters this information into the system and sends it to the server via their terminal. The server analyzes this information, compiles a list of suitable job openings from the database, such as "project manager position at company X," and sends it to the terminal. If the user is interested in "project manager position at company X" and selects that information, the server will respond to the selection and generate resume writing advice and interview preparation specific to company X, and send it to the terminal. For example, advice such as "Describe specific examples of successful project management" will be displayed.

[0132] Prompt Sentence Examples

[0133] "If a user has the skill "Project Management" in the field of "Engineering" and desires to work in "Tokyo," please explain in detail the steps required to generate suitable job offers and career advice. Please also mention the specific actions for each step."

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] Step 1:

[0136] Users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job conditions on the registration screen. The entered information is collected on the web page through an HTML form and validated using JavaScript.

[0137] Input: User's personal information, work history, skill set, job search requirements

[0138] Output: Validated user information

[0139] Specific behavior:

[0140] The terminal receives input from the user and uses JavaScript to check whether the form has been filled out correctly.

[0141] If validation is successful, the form data is encoded and sent to the server using an AJAX request.

[0142] Step 2:

[0143] The server stores the received user information in a data storage (such as MySQL or PostgreSQL), during which the data is encoded and encrypted as necessary.

[0144] Input: Validated user information

[0145] Output: User information saved in data storage

[0146] Specific behavior:

[0147] The server decodes the data received from the AJAX request and takes measures against SQL injection.

[0148] Executes an INSERT statement against the database to securely store the user information.

[0149] Step 3:

[0150] The server analyzes the stored user information, using natural language processing (NLP) techniques such as Python and PySpark to analyze the user's skill set, work history, and desired conditions.

[0151] Input: User information stored in data storage

[0152] Output: Parsed user information (e.g., JSON format)

[0153] Specific behavior:

[0154] The server reads user information from a database and uses SpaCy and NLTK for tokenization, part-of-speech tagging, and named entity recognition.

[0155] The parsed results are converted to JSON format and saved for further processing.

[0156] Step 4:

[0157] The server applies a matching algorithm based on the analyzed information to select the most suitable job postings, specifically by running machine learning models (e.g., SVMs and decision trees) using the Scikit-learn library.

[0158] Input: Parsed user information

[0159] Output: List of matching jobs (e.g., in JSON format)

[0160] Specific behavior:

[0161] The server compares the parsed user information with job listings stored in a database and applies a matching algorithm.

[0162] Select the most suitable job information, convert it to JSON format and save it.

[0163] Step 5:

[0164] The server sends a list of matching jobs in JSON format to the device, which then displays the received job information in a user interface using front-end frameworks such as React and Vue.js.

[0165] Input: List of matching jobs (e.g., in JSON format)

[0166] Output: The job displayed in the user interface

[0167] Specific behavior:

[0168] The server encodes the job information in JSON format and sends it to the terminal as an HTTP response.

[0169] The device receives the job information, renders it in HTML using React or Vue.js, and displays it on the user's screen.

[0170] Step 6:

[0171] The user selects from the displayed job information the job they are interested in. This selection information is sent from the terminal to the server.

[0172] Input: Job listing selected by user

[0173] Output: Selections sent to the server

[0174] Specific behavior:

[0175] The terminal records the user's selection and transmits the selected job information in an encoded form to the server.

[0176] The server decodes the received selection information and prepares for the next process.

[0177] Step 7:

[0178] The server generates job-change advice based on the selected job information, using an analysis engine written in Python to provide advice specific to the job.

[0179] Input: Job listing selected by user

[0180] Output: Generated job-changing advice (e.g., JSON format)

[0181] Specific behavior:

[0182] The server parses the selected job postings and generates recommendations in a Python script.

[0183] The generated advice is encoded in JSON format and sent to the device.

[0184] Step 8:

[0185] The terminal displays the job change advice sent from the server to the user.

[0186] Input: Generated job change advice (e.g., JSON format)

[0187] Output: Career change advice displayed in a user interface

[0188] Specific behavior:

[0189] The terminal receives the advisory information and visualizes it to the user using HTML and CSS.

[0190] The user can refer to the displayed advice and use it to help with their job search.

[0191] (Application example 1)

[0192] 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."

[0193] Conventional job-hunting support systems are only available online, making them inadequate for job seekers who prefer to receive in-person support in a brick-and-mortar store. Furthermore, when it comes to providing job information and career advice, the same content is provided to all users, and it is not customized to fit individual skill sets or desired conditions. This often results in inefficient job hunting.

[0194] 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.

[0195] In this invention, the server includes: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information in the server and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for a user to select displayed job offers; means for generating job-changing advice based on the selected job offers and transmitting it to the terminal; means for displaying the job-changing advice on the terminal; means for executing processes from information input to display of job-changing advice via a smartphone app in a physical store; and means for generating job offers and job-changing advice using prompt sentences generated by a generative AI model. This enables direct support in physical stores and makes it possible to provide job offers and job offers and advice customized to individual job seekers.

[0196] A "user" is an individual who uses the system to input their skill set and desired job-changing conditions and receives job information and advice on career changes.

[0197] A "skill set" is a collection of skills and abilities related to a user's job or work.

[0198] "Desired conditions for changing jobs" are conditions such as the place of work, job type, salary, etc. that the user desires when changing jobs.

[0199] The "server" is a central management device that receives and stores information entered by users, analyzes it, selects job information, and generates career change advice.

[0200] "Database" refers to the storage area within the system for storing information entered by users and job information.

[0201] A "matching algorithm" is a calculation method or procedure for selecting the most suitable job offer based on a user's skill set and desired job change conditions.

[0202] A "terminal" is an electronic device that a user uses to display job information and career change advice, and to transmit input information.

[0203] "Job information" refers to information provided by companies, such as job content, required skills, work location, and salary.

[0204] "Career change advice" is advice on how to prepare a resume and interview for a job that the user is looking for.

[0205] A "physical store" is a physical location where job seekers can visit in person and receive job change support services using the system.

[0206] A "smartphone app" is software that runs on a smartphone and allows users to use the system to input their skill set and desired job-changing conditions, and receive job information and advice on how to change jobs.

[0207] A "generative AI model" is an artificial intelligence technology that generates prompts based on user input and customizes job information and career change advice.

[0208] A "prompt" is text generated by a generative AI model, and is an instructional sentence that provides job information and career change advice.

[0209] This invention is a job change support system that uses AI. Users can input their skill set and desired job change conditions via a smartphone app at a physical store, obtain the most suitable job information, and receive effective advice on how to change jobs.

[0210] Overall system configuration

[0211] 1. User registration and information entry

[0212] Users use a smartphone app installed in a physical store to enter information such as their name, email address, password, work history, skill set, and desired job conditions. The information entered is sent to and stored on a cloud server in real time.

[0213] 2. Analysis of Information

[0214] The server stores the received information in a database and uses a natural language processing engine (Google Cloud Natural Language API) to analyze the skillset and desired job conditions. The analyzed information is stored as structured data for use in the next step.

[0215] 3. Matching and job information provision

[0216] The server uses an AI matching algorithm (TensorFlow) to select suitable job offers based on the analyzed user information. The selected job offers are sent to the user's smartphone in real time and displayed to the user.

[0217] 4. Selection of job information and advice on countermeasures

[0218] When a user selects a job posting, the selection is sent to the server. The server generates job-changing advice specific to the company based on the selection. At this time, a generative AI model is used to generate a prompt message, and advice reflecting that message is created.

[0219] The generated advice for career change is sent back to the smartphone and displayed to the user.

[0220] Specific examples

[0221] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in an "urban area." The user enters this information into a smartphone app, which then sends it to the server. The server analyzes this information and lists suitable job postings from its database, such as "project manager position at Company A." The listed job postings are displayed on the smartphone, and if the user is interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the smartphone. For example, advice such as "Describe specific examples of successful project management practices" is displayed.

[0222] Prompt Sentence Examples

[0223] As a concrete example, the following prompt sentence is input to the generative AI model:

[0224] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[0225] Based on this prompt, the AI ​​model generates relevant job information and career change advice.

[0226] With the introduction of this system, job seekers will be able to efficiently conduct their job search even at physical stores, and will be able to receive individually customized job information and career change advice via a smartphone app.

[0227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0228] Step 1:

[0229] Users use a smartphone app installed in a physical store to input their skill set and desired job conditions. At this time, users enter information such as their name, email address, password, work history, skill set, and desired job conditions into the app. The input information is sent in real time to a server on the cloud. This step also involves verifying the input data and checking for required fields.

[0230] input:

[0231] Name, email address, password, work history, skill set, desired job conditions

[0232] output:

[0233] User information sent to the cloud server

[0234] Step 2:

[0235] The server stores the received user information in a database. At the same time, the stored information is analyzed using a natural language processing engine (Google Cloud Natural Language API). This analysis extracts skill sets and desired job conditions as structured data.

[0236] input:

[0237] User Information

[0238] output:

[0239] Structured data stored in a database

[0240] Step 3:

[0241] The server uses an AI matching algorithm (TensorFlow) to select the most suitable job postings based on the analyzed user structured data. The selection process involves referencing a job posting database to find the job that best suits the user's skill set and desired job change conditions.

[0242] input:

[0243] Structured data, job information database

[0244] output:

[0245] Best job listings

[0246] Step 4:

[0247] The server sends the selected job listings to the user's smartphone, where they are displayed and the user can review them. Here, job seekers can view the details of various job listings and select the one that best suits them.

[0248] input:

[0249] Best job listings

[0250] output:

[0251] Job information displayed on a smartphone

[0252] Step 5:

[0253] Once a user selects the job postings they are interested in, the selection is sent to the server, which then generates job-changing advice specific to the company using a generative AI model to generate prompts and customize the advice accordingly.

[0254] input:

[0255] User-selected job listings

[0256] output:

[0257] Generated career change advice

[0258] Step 6:

[0259] The server then sends the generated job-changing advice back to the smartphone, where the user can check the advice and use it to prepare for their resume or interview.

[0260] input:

[0261] Generated career change advice

[0262] output:

[0263] Job change advice displayed on smartphones

[0264] For example, if the user name is "Yamada Taro" and the desired job is "software developer" and "work in an urban area," the following prompt sentence will be input to the generative AI model:

[0265] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[0266] Based on this prompt, the AI ​​model generates relevant job information and career change advice, which are then provided to the user.

[0267] These specific processing steps enable users to efficiently conduct job hunting activities even at brick-and-mortar stores, and receive individually customized job information and career change advice via a smartphone app.

[0268] 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.

[0269] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[0270] Specific system configuration and processing explanation

[0271] User registration and information entry

[0272] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[0273] Information storage and analysis

[0274] The server receives the information entered by the user and stores it in a database. The received information is converted into a standard format by a pre-processing program, and then the analysis engine analyzes the user's skill set, work history, and desired conditions using natural language processing. Based on this, a matching algorithm selects the most suitable job opening from the database.

[0275] Introducing emotion engine analysis

[0276] The server also incorporates an emotion engine that recognizes emotions from user input and selection history. The emotion engine analyzes the user's input words and behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.).

[0277] Generating and displaying matching results

[0278] The server generates a list of job offers that best suit the user based on a matching algorithm and sends that list to the device. By taking into account the analysis results of the emotion engine, it is possible to customize the display of job information that is more appropriate to the user's current emotional state. For example, if a user is judged to be highly stressed, job offers with work environments that are deemed to be less stressful will be displayed preferentially.

[0279] The terminal displays the sent job listing to the user, and the user can view the details of the displayed job listing.

[0280] Selection of job information and provision of countermeasures advice

[0281] The user selects the job that interests them most from the displayed job information. The selected information is sent from the terminal to the server. Based on this selection, the server generates job change advice for the job. This advice is also customized taking into account the user's emotional state. For example, if the user tends to get nervous, advice on relaxation techniques and the importance of practice runs may be included.

[0282] Viewing and following advice

[0283] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[0284] Specific examples

[0285] For example, suppose a user is in the "Engineering" field, has "Project Management" skills, and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "Project Manager position at Company A." The emotion engine analyzes the user's reactions and language patterns at each step during the registration process, and detects that the user is highly dissatisfied with their current work situation.

[0286] For example, if a user is interested in a project manager position at Company A, they select that information. The server responds to that selection and generates resume-writing advice and interview strategies specific to Company A, reflecting the analysis results of the emotion engine. For example, advice such as "In your interview at Company A, give specific examples of successful project management experiences" or "Take several deep breaths before the interview to ease your nervousness" is displayed.

[0287] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, and also provides emotional support, allowing them to proceed with their job search efficiently and with peace of mind.

[0288] The processing flow will be explained below.

[0289] Step 1:

[0290] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[0291] Step 2:

[0292] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[0293] Step 3:

[0294] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[0295] Step 4:

[0296] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[0297] Step 5:

[0298] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[0299] Step 6:

[0300] Before the server sends the job listings to the user, it analyzes the user's emotional state using an emotion engine.

[0301] Step 7:

[0302] The emotion engine analyzes the user's input and selection history to identify their current emotional state (e.g., excitement, stress, relief, etc.).

[0303] Step 8:

[0304] The server customizes job listings based on the analysis results of the emotion engine. For example, if a user is judged to be highly stressed, job listings with a work environment deemed to be less stressful will be displayed first.

[0305] Step 9:

[0306] The server sends the customized job listings to the device.

[0307] Step 10:

[0308] The terminal displays the received job listings to the user, who can then click on the listings to view the details of the jobs.

[0309] Step 11:

[0310] When the user selects a job offer that interests them, the terminal transmits the selection information to the server.

[0311] Step 12:

[0312] The server receives the selected job information and generates job change advice specific to that job. The emotion engine customizes the advice taking into account the user's emotional state.

[0313] Step 13:

[0314] The server generates job-changing advice and sends it to the device, such as "Take several deep breaths and relax before the interview."

[0315] Step 14:

[0316] The device displays the received job change advice to the user, who can then use the advice to prepare for their job search.

[0317] Example 2

[0318] 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."

[0319] Conventional job-hunting support systems simply analyze and match information entered by users, making it difficult to fully consider the user's emotional state or provide personalized advice for job hunting. This often prevents users from receiving optimal advice tailored to their emotional state, increasing anxiety and stress during job hunting. Furthermore, the advice given is generally generic and unable to provide customized advice tailored to each user's situation.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0321] In this invention, the server includes means for a user to input a skill set and desired job-changing conditions, means for receiving the information input by the user and saving it in a database, means for converting the saved information into a standard format, means for analyzing the saved information using a natural language processing engine and selecting optimal job offers based on a matching algorithm, means for using an emotion engine to customize the selected job information based on the user's emotional state, and means for transmitting the customized job information to the user's terminal. This makes it possible to provide optimal job information and job-changing advice based on the user's emotional state and individual skill set.

[0322] "User" refers to an individual who uses the system to input their skill set and desired job search conditions and conducts a job search.

[0323] "Server" refers to a computer system for receiving input information from users and for storing, parsing, matching, and sentiment analysis.

[0324] A "skill set" refers to a specific collection of skills, knowledge, and experience that a user possesses.

[0325] "Desired conditions for changing jobs" refers to the conditions such as job type, work location, salary, etc. that a user desires when changing jobs.

[0326] A "natural language processing engine" refers to software that analyzes text information entered by a user and understands its meaning and intent.

[0327] "Matching algorithm" refers to a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[0328] An "emotion engine" refers to software that analyzes a user's input information and behavioral history and recognizes their emotional state.

[0329] "Database" refers to a data management system for systematically storing and managing user input information and job information.

[0330] "Job information" refers to detailed information about job types provided by companies.

[0331] "Career Advice" refers to information or advice that is useful to a user when applying for a particular job.

[0332] "Terminal" means a device through which a user accesses the system and inputs and receives information from the system.

[0333] The present invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions. A specific embodiment of this system is described below.

[0334] User registration and information entry

[0335] Users access the service's website or application and first enter their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. After entering this information, it is sent to the server via the device.

[0336] Information storage and preprocessing

[0337] The server receives the information entered by the user and stores it in a database. At this stage, the data is converted into a standard format. For example, work history data is formatted in a unified format, and skill set information is standardized. Specific software used here is the Pandas library in Python.

[0338] Information analysis and matching

[0339] The server analyzes the stored user information using a natural language processing engine (e.g., SpaCy or Google Cloud Natural Language API). Based on the analyzed data, it uses a matching algorithm (Collaborative Filtering or Content-Based Filtering) to select the most suitable job information from the database.

[0340] Emotion analysis using an emotion engine

[0341] An emotion engine (e.g., IBM Watson Emotion Analysis) is installed on the server. This engine analyzes the words entered by the user and their behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.). Specifically, it infers emotions from the user's comments and behavioral patterns and generates an optimal response.

[0342] Generating and displaying matching results

[0343] The server combines the analysis results with the emotion engine results to generate a job listing that is optimal for the user. For example, if the user is determined to be under stress, the listing will prioritize job listings with low-stress working environments. The generated listing is sent to the terminal, which displays it to the user. The user can review the displayed job listing and view detailed information.

[0344] Selection of job information and generation of career change advice

[0345] The user selects the job they are most interested in from the displayed job information. This selection is sent to the server via the terminal. The server generates specific job change advice based on the selected job information. This advice includes how to write an appropriate resume for the selected job and how to prepare for an interview. The results of the emotion engine are also reflected, so for example, advice on relaxation methods is included for "users who get nervous easily."

[0346] Viewing and following advice

[0347] The terminal receives the job change advice sent from the server and displays it to the user, allowing the user to prepare for specific job changes, such as creating a resume or rehearsing for an interview.

[0348] Specific examples

[0349] For example, suppose a user has the skills of "project management" in the "engineering" field and would like to work in a "major city." The user enters this information and sends it to the server via their device. The server analyzes this information and lists the most suitable job openings from its database. The emotion engine can detect, for example, that the user is feeling strong stress in their current work environment.

[0350] If a user is interested in "project manager positions at a specific company" and selects that information, the server generates specific advice based on the selection. For example, advice such as "In an interview with a specific company, give specific examples of successful project management" is displayed. Furthermore, if the emotion engine determines that the user tends to get nervous, relaxation techniques such as "take several deep breaths before the interview" are also included.

[0351] Prompt Sentence Examples

[0352] "Based on the user's input skillset and desired location, select the most suitable job offers from a database and prioritize them according to the user's current emotional state.

[0353] Skill Set: Project Management

[0354] Desired work location: Major city

[0355] "For the job posting selected by the user, generate advice on resume writing and interview preparation based on the analysis results of the sentiment engine.

[0356] Selective Job: Project Manager position at a specific company

[0357] Emotional state: Tendency

[0358] In this way, users can obtain job information that best suits their desired conditions, and also receive advice tailored to their own emotional state, allowing them to proceed with their job search efficiently and with peace of mind.

[0359] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0360] Step 1:

[0361] The user enters information. The user accesses the service's website or application and enters their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. The entered information is sent from the device to the server.

[0362] Input: Name, email address, password, work history, skill set, desired job conditions

[0363] Output: User information (sent to server)

[0364] What happens: A user fills in a form and clicks the submit button.

[0365] Step 2:

[0366] The server receives and stores the information. The server receives the information sent by the user and stores it in a database. The stored data converts the employment history data into a unified format and standardizes the skill set information.

[0367] Input: User information

[0368] Output: Standardized user information (stored in a database)

[0369] What happens: A server-side script processes the received information and stores it in a database.

[0370] Step 3:

[0371] The server analyzes the information. The server uses a natural language processing engine (such as SpaCy or Google Cloud Natural Language API) to analyze the user information stored in the database. Based on the analyzed data, a matching algorithm (such as Collaborative Filtering or Content-Based Filtering) is used to select the most suitable job information.

[0372] Input: Standardized user information

[0373] Output: Analysis results (data based on the user's skill set and desired conditions)

[0374] What it does: A natural language processing engine analyzes the user's input data to understand its meaning and intent.

[0375] Step 4:

[0376] The server performs emotion analysis using an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's input information and behavioral history to identify their emotional state (excitement, stress, relief, etc.).

[0377] Input: User comments and behavior history

[0378] Output: Emotion analysis results (identification of emotional state)

[0379] Specific operation: The emotion engine analyzes the user's text and behavioral patterns to calculate their emotional state.

[0380] Step 5:

[0381] The server generates matching results. The server combines the analysis results and the emotion engine results to generate the optimal job listings for the user. For users in a stressed state, job listings with low-stress working environments are prioritized.

[0382] Input: Analysis results, emotion analysis results

[0383] Output: A list of the best jobs

[0384] How it works: A server-side matching algorithm searches the database and aggregates jobs that match your criteria.

[0385] Step 6:

[0386] The server sends the job listing. The server then sends the generated job listing to the terminal, which displays it to the user. The user can then check the displayed job listing and view detailed information.

[0387] Input: Best Job Listings

[0388] Output: Display of job information (displayed on terminal)

[0389] Specific operation: The application on the terminal displays the job list received from the server on the screen.

[0390] Step 7:

[0391] The user selects the job information that interests them most from the displayed job information, and sends the selected information to the server via their terminal.

[0392] Input: User selected job posting

[0393] Output: Selected job information (sent to server)

[0394] Specific operation: The user clicks on the job posting that interests them and presses the select button.

[0395] Step 8:

[0396] The server generates career change advice. The server generates specific career change advice based on the selected job information. The advice includes how to write a resume and how to prepare for an interview, and also reflects the results of the emotion engine.

[0397] Input: Selected job postings, sentiment analysis results

[0398] Output: Job change advice

[0399] Specific operation: The server-side program generates appropriate advice based on job information and the user's emotional state.

[0400] Step 9:

[0401] The terminal displays the advice for job hunting. The terminal receives the advice from the server and displays it to the user. This allows the user to prepare for specific job hunting activities.

[0402] Input: Career change advice

[0403] Output: Display of job change advice (displayed on the terminal)

[0404] Specific operation: The application on the terminal displays the advice received from the server on the screen.

[0405] Through the above processing steps, the user can obtain job information that best suits their desired conditions, receive advice tailored to their own emotional state, and proceed with their job search efficiently and with peace of mind.

[0406] (Application example 2)

[0407] 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."

[0408] While conventional job-change support systems can provide job information based on a user's skill set and desired conditions, it is difficult to provide job information and advice that takes into account the user's emotional state. Furthermore, users have limited means to check the actual work environment in advance, making it difficult to understand the corporate culture and workplace atmosphere of the new employer, which increases the likelihood of mismatches after changing jobs. This creates a challenge for users, as they are unable to feel at ease when searching for a new job.

[0409] 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: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for the user to select the displayed job offers; means for the server to generate job-changing advice based on the selected job offers and send it to the terminal; means for recognizing the user's emotions; means for customizing and providing job offers based on the recognized emotions; means for allowing the user to tour a company's work environment in a virtual space; and means for displaying the job-changing advice on the terminal. This makes it possible to provide job offers and customized job-changing advice that take the user's emotional state into consideration. Furthermore, the virtual space allows the user to tour a company's work environment in advance, preventing mismatches with potential job seekers and allowing the user to proceed with their job-changing search with peace of mind.

[0410] A "skill set" is a collection of specialized abilities and techniques possessed by a user.

[0411] "Desired conditions for changing jobs" refers to the type of job, work location, working conditions, and other requirements that a user desires in a new job.

[0412] "Server" means a computer system that processes information received from users and stores and analyzes data.

[0413] A "database" is a digital storage device that systematically stores user input information and job information.

[0414] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[0415] "Emotion recognition" is a technology that analyzes a user's emotional state from their facial expressions and behavior.

[0416] A "virtual space" is a virtual three-dimensional environment generated by computer simulation.

[0417] "Career change advice" is advice on applying for and preparing for interviews for jobs selected by the user.

[0418] A "terminal" is an electronic device through which a user inputs information and receives output from a system.

[0419] A specific system for implementing this invention provides optimal job information based on the user's skill set and desired job-changing conditions, and also provides job-changing advice that takes into account the user's emotional state. Below, we will create a program for this system and explain its processing in natural language.

[0420] System Configuration

[0421] 1. Server:

[0422] The server receives the skill set and desired job conditions entered by the user and stores them in a database.

[0423] The database stores all user and job information in an organized manner.

[0424] The server analyzes the received information using natural language processing and selects the most suitable job information using a matching algorithm.

[0425] It is equipped with an emotion recognition engine that analyzes the user's emotional state from their facial expressions and behavior.

[0426] Job information selected based on a matching algorithm is customized taking into account the user's emotional state and sent to the terminal.

[0427] 2. Terminal:

[0428] It provides an interface for users to input their skill sets and desired job search conditions.

[0429] Job information sent from the server is displayed, and the user can select from it.

[0430] The job change advice sent from the server is displayed, and appropriate advice is provided to the user.

[0431] Users can access the virtual space through their devices and tour the corporate work environment.

[0432] Main hardware and software used

[0433] Hardware: The server is a computer system with a powerful processor and large storage capacity. The user device is an electronic device such as a smartphone, tablet, or smart glasses.

[0434] Software: Python libraries (e.g., nltk, spaCy) are used for natural language processing. Libraries such as OpenCV and TensorFlow are used for emotion recognition. The virtual space is built using the Unity engine.

[0435] Specific examples

[0436] A user uses a smartphone to enter their skill set (e.g., engineering, project management) and desired job conditions (e.g., work location: Tokyo) into the application. This information is sent to the server and stored in a database. The server analyzes the received information using natural language processing and selects the most suitable job information (e.g., project manager position) from the database. An emotion recognition engine analyzes the user's facial expression data and detects their current emotional state (e.g., high stress).

[0437] For example, if a user is feeling stressed, the server will customize the display to prioritize job listings that encourage relaxation. Additionally, while the user is touring the workplace in the virtual space, the server will change the appropriate explanations and guidance based on the user's emotional state. If the user is interested in a selected job listing, the server will provide customized advice on how to change jobs (e.g., "Take several deep breaths before the interview") based on that information.

[0438] Example prompt sentence:

[0439] Create prompts that help users surface relevant job listings and generate customized career advice based on sentiment data.

[0440] User skills: Engineering, Project Management

[0441] Preferred location: Tokyo

[0442] I am dissatisfied with my current work situation

[0443] This allows users to receive emotional support and proceed with their job search with peace of mind.

[0444] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0445] Step 1:

[0446] The user inputs their skill set and desired job search conditions. Using the interface of a device such as a smartphone or tablet, the user inputs their work history, skill set (e.g., engineering, project management), and desired job search conditions (e.g., work location in Tokyo). The input information is sent from the device to the server.

[0447] Step 2:

[0448] The server receives the information sent by the user and stores it in a database. When the server receives the user's input information, it converts it into a standard format and stores it in a database. This database is used to systematically manage all user information and job information. Pre-processing is performed to format the input data and prepare the storage location.

[0449] Step 3:

[0450] The server analyzes the stored information using natural language processing (NLP). The server uses NLP techniques to analyze the user's work history, skill set, and desired job conditions to extract the user's strengths and characteristics. This analysis uses Python libraries (e.g., nltk, spaCy) to analyze the text of the input data and structure it.

[0451] Step 4:

[0452] The server selects the most suitable job offer based on a matching algorithm. The analyzed user information is compared with the job information in the database, and the matching algorithm (e.g., recommender system) selects the most suitable job offer for the user. The matching algorithm compares the user's requirements with the job offer requirements and lists the most suitable offers.

[0453] Step 5:

[0454] The server customizes the selected job listings using an emotion recognition engine. The server recognizes the user's emotional state in real time and customizes the job listings based on that. Emotion recognition involves capturing facial expression data and analyzing it using an AI model (e.g., an emotion recognition model using TensorFlow). If the user is feeling stressed, job listings that help them relax will be prioritized.

[0455] Step 6:

[0456] The server selects and sends customized job information to the terminal. The customized job information is then sent from the server to the user's terminal. The terminal outputs the received information in a format that is displayed to the user. The user can view the most suitable job information on the terminal screen.

[0457] Step 7:

[0458] The user selects the job information they are interested in from the displayed job information. The user looks at the list of job information displayed on the terminal and selects the information they are interested in. The selected information is then sent back to the server from the terminal.

[0459] Step 8:

[0460] The server generates career change advice based on the selected job information. The server generates career change advice based on the job information selected by the user and the emotion recognition results. This advice is created by an AI model (e.g., using a natural language generation model) and includes specific advice, such as how to calm nerves before an interview.

[0461] Step 9:

[0462] The server sends the generated job change advice to the terminal. The job change advice is sent from the server to the user's terminal, and the terminal displays it. The user can refer to the advice and conduct more effective job change activities.

[0463] Step 10:

[0464] Users can tour a company's work environment in a virtual space. Using their devices, users can access the virtual space and experience a realistic tour of the company's work environment. The virtual space was built using the Unity engine and is designed to allow users to tour interactively. During the tour, an emotion recognition system monitors the user's reactions and changes the route as necessary.

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

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

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

[0468] [Second embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0481] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI to replace the work traditionally performed by job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[0482] Specific system configuration and processing explanation

[0483] User registration and information entry

[0484] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[0485] Information storage and analysis

[0486] The server receives the information entered by the user and stores it in a database. The received information is then analyzed using an analysis engine to analyze the user's skill set, work history, and desired conditions using natural language processing. Based on the analyzed information, a matching algorithm selects the most suitable job opening from the database.

[0487] Generating and displaying matching results

[0488] The server generates a job listing that best suits the user based on a matching algorithm and transmits the listing to the user's terminal, which then displays the listing to the user, allowing the user to view details of the displayed job listings.

[0489] Selection of job information and provision of countermeasures advice

[0490] The user selects the job they are most interested in from the displayed job information. The selected information is sent from the device to the server. The server then generates career change advice for the job based on this selection information. Specifically, the advice is provided tailored to the skill set required by the company, such as how to write a resume and what to emphasize in an interview.

[0491] Viewing and following advice

[0492] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[0493] Specific examples

[0494] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "project manager position at Company A." These job openings are again displayed to the user via their device, and if the user views the details and becomes interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the user via their device. For example, advice such as "Describe specific examples of successful project management" is displayed.

[0495] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, making job hunting more efficient.

[0496] The processing flow will be explained below.

[0497] Step 1:

[0498] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[0499] Step 2:

[0500] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[0501] Step 3:

[0502] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[0503] Step 4:

[0504] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[0505] Step 5:

[0506] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[0507] Step 6:

[0508] The server sends the job listing to the terminal. The information sent is encrypted in response format.

[0509] Step 7:

[0510] The terminal displays the received job list to the user, who then clicks on the details of the job that interests them.

[0511] Step 8:

[0512] When the user selects a job offer that he or she wishes to view, the terminal transmits the selected job offer information to the server.

[0513] Step 9:

[0514] The server receives the selected job information and generates career change advice specific to the job, including tips on how to prepare for an interview and how to write a resume.

[0515] Step 10:

[0516] The server generates and sends the advice to the terminal. The advice information is encrypted.

[0517] Step 11:

[0518] The device displays the received advice to the user, who can then use this advice to prepare for specific job hunting activities.

[0519] Explanation with concrete examples

[0520] Step 1:

[0521] The user accesses the app and enters their name, email address, password, work history (e.g., "Engineer, ABC Company, 3 years"), skill set (e.g., "Java, project management"), and desired job conditions (e.g., "Project manager, Tokyo, annual salary of 6 million yen or more") on the new registration screen.

[0522] Step 2:

[0523] The terminal sends the above input information to the server.

[0524] Step 3:

[0525] The server stores the input information in a database.

[0526] Step 4:

[0527] The server runs the input information through a natural language processing engine to analyze skills and work history.

[0528] Step 5:

[0529] The server lists the most suitable job information based on the analysis results.

[0530] Step 6:

[0531] The server sends the most suitable job listings to the device.

[0532] Step 7:

[0533] The device displays a list of job listings to the user, such as "Project Manager position at Company D" or "Senior Engineer position at Company E."

[0534] Step 8:

[0535] The user selects "Project Manager position at Company D."

[0536] Step 9:

[0537] The server receives the selected job information and generates advice on interview preparation and resume writing specific to Company D.

[0538] Step 10:

[0539] The server generates job change advice and sends it to the terminal.

[0540] Step 11:

[0541] The device will display advice to the user, such as "In your interview with Company D, emphasize specific examples of successful project management" or "It is recommended that you include detailed information about your leadership experience in your resume."

[0542] Example 1

[0543] 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."

[0544] Traditional career change support services are often provided through recruitment agencies, but the quality and response speed of the services provided by these agencies vary. They also lack efficient methods for matching users with the right skills and desired conditions. Furthermore, when it comes to career change strategies, they often provide general advice, without providing specific advice tailored to individual job openings.

[0545] 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.

[0546] In this invention, the server includes a means for a user to input information, a means for receiving the information input by the user and storing it in a data storage, a means for analyzing the stored information in the server and selecting an optimal job based on a matching algorithm, a means for transmitting the selected job information to the user's device, a means for displaying the job information on the device, a means for the user to select the displayed job information, a means for generating career change advice based on the selected job in the server and transmitting it to the device, and a means for displaying the career change advice on the device. This allows users to efficiently find a job that best suits their skill set and desired conditions without relying on traditional career change agents. Furthermore, by providing specific career change advice tailored to individual job openings, the user's success rate in changing jobs can be improved.

[0547] "User" refers to an individual who uses the system to search for a new job.

[0548] "Information" refers to data entered by the user, such as skill set, desired job conditions, and work history.

[0549] "Server" refers to a computer system that receives information sent by a user, stores it in data storage, analyzes it, and provides appropriate services.

[0550] "Data Storage" refers to a data storage device or database for storing information received from a user.

[0551] A "matching algorithm" refers to a calculation method or program for selecting the most suitable job based on user information.

[0552] "Job information" refers to information about jobs stored on the server, including job type, job content, working conditions, etc.

[0553] "Device" refers to hardware such as a computer, tablet, or smartphone that a user uses to access the system.

[0554] "Career change advice" refers to advice and suggestions that are generated by the server and provided to users to help them with their job search.

[0555] "Natural language processing" refers to a computer science technique for analyzing textual information entered by a user and understanding its meaning.

[0556] A "skill set" refers to the qualifications, experience, and abilities that a company is looking for.

[0557] This invention is a job change support system that helps users efficiently find a job that suits them. This system uses advanced analytical means and matching algorithms to provide optimal job information based on the user's skill set and desired job change conditions, and also provides advice on how to change jobs.

[0558] Specifically, the system consists of the following elements:

[0559] 1. User Interface

[0560] Users enter information about themselves through a website or application, including their name, email address, password, work history, skill set, and job preferences. The information is collected using HTML forms and validated using JavaScript.

[0561] 2. Receipt and storage of information

[0562] The terminal sends the information entered by the user to the server, which then stores the received information in data storage (e.g., MySQL or PostgreSQL). This step uses encoding and encryption techniques to ensure that user information is stored safely and efficiently.

[0563] 3. Information analysis

[0564] The server analyzes the stored information using Python, PySpark, etc. Natural language processing (NLP) techniques are used for this analysis. Specifically, libraries such as SpaCy and NLTK are used to analyze the user's skill set, work history, and desired conditions through tokenization, part-of-speech tagging, and named entity recognition.

[0565] 4. Matching Algorithm

[0566] The server then applies a matching algorithm based on the analysis results, using machine learning models (e.g., SVM and decision tree algorithms) using the Scikit-learn library. Suitable job postings are selected from the database and listed.

[0567] 5. Submitting and Displaying Job Postings

[0568] The server sends the generated job listings in JSON format to the device, which receives the information and displays it on the user's screen using a front-end framework such as React or Vue.js.

[0569] 6. Job information selection and job change advice generation

[0570] The user selects the job they are interested in from the displayed job information. This selection information is also sent from the device to the server. Based on the selected job, the server uses an analysis engine written in a Python program or similar to generate career change advice tailored to the job.

[0571] 7. Advice Display

[0572] The job-changing advice sent from the server is displayed on the device, and users can refer to this advice to smoothly proceed with their specific job-changing activities.

[0573] Specific examples

[0574] For example, imagine a user has the skill of "project management" in the field of "engineering" and would like to work in "Tokyo." The user enters this information into the system and sends it to the server via their terminal. The server analyzes this information, compiles a list of suitable job openings from the database, such as "project manager position at company X," and sends it to the terminal. If the user is interested in "project manager position at company X" and selects that information, the server will respond to the selection and generate resume writing advice and interview preparation specific to company X, and send it to the terminal. For example, advice such as "Describe specific examples of successful project management" will be displayed.

[0575] Prompt Sentence Examples

[0576] "If a user has the skill "Project Management" in the field of "Engineering" and desires to work in "Tokyo," please explain in detail the steps required to generate suitable job offers and career advice. Please also mention the specific actions for each step."

[0577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0578] Step 1:

[0579] Users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job conditions on the registration screen. The entered information is collected on the web page through an HTML form and validated using JavaScript.

[0580] Input: User's personal information, work history, skill set, job search requirements

[0581] Output: Validated user information

[0582] Specific behavior:

[0583] The terminal receives input from the user and uses JavaScript to check whether the form has been filled out correctly.

[0584] If validation is successful, the form data is encoded and sent to the server using an AJAX request.

[0585] Step 2:

[0586] The server stores the received user information in a data storage (such as MySQL or PostgreSQL), during which the data is encoded and encrypted as necessary.

[0587] Input: Validated user information

[0588] Output: User information saved in data storage

[0589] Specific behavior:

[0590] The server decodes the data received from the AJAX request and takes measures against SQL injection.

[0591] Executes an INSERT statement against the database to securely store the user information.

[0592] Step 3:

[0593] The server analyzes the stored user information, using natural language processing (NLP) techniques such as Python and PySpark to analyze the user's skill set, work history, and desired conditions.

[0594] Input: User information stored in data storage

[0595] Output: Parsed user information (e.g., JSON format)

[0596] Specific behavior:

[0597] The server reads user information from a database and uses SpaCy and NLTK for tokenization, part-of-speech tagging, and named entity recognition.

[0598] The parsed results are converted to JSON format and saved for further processing.

[0599] Step 4:

[0600] The server applies a matching algorithm based on the analyzed information to select the most suitable job postings, specifically by running machine learning models (e.g., SVMs and decision trees) using the Scikit-learn library.

[0601] Input: Parsed user information

[0602] Output: List of matching jobs (e.g., in JSON format)

[0603] Specific behavior:

[0604] The server compares the parsed user information with job listings stored in a database and applies a matching algorithm.

[0605] Select the most suitable job information, convert it to JSON format and save it.

[0606] Step 5:

[0607] The server sends a list of matching jobs in JSON format to the device, which then displays the received job information in a user interface using front-end frameworks such as React and Vue.js.

[0608] Input: List of matching jobs (e.g., in JSON format)

[0609] Output: The job displayed in the user interface

[0610] Specific behavior:

[0611] The server encodes the job information in JSON format and sends it to the terminal as an HTTP response.

[0612] The device receives the job information, renders it in HTML using React or Vue.js, and displays it on the user's screen.

[0613] Step 6:

[0614] The user selects from the displayed job information the job they are interested in. This selection information is sent from the terminal to the server.

[0615] Input: Job listing selected by user

[0616] Output: Selections sent to the server

[0617] Specific behavior:

[0618] The terminal records the user's selection and transmits the selected job information in an encoded form to the server.

[0619] The server decodes the received selection information and prepares for the next process.

[0620] Step 7:

[0621] The server generates job-change advice based on the selected job information, using an analysis engine written in Python to provide advice specific to the job.

[0622] Input: Job listing selected by user

[0623] Output: Generated job-changing advice (e.g., JSON format)

[0624] Specific behavior:

[0625] The server parses the selected job postings and generates recommendations in a Python script.

[0626] The generated advice is encoded in JSON format and sent to the device.

[0627] Step 8:

[0628] The terminal displays the job change advice sent from the server to the user.

[0629] Input: Generated job change advice (e.g., JSON format)

[0630] Output: Career change advice displayed in a user interface

[0631] Specific behavior:

[0632] The terminal receives the advisory information and visualizes it to the user using HTML and CSS.

[0633] The user can refer to the displayed advice and use it to help with their job search.

[0634] (Application example 1)

[0635] 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."

[0636] Conventional job-hunting support systems are only available online, making them inadequate for job seekers who prefer to receive in-person support in a brick-and-mortar store. Furthermore, when it comes to providing job information and career advice, the same content is provided to all users, and it is not customized to fit individual skill sets or desired conditions. This often results in inefficient job hunting.

[0637] 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.

[0638] In this invention, the server includes: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information in the server and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for a user to select displayed job offers; means for generating job-changing advice based on the selected job offers and transmitting it to the terminal; means for displaying the job-changing advice on the terminal; means for executing processes from information input to display of job-changing advice via a smartphone app in a physical store; and means for generating job offers and job-changing advice using prompt sentences generated by a generative AI model. This enables direct support in physical stores and makes it possible to provide job offers and job offers and advice customized to individual job seekers.

[0639] A "user" is an individual who uses the system to input their skill set and desired job-changing conditions and receives job information and advice on career changes.

[0640] A "skill set" is a collection of skills and abilities related to a user's job or work.

[0641] "Desired conditions for changing jobs" are conditions such as the place of work, job type, salary, etc. that the user desires when changing jobs.

[0642] The "server" is a central management device that receives and stores information entered by users, analyzes it, selects job information, and generates career change advice.

[0643] "Database" refers to the storage area within the system for storing information entered by users and job information.

[0644] A "matching algorithm" is a calculation method or procedure for selecting the most suitable job offer based on a user's skill set and desired job change conditions.

[0645] A "terminal" is an electronic device that a user uses to display job information and career change advice, and to transmit input information.

[0646] "Job information" refers to information provided by companies, such as job content, required skills, work location, and salary.

[0647] "Career change advice" is advice on how to prepare a resume and interview for a job that the user is looking for.

[0648] A "physical store" is a physical location where job seekers can visit in person and receive job change support services using the system.

[0649] A "smartphone app" is software that runs on a smartphone and allows users to use the system to input their skill set and desired job-changing conditions, and receive job information and advice on how to change jobs.

[0650] A "generative AI model" is an artificial intelligence technology that generates prompts based on user input and customizes job information and career change advice.

[0651] A "prompt" is text generated by a generative AI model, and is an instructional sentence that provides job information and career change advice.

[0652] This invention is a job change support system that uses AI. Users can input their skill set and desired job change conditions via a smartphone app at a physical store, obtain the most suitable job information, and receive effective advice on how to change jobs.

[0653] Overall system configuration

[0654] 1. User registration and information entry

[0655] Users use a smartphone app installed in a physical store to enter information such as their name, email address, password, work history, skill set, and desired job conditions. The information entered is sent to and stored on a cloud server in real time.

[0656] 2. Analysis of Information

[0657] The server stores the received information in a database and uses a natural language processing engine (Google Cloud Natural Language API) to analyze the skillset and desired job conditions. The analyzed information is stored as structured data for use in the next step.

[0658] 3. Matching and job information provision

[0659] The server uses an AI matching algorithm (TensorFlow) to select suitable job offers based on the analyzed user information. The selected job offers are sent to the user's smartphone in real time and displayed to the user.

[0660] 4. Selection of job information and advice on countermeasures

[0661] When a user selects a job posting, the selection is sent to the server. The server generates job-changing advice specific to the company based on the selection. At this time, a generative AI model is used to generate a prompt message, and advice reflecting that message is created.

[0662] The generated advice for career change is sent back to the smartphone and displayed to the user.

[0663] Specific examples

[0664] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in an "urban area." The user enters this information into a smartphone app, which then sends it to the server. The server analyzes this information and lists suitable job postings from its database, such as "project manager position at Company A." The listed job postings are displayed on the smartphone, and if the user is interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the smartphone. For example, advice such as "Describe specific examples of successful project management practices" is displayed.

[0665] Prompt Sentence Examples

[0666] As a concrete example, the following prompt sentence is input to the generative AI model:

[0667] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[0668] Based on this prompt, the AI ​​model generates relevant job information and career change advice.

[0669] With the introduction of this system, job seekers will be able to efficiently conduct their job search even at physical stores, and will be able to receive individually customized job information and career change advice via a smartphone app.

[0670] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0671] Step 1:

[0672] Users use a smartphone app installed in a physical store to input their skill set and desired job conditions. At this time, users enter information such as their name, email address, password, work history, skill set, and desired job conditions into the app. The input information is sent in real time to a server on the cloud. This step also involves verifying the input data and checking for required fields.

[0673] input:

[0674] Name, email address, password, work history, skill set, desired job conditions

[0675] output:

[0676] User information sent to the cloud server

[0677] Step 2:

[0678] The server stores the received user information in a database. At the same time, the stored information is analyzed using a natural language processing engine (Google Cloud Natural Language API). This analysis extracts skill sets and desired job conditions as structured data.

[0679] input:

[0680] User Information

[0681] output:

[0682] Structured data stored in a database

[0683] Step 3:

[0684] The server uses an AI matching algorithm (TensorFlow) to select the most suitable job postings based on the analyzed user structured data. The selection process involves referencing a job posting database to find the job that best suits the user's skill set and desired job change conditions.

[0685] input:

[0686] Structured data, job information database

[0687] output:

[0688] Best job listings

[0689] Step 4:

[0690] The server sends the selected job listings to the user's smartphone, where they are displayed and the user can review them. Here, job seekers can view the details of various job listings and select the one that best suits them.

[0691] input:

[0692] Best job listings

[0693] output:

[0694] Job information displayed on a smartphone

[0695] Step 5:

[0696] Once a user selects the job postings they are interested in, the selection is sent to the server, which then generates job-changing advice specific to the company using a generative AI model to generate prompts and customize the advice accordingly.

[0697] input:

[0698] User-selected job listings

[0699] output:

[0700] Generated career change advice

[0701] Step 6:

[0702] The server then sends the generated job-changing advice back to the smartphone, where the user can check the advice and use it to prepare for their resume or interview.

[0703] input:

[0704] Generated career change advice

[0705] output:

[0706] Job change advice displayed on smartphones

[0707] For example, if the user name is "Yamada Taro" and the desired job is "software developer" and "work in an urban area," the following prompt sentence will be input to the generative AI model:

[0708] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[0709] Based on this prompt, the AI ​​model generates relevant job information and career change advice, which are then provided to the user.

[0710] These specific processing steps enable users to efficiently conduct job hunting activities even at brick-and-mortar stores, and receive individually customized job information and career change advice via a smartphone app.

[0711] 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.

[0712] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[0713] Specific system configuration and processing explanation

[0714] User registration and information entry

[0715] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[0716] Information storage and analysis

[0717] The server receives the information entered by the user and stores it in a database. The received information is converted into a standard format by a pre-processing program, and then the analysis engine analyzes the user's skill set, work history, and desired conditions using natural language processing. Based on this, a matching algorithm selects the most suitable job opening from the database.

[0718] Introducing emotion engine analysis

[0719] The server also incorporates an emotion engine that recognizes emotions from user input and selection history. The emotion engine analyzes the user's input words and behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.).

[0720] Generating and displaying matching results

[0721] The server generates a list of job offers that best suit the user based on a matching algorithm and sends that list to the device. By taking into account the analysis results of the emotion engine, it is possible to customize the display of job information that is more appropriate to the user's current emotional state. For example, if a user is judged to be highly stressed, job offers with work environments that are deemed to be less stressful will be displayed preferentially.

[0722] The terminal displays the sent job listing to the user, and the user can view the details of the displayed job listing.

[0723] Selection of job information and provision of countermeasures advice

[0724] The user selects the job that interests them most from the displayed job information. The selected information is sent from the terminal to the server. Based on this selection, the server generates job change advice for the job. This advice is also customized taking into account the user's emotional state. For example, if the user tends to get nervous, advice on relaxation techniques and the importance of practice runs may be included.

[0725] Viewing and following advice

[0726] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[0727] Specific examples

[0728] For example, suppose a user is in the "Engineering" field, has "Project Management" skills, and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "Project Manager position at Company A." The emotion engine analyzes the user's reactions and language patterns at each step during the registration process, and detects that the user is highly dissatisfied with their current work situation.

[0729] For example, if a user is interested in a project manager position at Company A, they select that information. The server responds to that selection and generates resume-writing advice and interview strategies specific to Company A, reflecting the analysis results of the emotion engine. For example, advice such as "In your interview at Company A, give specific examples of successful project management experiences" or "Take several deep breaths before the interview to ease your nervousness" is displayed.

[0730] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, and also provides emotional support, allowing them to proceed with their job search efficiently and with peace of mind.

[0731] The processing flow will be explained below.

[0732] Step 1:

[0733] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[0734] Step 2:

[0735] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[0736] Step 3:

[0737] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[0738] Step 4:

[0739] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[0740] Step 5:

[0741] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[0742] Step 6:

[0743] Before the server sends the job listings to the user, it analyzes the user's emotional state using an emotion engine.

[0744] Step 7:

[0745] The emotion engine analyzes the user's input and selection history to identify their current emotional state (e.g., excitement, stress, relief, etc.).

[0746] Step 8:

[0747] The server customizes job listings based on the analysis results of the emotion engine. For example, if a user is judged to be highly stressed, job listings with a work environment deemed to be less stressful will be displayed first.

[0748] Step 9:

[0749] The server sends the customized job listings to the device.

[0750] Step 10:

[0751] The terminal displays the received job listings to the user, who can then click on the listings to view the details of the jobs.

[0752] Step 11:

[0753] When the user selects a job offer that interests them, the terminal transmits the selection information to the server.

[0754] Step 12:

[0755] The server receives the selected job information and generates job change advice specific to that job. The emotion engine customizes the advice taking into account the user's emotional state.

[0756] Step 13:

[0757] The server generates job-changing advice and sends it to the device, such as "Take several deep breaths and relax before the interview."

[0758] Step 14:

[0759] The device displays the received job change advice to the user, who can then use the advice to prepare for their job search.

[0760] Example 2

[0761] 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."

[0762] Conventional job-hunting support systems simply analyze and match information entered by users, making it difficult to fully consider the user's emotional state or provide personalized advice for job hunting. This often prevents users from receiving optimal advice tailored to their emotional state, increasing anxiety and stress during job hunting. Furthermore, the advice given is generally generic and unable to provide customized advice tailored to each user's situation.

[0763] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0764] In this invention, the server includes means for a user to input a skill set and desired job-changing conditions, means for receiving the information input by the user and saving it in a database, means for converting the saved information into a standard format, means for analyzing the saved information using a natural language processing engine and selecting optimal job offers based on a matching algorithm, means for using an emotion engine to customize the selected job information based on the user's emotional state, and means for transmitting the customized job information to the user's terminal. This makes it possible to provide optimal job information and job-changing advice based on the user's emotional state and individual skill set.

[0765] "User" refers to an individual who uses the system to input their skill set and desired job search conditions and conducts a job search.

[0766] "Server" refers to a computer system for receiving input information from users and for storing, parsing, matching, and sentiment analysis.

[0767] A "skill set" refers to a specific collection of skills, knowledge, and experience that a user possesses.

[0768] "Desired conditions for changing jobs" refers to the conditions such as job type, work location, salary, etc. that a user desires when changing jobs.

[0769] A "natural language processing engine" refers to software that analyzes text information entered by a user and understands its meaning and intent.

[0770] "Matching algorithm" refers to a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[0771] An "emotion engine" refers to software that analyzes a user's input information and behavioral history and recognizes their emotional state.

[0772] "Database" refers to a data management system for systematically storing and managing user input information and job information.

[0773] "Job information" refers to detailed information about job types provided by companies.

[0774] "Career Advice" refers to information or advice that is useful to a user when applying for a particular job.

[0775] "Terminal" means a device through which a user accesses the system and inputs and receives information from the system.

[0776] The present invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions. A specific embodiment of this system is described below.

[0777] User registration and information entry

[0778] Users access the service's website or application and first enter their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. After entering this information, it is sent to the server via the device.

[0779] Information storage and preprocessing

[0780] The server receives the information entered by the user and stores it in a database. At this stage, the data is converted into a standard format. For example, work history data is formatted in a unified format, and skill set information is standardized. Specific software used here is the Pandas library in Python.

[0781] Information analysis and matching

[0782] The server analyzes the stored user information using a natural language processing engine (e.g., SpaCy or Google Cloud Natural Language API). Based on the analyzed data, it uses a matching algorithm (Collaborative Filtering or Content-Based Filtering) to select the most suitable job information from the database.

[0783] Emotion analysis using an emotion engine

[0784] An emotion engine (e.g., IBM Watson Emotion Analysis) is installed on the server. This engine analyzes the words entered by the user and their behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.). Specifically, it infers emotions from the user's comments and behavioral patterns and generates an optimal response.

[0785] Generating and displaying matching results

[0786] The server combines the analysis results with the emotion engine results to generate a job listing that is optimal for the user. For example, if the user is determined to be under stress, the listing will prioritize job listings with low-stress working environments. The generated listing is sent to the terminal, which displays it to the user. The user can review the displayed job listing and view detailed information.

[0787] Selection of job information and generation of career change advice

[0788] The user selects the job they are most interested in from the displayed job information. This selection is sent to the server via the terminal. The server generates specific job change advice based on the selected job information. This advice includes how to write an appropriate resume for the selected job and how to prepare for an interview. The results of the emotion engine are also reflected, so for example, advice on relaxation methods is included for "users who get nervous easily."

[0789] Viewing and following advice

[0790] The terminal receives the job change advice sent from the server and displays it to the user, allowing the user to prepare for specific job changes, such as creating a resume or rehearsing for an interview.

[0791] Specific examples

[0792] For example, suppose a user has the skills of "project management" in the "engineering" field and would like to work in a "major city." The user enters this information and sends it to the server via their device. The server analyzes this information and lists the most suitable job openings from its database. The emotion engine can detect, for example, that the user is feeling strong stress in their current work environment.

[0793] If a user is interested in "project manager positions at a specific company" and selects that information, the server generates specific advice based on the selection. For example, advice such as "In an interview with a specific company, give specific examples of successful project management" is displayed. Furthermore, if the emotion engine determines that the user tends to get nervous, relaxation techniques such as "take several deep breaths before the interview" are also included.

[0794] Prompt Sentence Examples

[0795] "Based on the user's input skillset and desired location, select the most suitable job offers from a database and prioritize them according to the user's current emotional state.

[0796] Skill Set: Project Management

[0797] Desired work location: Major city

[0798] "For the job posting selected by the user, generate advice on resume writing and interview preparation based on the analysis results of the sentiment engine.

[0799] Selective Job: Project Manager position at a specific company

[0800] Emotional state: Tendency

[0801] In this way, users can obtain job information that best suits their desired conditions, and also receive advice tailored to their own emotional state, allowing them to proceed with their job search efficiently and with peace of mind.

[0802] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0803] Step 1:

[0804] The user enters information. The user accesses the service's website or application and enters their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. The entered information is sent from the device to the server.

[0805] Input: Name, email address, password, work history, skill set, desired job conditions

[0806] Output: User information (sent to server)

[0807] What happens: A user fills in a form and clicks the submit button.

[0808] Step 2:

[0809] The server receives and stores the information. The server receives the information sent by the user and stores it in a database. The stored data converts the employment history data into a unified format and standardizes the skill set information.

[0810] Input: User information

[0811] Output: Standardized user information (stored in a database)

[0812] What happens: A server-side script processes the received information and stores it in a database.

[0813] Step 3:

[0814] The server analyzes the information. The server uses a natural language processing engine (such as SpaCy or Google Cloud Natural Language API) to analyze the user information stored in the database. Based on the analyzed data, a matching algorithm (such as Collaborative Filtering or Content-Based Filtering) is used to select the most suitable job information.

[0815] Input: Standardized user information

[0816] Output: Analysis results (data based on the user's skill set and desired conditions)

[0817] What it does: A natural language processing engine analyzes the user's input data to understand its meaning and intent.

[0818] Step 4:

[0819] The server performs emotion analysis using an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's input information and behavioral history to identify their emotional state (excitement, stress, relief, etc.).

[0820] Input: User comments and behavior history

[0821] Output: Emotion analysis results (identification of emotional state)

[0822] Specific operation: The emotion engine analyzes the user's text and behavioral patterns to calculate their emotional state.

[0823] Step 5:

[0824] The server generates matching results. The server combines the analysis results and the emotion engine results to generate the optimal job listings for the user. For users in a stressed state, job listings with low-stress working environments are prioritized.

[0825] Input: Analysis results, emotion analysis results

[0826] Output: A list of the best jobs

[0827] How it works: A server-side matching algorithm searches the database and aggregates jobs that match your criteria.

[0828] Step 6:

[0829] The server sends the job listing. The server then sends the generated job listing to the terminal, which displays it to the user. The user can then check the displayed job listing and view detailed information.

[0830] Input: Best Job Listings

[0831] Output: Display of job information (displayed on terminal)

[0832] Specific operation: The application on the terminal displays the job list received from the server on the screen.

[0833] Step 7:

[0834] The user selects the job information that interests them most from the displayed job information, and sends the selected information to the server via their terminal.

[0835] Input: User selected job posting

[0836] Output: Selected job information (sent to server)

[0837] Specific operation: The user clicks on the job posting that interests them and presses the select button.

[0838] Step 8:

[0839] The server generates career change advice. The server generates specific career change advice based on the selected job information. The advice includes how to write a resume and how to prepare for an interview, and also reflects the results of the emotion engine.

[0840] Input: Selected job postings, sentiment analysis results

[0841] Output: Job change advice

[0842] Specific operation: The server-side program generates appropriate advice based on job information and the user's emotional state.

[0843] Step 9:

[0844] The terminal displays the advice for job hunting. The terminal receives the advice from the server and displays it to the user. This allows the user to prepare for specific job hunting activities.

[0845] Input: Career change advice

[0846] Output: Display of job change advice (displayed on the terminal)

[0847] Specific operation: The application on the terminal displays the advice received from the server on the screen.

[0848] Through the above processing steps, the user can obtain job information that best suits their desired conditions, receive advice tailored to their own emotional state, and proceed with their job search efficiently and with peace of mind.

[0849] (Application example 2)

[0850] 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."

[0851] While conventional job-change support systems can provide job information based on a user's skill set and desired conditions, it is difficult to provide job information and advice that takes into account the user's emotional state. Furthermore, users have limited means to check the actual work environment in advance, making it difficult to understand the corporate culture and workplace atmosphere of the new employer, which increases the likelihood of mismatches after changing jobs. This creates a challenge for users, as they are unable to feel at ease when searching for a new job.

[0852] 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: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for the user to select the displayed job offers; means for the server to generate job-changing advice based on the selected job offers and send it to the terminal; means for recognizing the user's emotions; means for customizing and providing job offers based on the recognized emotions; means for allowing the user to tour a company's work environment in a virtual space; and means for displaying the job-changing advice on the terminal. This makes it possible to provide job offers and customized job-changing advice that take the user's emotional state into consideration. Furthermore, the virtual space allows the user to tour a company's work environment in advance, preventing mismatches with potential job seekers and allowing the user to proceed with their job-changing search with peace of mind.

[0853] A "skill set" is a collection of specialized abilities and techniques possessed by a user.

[0854] "Desired conditions for changing jobs" refers to the type of job, work location, working conditions, and other requirements that a user desires in a new job.

[0855] "Server" means a computer system that processes information received from users and stores and analyzes data.

[0856] A "database" is a digital storage device that systematically stores user input information and job information.

[0857] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[0858] "Emotion recognition" is a technology that analyzes a user's emotional state from their facial expressions and behavior.

[0859] A "virtual space" is a virtual three-dimensional environment generated by computer simulation.

[0860] "Career change advice" is advice on applying for and preparing for interviews for jobs selected by the user.

[0861] A "terminal" is an electronic device through which a user inputs information and receives output from a system.

[0862] A specific system for implementing this invention provides optimal job information based on the user's skill set and desired job-changing conditions, and also provides job-changing advice that takes into account the user's emotional state. Below, we will create a program for this system and explain its processing in natural language.

[0863] System Configuration

[0864] 1. Server:

[0865] The server receives the skill set and desired job conditions entered by the user and stores them in a database.

[0866] The database stores all user and job information in an organized manner.

[0867] The server analyzes the received information using natural language processing and selects the most suitable job information using a matching algorithm.

[0868] It is equipped with an emotion recognition engine that analyzes the user's emotional state from their facial expressions and behavior.

[0869] Job information selected based on a matching algorithm is customized taking into account the user's emotional state and sent to the terminal.

[0870] 2. Terminal:

[0871] It provides an interface for users to input their skill sets and desired job search conditions.

[0872] Job information sent from the server is displayed, and the user can select from it.

[0873] The job change advice sent from the server is displayed, and appropriate advice is provided to the user.

[0874] Users can access the virtual space through their devices and tour the corporate work environment.

[0875] Main hardware and software used

[0876] Hardware: The server is a computer system with a powerful processor and large storage capacity. The user device is an electronic device such as a smartphone, tablet, or smart glasses.

[0877] Software: Python libraries (e.g., nltk, spaCy) are used for natural language processing. Libraries such as OpenCV and TensorFlow are used for emotion recognition. The virtual space is built using the Unity engine.

[0878] Specific examples

[0879] A user uses a smartphone to enter their skill set (e.g., engineering, project management) and desired job conditions (e.g., work location: Tokyo) into the application. This information is sent to the server and stored in a database. The server analyzes the received information using natural language processing and selects the most suitable job information (e.g., project manager position) from the database. An emotion recognition engine analyzes the user's facial expression data and detects their current emotional state (e.g., high stress).

[0880] For example, if a user is feeling stressed, the server will customize the display to prioritize job listings that encourage relaxation. Additionally, while the user is touring the workplace in the virtual space, the server will change the appropriate explanations and guidance based on the user's emotional state. If the user is interested in a selected job listing, the server will provide customized advice on how to change jobs (e.g., "Take several deep breaths before the interview") based on that information.

[0881] Example prompt sentence:

[0882] Create prompts that help users surface relevant job listings and generate customized career advice based on sentiment data.

[0883] User skills: Engineering, Project Management

[0884] Preferred location: Tokyo

[0885] I am dissatisfied with my current work situation

[0886] This allows users to receive emotional support and proceed with their job search with peace of mind.

[0887] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0888] Step 1:

[0889] The user inputs their skill set and desired job search conditions. Using the interface of a device such as a smartphone or tablet, the user inputs their work history, skill set (e.g., engineering, project management), and desired job search conditions (e.g., work location in Tokyo). The input information is sent from the device to the server.

[0890] Step 2:

[0891] The server receives the information sent by the user and stores it in a database. When the server receives the user's input information, it converts it into a standard format and stores it in a database. This database is used to systematically manage all user information and job information. Pre-processing is performed to format the input data and prepare the storage location.

[0892] Step 3:

[0893] The server analyzes the stored information using natural language processing (NLP). The server uses NLP techniques to analyze the user's work history, skill set, and desired job conditions to extract the user's strengths and characteristics. This analysis uses Python libraries (e.g., nltk, spaCy) to analyze the text of the input data and structure it.

[0894] Step 4:

[0895] The server selects the most suitable job offer based on a matching algorithm. The analyzed user information is compared with the job information in the database, and the matching algorithm (e.g., recommender system) selects the most suitable job offer for the user. The matching algorithm compares the user's requirements with the job offer requirements and lists the most suitable offers.

[0896] Step 5:

[0897] The server customizes the selected job listings using an emotion recognition engine. The server recognizes the user's emotional state in real time and customizes the job listings based on that. Emotion recognition involves capturing facial expression data and analyzing it using an AI model (e.g., an emotion recognition model using TensorFlow). If the user is feeling stressed, job listings that help them relax will be prioritized.

[0898] Step 6:

[0899] The server selects and sends customized job information to the terminal. The customized job information is then sent from the server to the user's terminal. The terminal outputs the received information in a format that is displayed to the user. The user can view the most suitable job information on the terminal screen.

[0900] Step 7:

[0901] The user selects the job information they are interested in from the displayed job information. The user looks at the list of job information displayed on the terminal and selects the information they are interested in. The selected information is then sent back to the server from the terminal.

[0902] Step 8:

[0903] The server generates career change advice based on the selected job information. The server generates career change advice based on the job information selected by the user and the emotion recognition results. This advice is created by an AI model (e.g., using a natural language generation model) and includes specific advice, such as how to calm nerves before an interview.

[0904] Step 9:

[0905] The server sends the generated job change advice to the terminal. The job change advice is sent from the server to the user's terminal, and the terminal displays it. The user can refer to the advice and conduct more effective job change activities.

[0906] Step 10:

[0907] Users can tour a company's work environment in a virtual space. Using their devices, users can access the virtual space and experience a realistic tour of the company's work environment. The virtual space was built using the Unity engine and is designed to allow users to tour interactively. During the tour, an emotion recognition system monitors the user's reactions and changes the route as necessary.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] [Third embodiment]

[0912] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0913] 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.

[0914] 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).

[0915] 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.

[0916] 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.

[0917] 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).

[0918] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0919] 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.

[0920] 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.

[0921] 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.

[0922] 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.

[0923] 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."

[0924] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI to replace the work traditionally performed by job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[0925] Specific system configuration and processing explanation

[0926] User registration and information entry

[0927] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[0928] Information storage and analysis

[0929] The server receives the information entered by the user and stores it in a database. The received information is then analyzed using an analysis engine to analyze the user's skill set, work history, and desired conditions using natural language processing. Based on the analyzed information, a matching algorithm selects the most suitable job opening from the database.

[0930] Generating and displaying matching results

[0931] The server generates a job listing that best suits the user based on a matching algorithm and transmits the listing to the user's terminal, which then displays the listing to the user, allowing the user to view details of the displayed job listings.

[0932] Selection of job information and provision of countermeasures advice

[0933] The user selects the job they are most interested in from the displayed job information. The selected information is sent from the device to the server. The server then generates career change advice for the job based on this selection information. Specifically, the advice is provided tailored to the skill set required by the company, such as how to write a resume and what to emphasize in an interview.

[0934] Viewing and following advice

[0935] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[0936] Specific examples

[0937] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "project manager position at Company A." These job openings are again displayed to the user via their device, and if the user views the details and becomes interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the user via their device. For example, advice such as "Describe specific examples of successful project management" is displayed.

[0938] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, making job hunting more efficient.

[0939] The processing flow will be explained below.

[0940] Step 1:

[0941] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[0942] Step 2:

[0943] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[0944] Step 3:

[0945] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[0946] Step 4:

[0947] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[0948] Step 5:

[0949] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[0950] Step 6:

[0951] The server sends the job listing to the terminal. The information sent is encrypted in response format.

[0952] Step 7:

[0953] The terminal displays the received job list to the user, who then clicks on the details of the job that interests them.

[0954] Step 8:

[0955] When the user selects a job offer that he or she wishes to view, the terminal transmits the selected job offer information to the server.

[0956] Step 9:

[0957] The server receives the selected job information and generates career change advice specific to the job, including tips on how to prepare for an interview and how to write a resume.

[0958] Step 10:

[0959] The server generates and sends the advice to the terminal. The advice information is encrypted.

[0960] Step 11:

[0961] The device displays the received advice to the user, who can then use this advice to prepare for specific job hunting activities.

[0962] Explanation with concrete examples

[0963] Step 1:

[0964] The user accesses the app and enters their name, email address, password, work history (e.g., "Engineer, ABC Company, 3 years"), skill set (e.g., "Java, project management"), and desired job conditions (e.g., "Project manager, Tokyo, annual salary of 6 million yen or more") on the new registration screen.

[0965] Step 2:

[0966] The terminal sends the above input information to the server.

[0967] Step 3:

[0968] The server stores the input information in a database.

[0969] Step 4:

[0970] The server runs the input information through a natural language processing engine to analyze skills and work history.

[0971] Step 5:

[0972] The server lists the most suitable job information based on the analysis results.

[0973] Step 6:

[0974] The server sends the most suitable job listings to the device.

[0975] Step 7:

[0976] The device displays a list of job listings to the user, such as "Project Manager position at Company D" or "Senior Engineer position at Company E."

[0977] Step 8:

[0978] The user selects "Project Manager position at Company D."

[0979] Step 9:

[0980] The server receives the selected job information and generates advice on interview preparation and resume writing specific to Company D.

[0981] Step 10:

[0982] The server generates job change advice and sends it to the terminal.

[0983] Step 11:

[0984] The device will display advice to the user, such as "In your interview with Company D, emphasize specific examples of successful project management" or "It is recommended that you include detailed information about your leadership experience in your resume."

[0985] Example 1

[0986] 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."

[0987] Traditional career change support services are often provided through recruitment agencies, but the quality and response speed of the services provided by these agencies vary. They also lack efficient methods for matching users with the right skills and desired conditions. Furthermore, when it comes to career change strategies, they often provide general advice, without providing specific advice tailored to individual job openings.

[0988] 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.

[0989] In this invention, the server includes a means for a user to input information, a means for receiving the information input by the user and storing it in a data storage, a means for analyzing the stored information in the server and selecting an optimal job based on a matching algorithm, a means for transmitting the selected job information to the user's device, a means for displaying the job information on the device, a means for the user to select the displayed job information, a means for generating career change advice based on the selected job in the server and transmitting it to the device, and a means for displaying the career change advice on the device. This allows users to efficiently find a job that best suits their skill set and desired conditions without relying on traditional career change agents. Furthermore, by providing specific career change advice tailored to individual job openings, the user's success rate in changing jobs can be improved.

[0990] "User" refers to an individual who uses the system to search for a new job.

[0991] "Information" refers to data entered by the user, such as skill set, desired job conditions, and work history.

[0992] "Server" refers to a computer system that receives information sent by a user, stores it in data storage, analyzes it, and provides appropriate services.

[0993] "Data Storage" refers to a data storage device or database for storing information received from a user.

[0994] A "matching algorithm" refers to a calculation method or program for selecting the most suitable job based on user information.

[0995] "Job information" refers to information about jobs stored on the server, including job type, job content, working conditions, etc.

[0996] "Device" refers to hardware such as a computer, tablet, or smartphone that a user uses to access the system.

[0997] "Career change advice" refers to advice and suggestions that are generated by the server and provided to users to help them with their job search.

[0998] "Natural language processing" refers to a computer science technique for analyzing textual information entered by a user and understanding its meaning.

[0999] A "skill set" refers to the qualifications, experience, and abilities that a company is looking for.

[1000] This invention is a job change support system that helps users efficiently find a job that suits them. This system uses advanced analytical means and matching algorithms to provide optimal job information based on the user's skill set and desired job change conditions, and also provides advice on how to change jobs.

[1001] Specifically, the system consists of the following elements:

[1002] 1. User Interface

[1003] Users enter information about themselves through a website or application, including their name, email address, password, work history, skill set, and job preferences. The information is collected using HTML forms and validated using JavaScript.

[1004] 2. Receipt and storage of information

[1005] The terminal sends the information entered by the user to the server, which then stores the received information in data storage (e.g., MySQL or PostgreSQL). This step uses encoding and encryption techniques to ensure that user information is stored safely and efficiently.

[1006] 3. Information analysis

[1007] The server analyzes the stored information using Python, PySpark, etc. Natural language processing (NLP) techniques are used for this analysis. Specifically, libraries such as SpaCy and NLTK are used to analyze the user's skill set, work history, and desired conditions through tokenization, part-of-speech tagging, and named entity recognition.

[1008] 4. Matching Algorithm

[1009] The server then applies a matching algorithm based on the analysis results, using machine learning models (e.g., SVM and decision tree algorithms) using the Scikit-learn library. Suitable job postings are selected from the database and listed.

[1010] 5. Submitting and Displaying Job Postings

[1011] The server sends the generated job listings in JSON format to the device, which receives the information and displays it on the user's screen using a front-end framework such as React or Vue.js.

[1012] 6. Job information selection and job change advice generation

[1013] The user selects the job they are interested in from the displayed job information. This selection information is also sent from the device to the server. Based on the selected job, the server uses an analysis engine written in a Python program or similar to generate career change advice tailored to the job.

[1014] 7. Advice Display

[1015] The job-changing advice sent from the server is displayed on the device, and users can refer to this advice to smoothly proceed with their specific job-changing activities.

[1016] Specific examples

[1017] For example, imagine a user has the skill of "project management" in the field of "engineering" and would like to work in "Tokyo." The user enters this information into the system and sends it to the server via their terminal. The server analyzes this information, compiles a list of suitable job openings from the database, such as "project manager position at company X," and sends it to the terminal. If the user is interested in "project manager position at company X" and selects that information, the server will respond to the selection and generate resume writing advice and interview preparation specific to company X, and send it to the terminal. For example, advice such as "Describe specific examples of successful project management" will be displayed.

[1018] Prompt Sentence Examples

[1019] "If a user has the skill "Project Management" in the field of "Engineering" and desires to work in "Tokyo," please explain in detail the steps required to generate suitable job offers and career advice. Please also mention the specific actions for each step."

[1020] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1021] Step 1:

[1022] Users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job conditions on the registration screen. The entered information is collected on the web page through an HTML form and validated using JavaScript.

[1023] Input: User's personal information, work history, skill set, job search requirements

[1024] Output: Validated user information

[1025] Specific behavior:

[1026] The terminal receives input from the user and uses JavaScript to check whether the form has been filled out correctly.

[1027] If validation is successful, the form data is encoded and sent to the server using an AJAX request.

[1028] Step 2:

[1029] The server stores the received user information in a data storage (such as MySQL or PostgreSQL), during which the data is encoded and encrypted as necessary.

[1030] Input: Validated user information

[1031] Output: User information saved in data storage

[1032] Specific behavior:

[1033] The server decodes the data received from the AJAX request and takes measures against SQL injection.

[1034] Executes an INSERT statement against the database to securely store the user information.

[1035] Step 3:

[1036] The server analyzes the stored user information, using natural language processing (NLP) techniques such as Python and PySpark to analyze the user's skill set, work history, and desired conditions.

[1037] Input: User information stored in data storage

[1038] Output: Parsed user information (e.g., JSON format)

[1039] Specific behavior:

[1040] The server reads user information from a database and uses SpaCy and NLTK for tokenization, part-of-speech tagging, and named entity recognition.

[1041] The parsed results are converted to JSON format and saved for further processing.

[1042] Step 4:

[1043] The server applies a matching algorithm based on the analyzed information to select the most suitable job postings, specifically by running machine learning models (e.g., SVMs and decision trees) using the Scikit-learn library.

[1044] Input: Parsed user information

[1045] Output: List of matching jobs (e.g., in JSON format)

[1046] Specific behavior:

[1047] The server compares the parsed user information with job listings stored in a database and applies a matching algorithm.

[1048] Select the most suitable job information, convert it to JSON format and save it.

[1049] Step 5:

[1050] The server sends a list of matching jobs in JSON format to the device, which then displays the received job information in a user interface using front-end frameworks such as React and Vue.js.

[1051] Input: List of matching jobs (e.g., in JSON format)

[1052] Output: The job displayed in the user interface

[1053] Specific behavior:

[1054] The server encodes the job information in JSON format and sends it to the terminal as an HTTP response.

[1055] The device receives the job information, renders it in HTML using React or Vue.js, and displays it on the user's screen.

[1056] Step 6:

[1057] The user selects from the displayed job information the job they are interested in. This selection information is sent from the terminal to the server.

[1058] Input: Job listing selected by user

[1059] Output: Selections sent to the server

[1060] Specific behavior:

[1061] The terminal records the user's selection and transmits the selected job information in an encoded form to the server.

[1062] The server decodes the received selection information and prepares for the next process.

[1063] Step 7:

[1064] The server generates job-change advice based on the selected job information, using an analysis engine written in Python to provide advice specific to the job.

[1065] Input: Job listing selected by user

[1066] Output: Generated job-changing advice (e.g., JSON format)

[1067] Specific behavior:

[1068] The server parses the selected job postings and generates recommendations in a Python script.

[1069] The generated advice is encoded in JSON format and sent to the device.

[1070] Step 8:

[1071] The terminal displays the job change advice sent from the server to the user.

[1072] Input: Generated job change advice (e.g., JSON format)

[1073] Output: Career change advice displayed in a user interface

[1074] Specific behavior:

[1075] The terminal receives the advisory information and visualizes it to the user using HTML and CSS.

[1076] The user can refer to the displayed advice and use it to help with their job search.

[1077] (Application example 1)

[1078] 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."

[1079] Conventional job-hunting support systems are only available online, making them inadequate for job seekers who prefer to receive in-person support in a brick-and-mortar store. Furthermore, when it comes to providing job information and career advice, the same content is provided to all users, and it is not customized to fit individual skill sets or desired conditions. This often results in inefficient job hunting.

[1080] 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.

[1081] In this invention, the server includes: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information in the server and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for a user to select displayed job offers; means for generating job-changing advice based on the selected job offers and transmitting it to the terminal; means for displaying the job-changing advice on the terminal; means for executing processes from information input to display of job-changing advice via a smartphone app in a physical store; and means for generating job offers and job-changing advice using prompt sentences generated by a generative AI model. This enables direct support in physical stores and makes it possible to provide job offers and job offers and advice customized to individual job seekers.

[1082] A "user" is an individual who uses the system to input their skill set and desired job-changing conditions and receives job information and advice on career changes.

[1083] A "skill set" is a collection of skills and abilities related to a user's job or work.

[1084] "Desired conditions for changing jobs" are conditions such as the place of work, job type, salary, etc. that the user desires when changing jobs.

[1085] The "server" is a central management device that receives and stores information entered by users, analyzes it, selects job information, and generates career change advice.

[1086] "Database" refers to the storage area within the system for storing information entered by users and job information.

[1087] A "matching algorithm" is a calculation method or procedure for selecting the most suitable job offer based on a user's skill set and desired job change conditions.

[1088] A "terminal" is an electronic device that a user uses to display job information and career change advice, and to transmit input information.

[1089] "Job information" refers to information provided by companies, such as job content, required skills, work location, and salary.

[1090] "Career change advice" is advice on how to prepare a resume and interview for a job that the user is looking for.

[1091] A "physical store" is a physical location where job seekers can visit in person and receive job change support services using the system.

[1092] A "smartphone app" is software that runs on a smartphone and allows users to use the system to input their skill set and desired job-changing conditions, and receive job information and advice on how to change jobs.

[1093] A "generative AI model" is an artificial intelligence technology that generates prompts based on user input and customizes job information and career change advice.

[1094] A "prompt" is text generated by a generative AI model, and is an instructional sentence that provides job information and career change advice.

[1095] This invention is a job change support system that uses AI. Users can input their skill set and desired job change conditions via a smartphone app at a physical store, obtain the most suitable job information, and receive effective advice on how to change jobs.

[1096] Overall system configuration

[1097] 1. User registration and information entry

[1098] Users use a smartphone app installed in a physical store to enter information such as their name, email address, password, work history, skill set, and desired job conditions. The information entered is sent to and stored on a cloud server in real time.

[1099] 2. Analysis of Information

[1100] The server stores the received information in a database and uses a natural language processing engine (Google Cloud Natural Language API) to analyze the skillset and desired job conditions. The analyzed information is stored as structured data for use in the next step.

[1101] 3. Matching and job information provision

[1102] The server uses an AI matching algorithm (TensorFlow) to select suitable job offers based on the analyzed user information. The selected job offers are sent to the user's smartphone in real time and displayed to the user.

[1103] 4. Selection of job information and advice on countermeasures

[1104] When a user selects a job posting, the selection is sent to the server. The server generates job-changing advice specific to the company based on the selection. At this time, a generative AI model is used to generate a prompt message, and advice reflecting that message is created.

[1105] The generated advice for career change is sent back to the smartphone and displayed to the user.

[1106] Specific examples

[1107] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in an "urban area." The user enters this information into a smartphone app, which then sends it to the server. The server analyzes this information and lists suitable job postings from its database, such as "project manager position at Company A." The listed job postings are displayed on the smartphone, and if the user is interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the smartphone. For example, advice such as "Describe specific examples of successful project management practices" is displayed.

[1108] Prompt Sentence Examples

[1109] As a concrete example, the following prompt sentence is input to the generative AI model:

[1110] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[1111] Based on this prompt, the AI ​​model generates relevant job information and career change advice.

[1112] With the introduction of this system, job seekers will be able to efficiently conduct their job search even at physical stores, and will be able to receive individually customized job information and career change advice via a smartphone app.

[1113] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1114] Step 1:

[1115] Users use a smartphone app installed in a physical store to input their skill set and desired job conditions. At this time, users enter information such as their name, email address, password, work history, skill set, and desired job conditions into the app. The input information is sent in real time to a server on the cloud. This step also involves verifying the input data and checking for required fields.

[1116] input:

[1117] Name, email address, password, work history, skill set, desired job conditions

[1118] output:

[1119] User information sent to the cloud server

[1120] Step 2:

[1121] The server stores the received user information in a database. At the same time, the stored information is analyzed using a natural language processing engine (Google Cloud Natural Language API). This analysis extracts skill sets and desired job conditions as structured data.

[1122] input:

[1123] User Information

[1124] output:

[1125] Structured data stored in a database

[1126] Step 3:

[1127] The server uses an AI matching algorithm (TensorFlow) to select the most suitable job postings based on the analyzed user structured data. The selection process involves referencing a job posting database to find the job that best suits the user's skill set and desired job change conditions.

[1128] input:

[1129] Structured data, job information database

[1130] output:

[1131] Best job listings

[1132] Step 4:

[1133] The server sends the selected job listings to the user's smartphone, where they are displayed and the user can review them. Here, job seekers can view the details of various job listings and select the one that best suits them.

[1134] input:

[1135] Best job listings

[1136] output:

[1137] Job information displayed on a smartphone

[1138] Step 5:

[1139] Once a user selects the job postings they are interested in, the selection is sent to the server, which then generates job-changing advice specific to the company using a generative AI model to generate prompts and customize the advice accordingly.

[1140] input:

[1141] User-selected job listings

[1142] output:

[1143] Generated career change advice

[1144] Step 6:

[1145] The server then sends the generated job-changing advice back to the smartphone, where the user can check the advice and use it to prepare for their resume or interview.

[1146] input:

[1147] Generated career change advice

[1148] output:

[1149] Job change advice displayed on smartphones

[1150] For example, if the user name is "Yamada Taro" and the desired job is "software developer" and "work in an urban area," the following prompt sentence will be input to the generative AI model:

[1151] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[1152] Based on this prompt, the AI ​​model generates relevant job information and career change advice, which are then provided to the user.

[1153] These specific processing steps enable users to efficiently conduct job hunting activities even at brick-and-mortar stores, and receive individually customized job information and career change advice via a smartphone app.

[1154] 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.

[1155] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[1156] Specific system configuration and processing explanation

[1157] User registration and information entry

[1158] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[1159] Information storage and analysis

[1160] The server receives the information entered by the user and stores it in a database. The received information is converted into a standard format by a pre-processing program, and then the analysis engine analyzes the user's skill set, work history, and desired conditions using natural language processing. Based on this, a matching algorithm selects the most suitable job opening from the database.

[1161] Introducing emotion engine analysis

[1162] The server also incorporates an emotion engine that recognizes emotions from user input and selection history. The emotion engine analyzes the user's input words and behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.).

[1163] Generating and displaying matching results

[1164] The server generates a list of job offers that best suit the user based on a matching algorithm and sends that list to the device. By taking into account the analysis results of the emotion engine, it is possible to customize the display of job information that is more appropriate to the user's current emotional state. For example, if a user is judged to be highly stressed, job offers with work environments that are deemed to be less stressful will be displayed preferentially.

[1165] The terminal displays the sent job listing to the user, and the user can view the details of the displayed job listing.

[1166] Selection of job information and provision of countermeasures advice

[1167] The user selects the job that interests them most from the displayed job information. The selected information is sent from the terminal to the server. Based on this selection, the server generates job change advice for the job. This advice is also customized taking into account the user's emotional state. For example, if the user tends to get nervous, advice on relaxation techniques and the importance of practice runs may be included.

[1168] Viewing and following advice

[1169] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[1170] Specific examples

[1171] For example, suppose a user is in the "Engineering" field, has "Project Management" skills, and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "Project Manager position at Company A." The emotion engine analyzes the user's reactions and language patterns at each step during the registration process, and detects that the user is highly dissatisfied with their current work situation.

[1172] For example, if a user is interested in a project manager position at Company A, they select that information. The server responds to that selection and generates resume-writing advice and interview strategies specific to Company A, reflecting the analysis results of the emotion engine. For example, advice such as "In your interview at Company A, give specific examples of successful project management experiences" or "Take several deep breaths before the interview to ease your nervousness" is displayed.

[1173] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, and also provides emotional support, allowing them to proceed with their job search efficiently and with peace of mind.

[1174] The processing flow will be explained below.

[1175] Step 1:

[1176] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[1177] Step 2:

[1178] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[1179] Step 3:

[1180] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[1181] Step 4:

[1182] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[1183] Step 5:

[1184] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[1185] Step 6:

[1186] Before the server sends the job listings to the user, it analyzes the user's emotional state using an emotion engine.

[1187] Step 7:

[1188] The emotion engine analyzes the user's input and selection history to identify their current emotional state (e.g., excitement, stress, relief, etc.).

[1189] Step 8:

[1190] The server customizes job listings based on the analysis results of the emotion engine. For example, if a user is judged to be highly stressed, job listings with a work environment deemed to be less stressful will be displayed first.

[1191] Step 9:

[1192] The server sends the customized job listings to the device.

[1193] Step 10:

[1194] The terminal displays the received job listings to the user, who can then click on the listings to view the details of the jobs.

[1195] Step 11:

[1196] When the user selects a job offer that interests them, the terminal transmits the selection information to the server.

[1197] Step 12:

[1198] The server receives the selected job information and generates job change advice specific to that job. The emotion engine customizes the advice taking into account the user's emotional state.

[1199] Step 13:

[1200] The server generates job-changing advice and sends it to the device, such as "Take several deep breaths and relax before the interview."

[1201] Step 14:

[1202] The device displays the received job change advice to the user, who can then use the advice to prepare for their job search.

[1203] Example 2

[1204] 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."

[1205] Conventional job-hunting support systems simply analyze and match information entered by users, making it difficult to fully consider the user's emotional state or provide personalized advice for job hunting. This often prevents users from receiving optimal advice tailored to their emotional state, increasing anxiety and stress during job hunting. Furthermore, the advice given is generally generic and unable to provide customized advice tailored to each user's situation.

[1206] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1207] In this invention, the server includes means for a user to input a skill set and desired job-changing conditions, means for receiving the information input by the user and saving it in a database, means for converting the saved information into a standard format, means for analyzing the saved information using a natural language processing engine and selecting optimal job offers based on a matching algorithm, means for using an emotion engine to customize the selected job information based on the user's emotional state, and means for transmitting the customized job information to the user's terminal. This makes it possible to provide optimal job information and job-changing advice based on the user's emotional state and individual skill set.

[1208] "User" refers to an individual who uses the system to input their skill set and desired job search conditions and conducts a job search.

[1209] "Server" refers to a computer system for receiving input information from users and for storing, parsing, matching, and sentiment analysis.

[1210] A "skill set" refers to a specific collection of skills, knowledge, and experience that a user possesses.

[1211] "Desired conditions for changing jobs" refers to the conditions such as job type, work location, salary, etc. that a user desires when changing jobs.

[1212] A "natural language processing engine" refers to software that analyzes text information entered by a user and understands its meaning and intent.

[1213] "Matching algorithm" refers to a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[1214] An "emotion engine" refers to software that analyzes a user's input information and behavioral history and recognizes their emotional state.

[1215] "Database" refers to a data management system for systematically storing and managing user input information and job information.

[1216] "Job information" refers to detailed information about job types provided by companies.

[1217] "Career Advice" refers to information or advice that is useful to a user when applying for a particular job.

[1218] "Terminal" means a device through which a user accesses the system and inputs and receives information from the system.

[1219] The present invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions. A specific embodiment of this system is described below.

[1220] User registration and information entry

[1221] Users access the service's website or application and first enter their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. After entering this information, it is sent to the server via the device.

[1222] Information storage and preprocessing

[1223] The server receives the information entered by the user and stores it in a database. At this stage, the data is converted into a standard format. For example, work history data is formatted in a unified format, and skill set information is standardized. Specific software used here is the Pandas library in Python.

[1224] Information analysis and matching

[1225] The server analyzes the stored user information using a natural language processing engine (e.g., SpaCy or Google Cloud Natural Language API). Based on the analyzed data, it uses a matching algorithm (Collaborative Filtering or Content-Based Filtering) to select the most suitable job information from the database.

[1226] Emotion analysis using an emotion engine

[1227] An emotion engine (e.g., IBM Watson Emotion Analysis) is installed on the server. This engine analyzes the words entered by the user and their behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.). Specifically, it infers emotions from the user's comments and behavioral patterns and generates an optimal response.

[1228] Generating and displaying matching results

[1229] The server combines the analysis results with the emotion engine results to generate a job listing that is optimal for the user. For example, if the user is determined to be under stress, the listing will prioritize job listings with low-stress working environments. The generated listing is sent to the terminal, which displays it to the user. The user can review the displayed job listing and view detailed information.

[1230] Selection of job information and generation of career change advice

[1231] The user selects the job they are most interested in from the displayed job information. This selection is sent to the server via the terminal. The server generates specific job change advice based on the selected job information. This advice includes how to write an appropriate resume for the selected job and how to prepare for an interview. The results of the emotion engine are also reflected, so for example, advice on relaxation methods is included for "users who get nervous easily."

[1232] Viewing and following advice

[1233] The terminal receives the job change advice sent from the server and displays it to the user, allowing the user to prepare for specific job changes, such as creating a resume or rehearsing for an interview.

[1234] Specific examples

[1235] For example, suppose a user has the skills of "project management" in the "engineering" field and would like to work in a "major city." The user enters this information and sends it to the server via their device. The server analyzes this information and lists the most suitable job openings from its database. The emotion engine can detect, for example, that the user is feeling strong stress in their current work environment.

[1236] If a user is interested in "project manager positions at a specific company" and selects that information, the server generates specific advice based on the selection. For example, advice such as "In an interview with a specific company, give specific examples of successful project management" is displayed. Furthermore, if the emotion engine determines that the user tends to get nervous, relaxation techniques such as "take several deep breaths before the interview" are also included.

[1237] Prompt Sentence Examples

[1238] "Based on the user's input skillset and desired location, select the most suitable job offers from a database and prioritize them according to the user's current emotional state.

[1239] Skill Set: Project Management

[1240] Desired work location: Major city

[1241] "For the job posting selected by the user, generate advice on resume writing and interview preparation based on the analysis results of the sentiment engine.

[1242] Selective Job: Project Manager position at a specific company

[1243] Emotional state: Tendency

[1244] In this way, users can obtain job information that best suits their desired conditions, and also receive advice tailored to their own emotional state, allowing them to proceed with their job search efficiently and with peace of mind.

[1245] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1246] Step 1:

[1247] The user enters information. The user accesses the service's website or application and enters their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. The entered information is sent from the device to the server.

[1248] Input: Name, email address, password, work history, skill set, desired job conditions

[1249] Output: User information (sent to server)

[1250] What happens: A user fills in a form and clicks the submit button.

[1251] Step 2:

[1252] The server receives and stores the information. The server receives the information sent by the user and stores it in a database. The stored data converts the employment history data into a unified format and standardizes the skill set information.

[1253] Input: User information

[1254] Output: Standardized user information (stored in a database)

[1255] What happens: A server-side script processes the received information and stores it in a database.

[1256] Step 3:

[1257] The server analyzes the information. The server uses a natural language processing engine (such as SpaCy or Google Cloud Natural Language API) to analyze the user information stored in the database. Based on the analyzed data, a matching algorithm (such as Collaborative Filtering or Content-Based Filtering) is used to select the most suitable job information.

[1258] Input: Standardized user information

[1259] Output: Analysis results (data based on the user's skill set and desired conditions)

[1260] What it does: A natural language processing engine analyzes the user's input data to understand its meaning and intent.

[1261] Step 4:

[1262] The server performs emotion analysis using an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's input information and behavioral history to identify their emotional state (excitement, stress, relief, etc.).

[1263] Input: User comments and behavior history

[1264] Output: Emotion analysis results (identification of emotional state)

[1265] Specific operation: The emotion engine analyzes the user's text and behavioral patterns to calculate their emotional state.

[1266] Step 5:

[1267] The server generates matching results. The server combines the analysis results and the emotion engine results to generate the optimal job listings for the user. For users in a stressed state, job listings with low-stress working environments are prioritized.

[1268] Input: Analysis results, emotion analysis results

[1269] Output: A list of the best jobs

[1270] How it works: A server-side matching algorithm searches the database and aggregates jobs that match your criteria.

[1271] Step 6:

[1272] The server sends the job listing. The server then sends the generated job listing to the terminal, which displays it to the user. The user can then check the displayed job listing and view detailed information.

[1273] Input: Best Job Listings

[1274] Output: Display of job information (displayed on terminal)

[1275] Specific operation: The application on the terminal displays the job list received from the server on the screen.

[1276] Step 7:

[1277] The user selects the job information that interests them most from the displayed job information, and sends the selected information to the server via their terminal.

[1278] Input: User selected job posting

[1279] Output: Selected job information (sent to server)

[1280] Specific operation: The user clicks on the job posting that interests them and presses the select button.

[1281] Step 8:

[1282] The server generates career change advice. The server generates specific career change advice based on the selected job information. The advice includes how to write a resume and how to prepare for an interview, and also reflects the results of the emotion engine.

[1283] Input: Selected job postings, sentiment analysis results

[1284] Output: Job change advice

[1285] Specific operation: The server-side program generates appropriate advice based on job information and the user's emotional state.

[1286] Step 9:

[1287] The terminal displays the advice for job hunting. The terminal receives the advice from the server and displays it to the user. This allows the user to prepare for specific job hunting activities.

[1288] Input: Career change advice

[1289] Output: Display of job change advice (displayed on the terminal)

[1290] Specific operation: The application on the terminal displays the advice received from the server on the screen.

[1291] Through the above processing steps, the user can obtain job information that best suits their desired conditions, receive advice tailored to their own emotional state, and proceed with their job search efficiently and with peace of mind.

[1292] (Application example 2)

[1293] 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."

[1294] While conventional job-change support systems can provide job information based on a user's skill set and desired conditions, it is difficult to provide job information and advice that takes into account the user's emotional state. Furthermore, users have limited means to check the actual work environment in advance, making it difficult to understand the corporate culture and workplace atmosphere of the new employer, which increases the likelihood of mismatches after changing jobs. This creates a challenge for users, as they are unable to feel at ease when searching for a new job.

[1295] 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: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for the user to select the displayed job offers; means for the server to generate job-changing advice based on the selected job offers and send it to the terminal; means for recognizing the user's emotions; means for customizing and providing job offers based on the recognized emotions; means for allowing the user to tour a company's work environment in a virtual space; and means for displaying the job-changing advice on the terminal. This makes it possible to provide job offers and customized job-changing advice that take the user's emotional state into consideration. Furthermore, the virtual space allows the user to tour a company's work environment in advance, preventing mismatches with potential job seekers and allowing the user to proceed with their job-changing search with peace of mind.

[1296] A "skill set" is a collection of specialized abilities and techniques possessed by a user.

[1297] "Desired conditions for changing jobs" refers to the type of job, work location, working conditions, and other requirements that a user desires in a new job.

[1298] "Server" means a computer system that processes information received from users and stores and analyzes data.

[1299] A "database" is a digital storage device that systematically stores user input information and job information.

[1300] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[1301] "Emotion recognition" is a technology that analyzes a user's emotional state from their facial expressions and behavior.

[1302] A "virtual space" is a virtual three-dimensional environment generated by computer simulation.

[1303] "Career change advice" is advice on applying for and preparing for interviews for jobs selected by the user.

[1304] A "terminal" is an electronic device through which a user inputs information and receives output from a system.

[1305] A specific system for implementing this invention provides optimal job information based on the user's skill set and desired job-changing conditions, and also provides job-changing advice that takes into account the user's emotional state. Below, we will create a program for this system and explain its processing in natural language.

[1306] System Configuration

[1307] 1. Server:

[1308] The server receives the skill set and desired job conditions entered by the user and stores them in a database.

[1309] The database stores all user and job information in an organized manner.

[1310] The server analyzes the received information using natural language processing and selects the most suitable job information using a matching algorithm.

[1311] It is equipped with an emotion recognition engine that analyzes the user's emotional state from their facial expressions and behavior.

[1312] Job information selected based on a matching algorithm is customized taking into account the user's emotional state and sent to the terminal.

[1313] 2. Terminal:

[1314] It provides an interface for users to input their skill sets and desired job search conditions.

[1315] Job information sent from the server is displayed, and the user can select from it.

[1316] The job change advice sent from the server is displayed, and appropriate advice is provided to the user.

[1317] Users can access the virtual space through their devices and tour the corporate work environment.

[1318] Main hardware and software used

[1319] Hardware: The server is a computer system with a powerful processor and large storage capacity. The user device is an electronic device such as a smartphone, tablet, or smart glasses.

[1320] Software: Python libraries (e.g., nltk, spaCy) are used for natural language processing. Libraries such as OpenCV and TensorFlow are used for emotion recognition. The virtual space is built using the Unity engine.

[1321] Specific examples

[1322] A user uses a smartphone to enter their skill set (e.g., engineering, project management) and desired job conditions (e.g., work location: Tokyo) into the application. This information is sent to the server and stored in a database. The server analyzes the received information using natural language processing and selects the most suitable job information (e.g., project manager position) from the database. An emotion recognition engine analyzes the user's facial expression data and detects their current emotional state (e.g., high stress).

[1323] For example, if a user is feeling stressed, the server will customize the display to prioritize job listings that encourage relaxation. Additionally, while the user is touring the workplace in the virtual space, the server will change the appropriate explanations and guidance based on the user's emotional state. If the user is interested in a selected job listing, the server will provide customized advice on how to change jobs (e.g., "Take several deep breaths before the interview") based on that information.

[1324] Example prompt sentence:

[1325] Create prompts that help users surface relevant job listings and generate customized career advice based on sentiment data.

[1326] User skills: Engineering, Project Management

[1327] Preferred location: Tokyo

[1328] I am dissatisfied with my current work situation

[1329] This allows users to receive emotional support and proceed with their job search with peace of mind.

[1330] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1331] Step 1:

[1332] The user inputs their skill set and desired job search conditions. Using the interface of a device such as a smartphone or tablet, the user inputs their work history, skill set (e.g., engineering, project management), and desired job search conditions (e.g., work location in Tokyo). The input information is sent from the device to the server.

[1333] Step 2:

[1334] The server receives the information sent by the user and stores it in a database. When the server receives the user's input information, it converts it into a standard format and stores it in a database. This database is used to systematically manage all user information and job information. Pre-processing is performed to format the input data and prepare the storage location.

[1335] Step 3:

[1336] The server analyzes the stored information using natural language processing (NLP). The server uses NLP techniques to analyze the user's work history, skill set, and desired job conditions to extract the user's strengths and characteristics. This analysis uses Python libraries (e.g., nltk, spaCy) to analyze the text of the input data and structure it.

[1337] Step 4:

[1338] The server selects the most suitable job offer based on a matching algorithm. The analyzed user information is compared with the job information in the database, and the matching algorithm (e.g., recommender system) selects the most suitable job offer for the user. The matching algorithm compares the user's requirements with the job offer requirements and lists the most suitable offers.

[1339] Step 5:

[1340] The server customizes the selected job listings using an emotion recognition engine. The server recognizes the user's emotional state in real time and customizes the job listings based on that. Emotion recognition involves capturing facial expression data and analyzing it using an AI model (e.g., an emotion recognition model using TensorFlow). If the user is feeling stressed, job listings that help them relax will be prioritized.

[1341] Step 6:

[1342] The server selects and sends customized job information to the terminal. The customized job information is then sent from the server to the user's terminal. The terminal outputs the received information in a format that is displayed to the user. The user can view the most suitable job information on the terminal screen.

[1343] Step 7:

[1344] The user selects the job information they are interested in from the displayed job information. The user looks at the list of job information displayed on the terminal and selects the information they are interested in. The selected information is then sent back to the server from the terminal.

[1345] Step 8:

[1346] The server generates career change advice based on the selected job information. The server generates career change advice based on the job information selected by the user and the emotion recognition results. This advice is created by an AI model (e.g., using a natural language generation model) and includes specific advice, such as how to calm nerves before an interview.

[1347] Step 9:

[1348] The server sends the generated job change advice to the terminal. The job change advice is sent from the server to the user's terminal, and the terminal displays it. The user can refer to the advice and conduct more effective job change activities.

[1349] Step 10:

[1350] Users can tour a company's work environment in a virtual space. Using their devices, users can access the virtual space and experience a realistic tour of the company's work environment. The virtual space was built using the Unity engine and is designed to allow users to tour interactively. During the tour, an emotion recognition system monitors the user's reactions and changes the route as necessary.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] [Fourth embodiment]

[1355] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1356] 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.

[1357] 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).

[1358] 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.

[1359] 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.

[1360] 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).

[1361] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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."

[1368] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI to replace the work traditionally performed by job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[1369] Specific system configuration and processing explanation

[1370] User registration and information entry

[1371] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[1372] Information storage and analysis

[1373] The server receives the information entered by the user and stores it in a database. The received information is then analyzed using an analysis engine to analyze the user's skill set, work history, and desired conditions using natural language processing. Based on the analyzed information, a matching algorithm selects the most suitable job opening from the database.

[1374] Generating and displaying matching results

[1375] The server generates a job listing that best suits the user based on a matching algorithm and transmits the listing to the user's terminal, which then displays the listing to the user, allowing the user to view details of the displayed job listings.

[1376] Selection of job information and provision of countermeasures advice

[1377] The user selects the job they are most interested in from the displayed job information. The selected information is sent from the device to the server. The server then generates career change advice for the job based on this selection information. Specifically, the advice is provided tailored to the skill set required by the company, such as how to write a resume and what to emphasize in an interview.

[1378] Viewing and following advice

[1379] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[1380] Specific examples

[1381] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "project manager position at Company A." These job openings are again displayed to the user via their device, and if the user views the details and becomes interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the user via their device. For example, advice such as "Describe specific examples of successful project management" is displayed.

[1382] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, making job hunting more efficient.

[1383] The processing flow will be explained below.

[1384] Step 1:

[1385] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[1386] Step 2:

[1387] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[1388] Step 3:

[1389] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[1390] Step 4:

[1391] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[1392] Step 5:

[1393] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[1394] Step 6:

[1395] The server sends the job listing to the terminal. The information sent is encrypted in response format.

[1396] Step 7:

[1397] The terminal displays the received job list to the user, who then clicks on the details of the job that interests them.

[1398] Step 8:

[1399] When the user selects a job offer that he or she wishes to view, the terminal transmits the selected job offer information to the server.

[1400] Step 9:

[1401] The server receives the selected job information and generates career change advice specific to the job, including tips on how to prepare for an interview and how to write a resume.

[1402] Step 10:

[1403] The server generates and sends the advice to the terminal. The advice information is encrypted.

[1404] Step 11:

[1405] The device displays the received advice to the user, who can then use this advice to prepare for specific job hunting activities.

[1406] Explanation with concrete examples

[1407] Step 1:

[1408] The user accesses the app and enters their name, email address, password, work history (e.g., "Engineer, ABC Company, 3 years"), skill set (e.g., "Java, project management"), and desired job conditions (e.g., "Project manager, Tokyo, annual salary of 6 million yen or more") on the new registration screen.

[1409] Step 2:

[1410] The terminal sends the above input information to the server.

[1411] Step 3:

[1412] The server stores the input information in a database.

[1413] Step 4:

[1414] The server runs the input information through a natural language processing engine to analyze skills and work history.

[1415] Step 5:

[1416] The server lists the most suitable job information based on the analysis results.

[1417] Step 6:

[1418] The server sends the most suitable job listings to the device.

[1419] Step 7:

[1420] The device displays a list of job listings to the user, such as "Project Manager position at Company D" or "Senior Engineer position at Company E."

[1421] Step 8:

[1422] The user selects "Project Manager position at Company D."

[1423] Step 9:

[1424] The server receives the selected job information and generates advice on interview preparation and resume writing specific to Company D.

[1425] Step 10:

[1426] The server generates job change advice and sends it to the terminal.

[1427] Step 11:

[1428] The device will display advice to the user, such as "In your interview with Company D, emphasize specific examples of successful project management" or "It is recommended that you include detailed information about your leadership experience in your resume."

[1429] Example 1

[1430] 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."

[1431] Traditional career change support services are often provided through recruitment agencies, but the quality and response speed of the services provided by these agencies vary. They also lack efficient methods for matching users with the right skills and desired conditions. Furthermore, when it comes to career change strategies, they often provide general advice, without providing specific advice tailored to individual job openings.

[1432] 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.

[1433] In this invention, the server includes a means for a user to input information, a means for receiving the information input by the user and storing it in a data storage, a means for analyzing the stored information in the server and selecting an optimal job based on a matching algorithm, a means for transmitting the selected job information to the user's device, a means for displaying the job information on the device, a means for the user to select the displayed job information, a means for generating career change advice based on the selected job in the server and transmitting it to the device, and a means for displaying the career change advice on the device. This allows users to efficiently find a job that best suits their skill set and desired conditions without relying on traditional career change agents. Furthermore, by providing specific career change advice tailored to individual job openings, the user's success rate in changing jobs can be improved.

[1434] "User" refers to an individual who uses the system to search for a new job.

[1435] "Information" refers to data entered by the user, such as skill set, desired job conditions, and work history.

[1436] "Server" refers to a computer system that receives information sent by a user, stores it in data storage, analyzes it, and provides appropriate services.

[1437] "Data Storage" refers to a data storage device or database for storing information received from a user.

[1438] A "matching algorithm" refers to a calculation method or program for selecting the most suitable job based on user information.

[1439] "Job information" refers to information about jobs stored on the server, including job type, job content, working conditions, etc.

[1440] "Device" refers to hardware such as a computer, tablet, or smartphone that a user uses to access the system.

[1441] "Career change advice" refers to advice and suggestions that are generated by the server and provided to users to help them with their job search.

[1442] "Natural language processing" refers to a computer science technique for analyzing textual information entered by a user and understanding its meaning.

[1443] A "skill set" refers to the qualifications, experience, and abilities that a company is looking for.

[1444] This invention is a job change support system that helps users efficiently find a job that suits them. This system uses advanced analytical means and matching algorithms to provide optimal job information based on the user's skill set and desired job change conditions, and also provides advice on how to change jobs.

[1445] Specifically, the system consists of the following elements:

[1446] 1. User Interface

[1447] Users enter information about themselves through a website or application, including their name, email address, password, work history, skill set, and job preferences. The information is collected using HTML forms and validated using JavaScript.

[1448] 2. Receipt and storage of information

[1449] The terminal sends the information entered by the user to the server, which then stores the received information in data storage (e.g., MySQL or PostgreSQL). This step uses encoding and encryption techniques to ensure that user information is stored safely and efficiently.

[1450] 3. Information analysis

[1451] The server analyzes the stored information using Python, PySpark, etc. Natural language processing (NLP) techniques are used for this analysis. Specifically, libraries such as SpaCy and NLTK are used to analyze the user's skill set, work history, and desired conditions through tokenization, part-of-speech tagging, and named entity recognition.

[1452] 4. Matching Algorithm

[1453] The server then applies a matching algorithm based on the analysis results, using machine learning models (e.g., SVM and decision tree algorithms) using the Scikit-learn library. Suitable job postings are selected from the database and listed.

[1454] 5. Submitting and Displaying Job Postings

[1455] The server sends the generated job listings in JSON format to the device, which receives the information and displays it on the user's screen using a front-end framework such as React or Vue.js.

[1456] 6. Job information selection and job change advice generation

[1457] The user selects the job they are interested in from the displayed job information. This selection information is also sent from the device to the server. Based on the selected job, the server uses an analysis engine written in a Python program or similar to generate career change advice tailored to the job.

[1458] 7. Advice Display

[1459] The job-changing advice sent from the server is displayed on the device, and users can refer to this advice to smoothly proceed with their specific job-changing activities.

[1460] Specific examples

[1461] For example, imagine a user has the skill of "project management" in the field of "engineering" and would like to work in "Tokyo." The user enters this information into the system and sends it to the server via their terminal. The server analyzes this information, compiles a list of suitable job openings from the database, such as "project manager position at company X," and sends it to the terminal. If the user is interested in "project manager position at company X" and selects that information, the server will respond to the selection and generate resume writing advice and interview preparation specific to company X, and send it to the terminal. For example, advice such as "Describe specific examples of successful project management" will be displayed.

[1462] Prompt Sentence Examples

[1463] "If a user has the skill "Project Management" in the field of "Engineering" and desires to work in "Tokyo," please explain in detail the steps required to generate suitable job offers and career advice. Please also mention the specific actions for each step."

[1464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1465] Step 1:

[1466] Users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job conditions on the registration screen. The entered information is collected on the web page through an HTML form and validated using JavaScript.

[1467] Input: User's personal information, work history, skill set, job search requirements

[1468] Output: Validated user information

[1469] Specific behavior:

[1470] The terminal receives input from the user and uses JavaScript to check whether the form has been filled out correctly.

[1471] If validation is successful, the form data is encoded and sent to the server using an AJAX request.

[1472] Step 2:

[1473] The server stores the received user information in a data storage (such as MySQL or PostgreSQL), during which the data is encoded and encrypted as necessary.

[1474] Input: Validated user information

[1475] Output: User information saved in data storage

[1476] Specific behavior:

[1477] The server decodes the data received from the AJAX request and takes measures against SQL injection.

[1478] Executes an INSERT statement against the database to securely store the user information.

[1479] Step 3:

[1480] The server analyzes the stored user information, using natural language processing (NLP) techniques such as Python and PySpark to analyze the user's skill set, work history, and desired conditions.

[1481] Input: User information stored in data storage

[1482] Output: Parsed user information (e.g., JSON format)

[1483] Specific behavior:

[1484] The server reads user information from a database and uses SpaCy and NLTK for tokenization, part-of-speech tagging, and named entity recognition.

[1485] The parsed results are converted to JSON format and saved for further processing.

[1486] Step 4:

[1487] The server applies a matching algorithm based on the analyzed information to select the most suitable job postings, specifically by running machine learning models (e.g., SVMs and decision trees) using the Scikit-learn library.

[1488] Input: Parsed user information

[1489] Output: List of matching jobs (e.g., in JSON format)

[1490] Specific behavior:

[1491] The server compares the parsed user information with job listings stored in a database and applies a matching algorithm.

[1492] Select the most suitable job information, convert it to JSON format and save it.

[1493] Step 5:

[1494] The server sends a list of matching jobs in JSON format to the device, which then displays the received job information in a user interface using front-end frameworks such as React and Vue.js.

[1495] Input: List of matching jobs (e.g., in JSON format)

[1496] Output: The job displayed in the user interface

[1497] Specific behavior:

[1498] The server encodes the job information in JSON format and sends it to the terminal as an HTTP response.

[1499] The device receives the job information, renders it in HTML using React or Vue.js, and displays it on the user's screen.

[1500] Step 6:

[1501] The user selects from the displayed job information the job they are interested in. This selection information is sent from the terminal to the server.

[1502] Input: Job listing selected by user

[1503] Output: Selections sent to the server

[1504] Specific behavior:

[1505] The terminal records the user's selection and transmits the selected job information in an encoded form to the server.

[1506] The server decodes the received selection information and prepares for the next process.

[1507] Step 7:

[1508] The server generates job-change advice based on the selected job information, using an analysis engine written in Python to provide advice specific to the job.

[1509] Input: Job listing selected by user

[1510] Output: Generated job-changing advice (e.g., JSON format)

[1511] Specific behavior:

[1512] The server parses the selected job postings and generates recommendations in a Python script.

[1513] The generated advice is encoded in JSON format and sent to the device.

[1514] Step 8:

[1515] The terminal displays the job change advice sent from the server to the user.

[1516] Input: Generated job change advice (e.g., JSON format)

[1517] Output: Career change advice displayed in a user interface

[1518] Specific behavior:

[1519] The terminal receives the advisory information and visualizes it to the user using HTML and CSS.

[1520] The user can refer to the displayed advice and use it to help with their job search.

[1521] (Application example 1)

[1522] 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."

[1523] Conventional job-hunting support systems are only available online, making them inadequate for job seekers who prefer to receive in-person support in a brick-and-mortar store. Furthermore, when it comes to providing job information and career advice, the same content is provided to all users, and it is not customized to fit individual skill sets or desired conditions. This often results in inefficient job hunting.

[1524] 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.

[1525] In this invention, the server includes: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information in the server and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for a user to select displayed job offers; means for generating job-changing advice based on the selected job offers and transmitting it to the terminal; means for displaying the job-changing advice on the terminal; means for executing processes from information input to display of job-changing advice via a smartphone app in a physical store; and means for generating job offers and job-changing advice using prompt sentences generated by a generative AI model. This enables direct support in physical stores and makes it possible to provide job offers and job offers and advice customized to individual job seekers.

[1526] A "user" is an individual who uses the system to input their skill set and desired job-changing conditions and receives job information and advice on career changes.

[1527] A "skill set" is a collection of skills and abilities related to a user's job or work.

[1528] "Desired conditions for changing jobs" are conditions such as the place of work, job type, salary, etc. that the user desires when changing jobs.

[1529] The "server" is a central management device that receives and stores information entered by users, analyzes it, selects job information, and generates career change advice.

[1530] "Database" refers to the storage area within the system for storing information entered by users and job information.

[1531] A "matching algorithm" is a calculation method or procedure for selecting the most suitable job offer based on a user's skill set and desired job change conditions.

[1532] A "terminal" is an electronic device that a user uses to display job information and career change advice, and to transmit input information.

[1533] "Job information" refers to information provided by companies, such as job content, required skills, work location, and salary.

[1534] "Career change advice" is advice on how to prepare a resume and interview for a job that the user is looking for.

[1535] A "physical store" is a physical location where job seekers can visit in person and receive job change support services using the system.

[1536] A "smartphone app" is software that runs on a smartphone and allows users to use the system to input their skill set and desired job-changing conditions, and receive job information and advice on how to change jobs.

[1537] A "generative AI model" is an artificial intelligence technology that generates prompts based on user input and customizes job information and career change advice.

[1538] A "prompt" is text generated by a generative AI model, and is an instructional sentence that provides job information and career change advice.

[1539] This invention is a job change support system that uses AI. Users can input their skill set and desired job change conditions via a smartphone app at a physical store, obtain the most suitable job information, and receive effective advice on how to change jobs.

[1540] Overall system configuration

[1541] 1. User registration and information entry

[1542] Users use a smartphone app installed in a physical store to enter information such as their name, email address, password, work history, skill set, and desired job conditions. The information entered is sent to and stored on a cloud server in real time.

[1543] 2. Analysis of Information

[1544] The server stores the received information in a database and uses a natural language processing engine (Google Cloud Natural Language API) to analyze the skillset and desired job conditions. The analyzed information is stored as structured data for use in the next step.

[1545] 3. Matching and job information provision

[1546] The server uses an AI matching algorithm (TensorFlow) to select suitable job offers based on the analyzed user information. The selected job offers are sent to the user's smartphone in real time and displayed to the user.

[1547] 4. Selection of job information and advice on countermeasures

[1548] When a user selects a job posting, the selection is sent to the server. The server generates job-changing advice specific to the company based on the selection. At this time, a generative AI model is used to generate a prompt message, and advice reflecting that message is created.

[1549] The generated advice for career change is sent back to the smartphone and displayed to the user.

[1550] Specific examples

[1551] For example, suppose a user has "project management" skills in the "engineering" field and would like to work in an "urban area." The user enters this information into a smartphone app, which then sends it to the server. The server analyzes this information and lists suitable job postings from its database, such as "project manager position at Company A." The listed job postings are displayed on the smartphone, and if the user is interested in "project manager position at Company A," they select that information. Based on this selection, the server generates resume writing advice and interview preparation specific to Company A and sends it back to the smartphone. For example, advice such as "Describe specific examples of successful project management practices" is displayed.

[1552] Prompt Sentence Examples

[1553] As a concrete example, the following prompt sentence is input to the generative AI model:

[1554] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[1555] Based on this prompt, the AI ​​model generates relevant job information and career change advice.

[1556] With the introduction of this system, job seekers will be able to efficiently conduct their job search even at physical stores, and will be able to receive individually customized job information and career change advice via a smartphone app.

[1557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1558] Step 1:

[1559] Users use a smartphone app installed in a physical store to input their skill set and desired job conditions. At this time, users enter information such as their name, email address, password, work history, skill set, and desired job conditions into the app. The input information is sent in real time to a server on the cloud. This step also involves verifying the input data and checking for required fields.

[1560] input:

[1561] Name, email address, password, work history, skill set, desired job conditions

[1562] output:

[1563] User information sent to the cloud server

[1564] Step 2:

[1565] The server stores the received user information in a database. At the same time, the stored information is analyzed using a natural language processing engine (Google Cloud Natural Language API). This analysis extracts skill sets and desired job conditions as structured data.

[1566] input:

[1567] User Information

[1568] output:

[1569] Structured data stored in a database

[1570] Step 3:

[1571] The server uses an AI matching algorithm (TensorFlow) to select the most suitable job postings based on the analyzed user structured data. The selection process involves referencing a job posting database to find the job that best suits the user's skill set and desired job change conditions.

[1572] input:

[1573] Structured data, job information database

[1574] output:

[1575] Best job listings

[1576] Step 4:

[1577] The server sends the selected job listings to the user's smartphone, where they are displayed and the user can review them. Here, job seekers can view the details of various job listings and select the one that best suits them.

[1578] input:

[1579] Best job listings

[1580] output:

[1581] Job information displayed on a smartphone

[1582] Step 5:

[1583] Once a user selects the job postings they are interested in, the selection is sent to the server, which then generates job-changing advice specific to the company using a generative AI model to generate prompts and customize the advice accordingly.

[1584] input:

[1585] User-selected job listings

[1586] output:

[1587] Generated career change advice

[1588] Step 6:

[1589] The server then sends the generated job-changing advice back to the smartphone, where the user can check the advice and use it to prepare for their resume or interview.

[1590] input:

[1591] Generated career change advice

[1592] output:

[1593] Job change advice displayed on smartphones

[1594] For example, if the user name is "Yamada Taro" and the desired job is "software developer" and "work in an urban area," the following prompt sentence will be input to the generative AI model:

[1595] "His username is Taro Yamada. He has 5 years of experience as a software developer and excels in Python and JavaScript. He prefers to work in an urban area. Please provide him with the best job opportunities and career advice."

[1596] Based on this prompt, the AI ​​model generates relevant job information and career change advice, which are then provided to the user.

[1597] These specific processing steps enable users to efficiently conduct job hunting activities even at brick-and-mortar stores, and receive individually customized job information and career change advice via a smartphone app.

[1598] 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.

[1599] This invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions.

[1600] Specific system configuration and processing explanation

[1601] User registration and information entry

[1602] First, users access the service's website or application and enter information such as their name, email address, password, work history, skill set, and desired job search conditions on the registration screen. This information is then sent to the server via the device.

[1603] Information storage and analysis

[1604] The server receives the information entered by the user and stores it in a database. The received information is converted into a standard format by a pre-processing program, and then the analysis engine analyzes the user's skill set, work history, and desired conditions using natural language processing. Based on this, a matching algorithm selects the most suitable job opening from the database.

[1605] Introducing emotion engine analysis

[1606] The server also incorporates an emotion engine that recognizes emotions from user input and selection history. The emotion engine analyzes the user's input words and behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.).

[1607] Generating and displaying matching results

[1608] The server generates a list of job offers that best suit the user based on a matching algorithm and sends that list to the device. By taking into account the analysis results of the emotion engine, it is possible to customize the display of job information that is more appropriate to the user's current emotional state. For example, if a user is judged to be highly stressed, job offers with work environments that are deemed to be less stressful will be displayed preferentially.

[1609] The terminal displays the sent job listing to the user, and the user can view the details of the displayed job listing.

[1610] Selection of job information and provision of countermeasures advice

[1611] The user selects the job that interests them most from the displayed job information. The selected information is sent from the terminal to the server. Based on this selection, the server generates job change advice for the job. This advice is also customized taking into account the user's emotional state. For example, if the user tends to get nervous, advice on relaxation techniques and the importance of practice runs may be included.

[1612] Viewing and following advice

[1613] The terminal displays the job change advice sent from the server to the user, allowing the user to make specific preparations for job hunting.

[1614] Specific examples

[1615] For example, suppose a user is in the "Engineering" field, has "Project Management" skills, and would like to work in "Tokyo." The user enters this information and sends it to the server via their device. The server analyzes this information and lists suitable job openings from its database, such as "Project Manager position at Company A." The emotion engine analyzes the user's reactions and language patterns at each step during the registration process, and detects that the user is highly dissatisfied with their current work situation.

[1616] For example, if a user is interested in a project manager position at Company A, they select that information. The server responds to that selection and generates resume-writing advice and interview strategies specific to Company A, reflecting the analysis results of the emotion engine. For example, advice such as "In your interview at Company A, give specific examples of successful project management experiences" or "Take several deep breaths before the interview to ease your nervousness" is displayed.

[1617] This allows users to find the job that best suits them from a wide range of options without relying on traditional job-hunting agents, and also provides emotional support, allowing them to proceed with their job search efficiently and with peace of mind.

[1618] The processing flow will be explained below.

[1619] Step 1:

[1620] A user accesses the service's website or application, opens the new registration screen, and enters information such as their name, email address, password, work history, skill set, and desired job conditions.

[1621] Step 2:

[1622] The terminal sends the information entered by the user to the server, which encrypts the information before transmitting it.

[1623] Step 3:

[1624] The server stores the received information in a database, and once stored, a pre-processing program converts the information into a standard format.

[1625] Step 4:

[1626] The server passes the preprocessed information to an analytics engine to perform natural language processing, such as analyzing work history and skill sets to identify the user's areas of expertise and experience.

[1627] Step 5:

[1628] The server uses a matching algorithm to match the data analyzed with job listings in the database, and lists the most suitable job listings.

[1629] Step 6:

[1630] Before the server sends the job listings to the user, it analyzes the user's emotional state using an emotion engine.

[1631] Step 7:

[1632] The emotion engine analyzes the user's input and selection history to identify their current emotional state (e.g., excitement, stress, relief, etc.).

[1633] Step 8:

[1634] The server customizes job listings based on the analysis results of the emotion engine. For example, if a user is judged to be highly stressed, job listings with a work environment deemed to be less stressful will be displayed first.

[1635] Step 9:

[1636] The server sends the customized job listings to the device.

[1637] Step 10:

[1638] The terminal displays the received job listings to the user, who can then click on the listings to view the details of the jobs.

[1639] Step 11:

[1640] When the user selects a job offer that interests them, the terminal transmits the selection information to the server.

[1641] Step 12:

[1642] The server receives the selected job information and generates job change advice specific to that job. The emotion engine customizes the advice taking into account the user's emotional state.

[1643] Step 13:

[1644] The server generates job-changing advice and sends it to the device, such as "Take several deep breaths and relax before the interview."

[1645] Step 14:

[1646] The device displays the received job change advice to the user, who can then use the advice to prepare for their job search.

[1647] Example 2

[1648] 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."

[1649] Conventional job-hunting support systems simply analyze and match information entered by users, making it difficult to fully consider the user's emotional state or provide personalized advice for job hunting. This often prevents users from receiving optimal advice tailored to their emotional state, increasing anxiety and stress during job hunting. Furthermore, the advice given is generally generic and unable to provide customized advice tailored to each user's situation.

[1650] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1651] In this invention, the server includes means for a user to input a skill set and desired job-changing conditions, means for receiving the information input by the user and saving it in a database, means for converting the saved information into a standard format, means for analyzing the saved information using a natural language processing engine and selecting optimal job offers based on a matching algorithm, means for using an emotion engine to customize the selected job information based on the user's emotional state, and means for transmitting the customized job information to the user's terminal. This makes it possible to provide optimal job information and job-changing advice based on the user's emotional state and individual skill set.

[1652] "User" refers to an individual who uses the system to input their skill set and desired job search conditions and conducts a job search.

[1653] "Server" refers to a computer system for receiving input information from users and for storing, parsing, matching, and sentiment analysis.

[1654] A "skill set" refers to a specific collection of skills, knowledge, and experience that a user possesses.

[1655] "Desired conditions for changing jobs" refers to the conditions such as job type, work location, salary, etc. that a user desires when changing jobs.

[1656] A "natural language processing engine" refers to software that analyzes text information entered by a user and understands its meaning and intent.

[1657] "Matching algorithm" refers to a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[1658] An "emotion engine" refers to software that analyzes a user's input information and behavioral history and recognizes their emotional state.

[1659] "Database" refers to a data management system for systematically storing and managing user input information and job information.

[1660] "Job information" refers to detailed information about job types provided by companies.

[1661] "Career Advice" refers to information or advice that is useful to a user when applying for a particular job.

[1662] "Terminal" means a device through which a user accesses the system and inputs and receives information from the system.

[1663] The present invention is a system that provides job change support services to users who are dissatisfied with their current jobs. This system uses AI and an emotion engine to replace the work performed by traditional job change agents, and provides matching and job change advice that takes into account the user's skills and desired conditions. A specific embodiment of this system is described below.

[1664] User registration and information entry

[1665] Users access the service's website or application and first enter their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. After entering this information, it is sent to the server via the device.

[1666] Information storage and preprocessing

[1667] The server receives the information entered by the user and stores it in a database. At this stage, the data is converted into a standard format. For example, work history data is formatted in a unified format, and skill set information is standardized. Specific software used here is the Pandas library in Python.

[1668] Information analysis and matching

[1669] The server analyzes the stored user information using a natural language processing engine (e.g., SpaCy or Google Cloud Natural Language API). Based on the analyzed data, it uses a matching algorithm (Collaborative Filtering or Content-Based Filtering) to select the most suitable job information from the database.

[1670] Emotion analysis using an emotion engine

[1671] An emotion engine (e.g., IBM Watson Emotion Analysis) is installed on the server. This engine analyzes the words entered by the user and their behavioral history to identify their emotional state (e.g., excitement, stress, relief, etc.). Specifically, it infers emotions from the user's comments and behavioral patterns and generates an optimal response.

[1672] Generating and displaying matching results

[1673] The server combines the analysis results with the emotion engine results to generate a job listing that is optimal for the user. For example, if the user is determined to be under stress, the listing will prioritize job listings with low-stress working environments. The generated listing is sent to the terminal, which displays it to the user. The user can review the displayed job listing and view detailed information.

[1674] Selection of job information and generation of career change advice

[1675] The user selects the job they are most interested in from the displayed job information. This selection is sent to the server via the terminal. The server generates specific job change advice based on the selected job information. This advice includes how to write an appropriate resume for the selected job and how to prepare for an interview. The results of the emotion engine are also reflected, so for example, advice on relaxation methods is included for "users who get nervous easily."

[1676] Viewing and following advice

[1677] The terminal receives the job change advice sent from the server and displays it to the user, allowing the user to prepare for specific job changes, such as creating a resume or rehearsing for an interview.

[1678] Specific examples

[1679] For example, suppose a user has the skills of "project management" in the "engineering" field and would like to work in a "major city." The user enters this information and sends it to the server via their device. The server analyzes this information and lists the most suitable job openings from its database. The emotion engine can detect, for example, that the user is feeling strong stress in their current work environment.

[1680] If a user is interested in "project manager positions at a specific company" and selects that information, the server generates specific advice based on the selection. For example, advice such as "In an interview with a specific company, give specific examples of successful project management" is displayed. Furthermore, if the emotion engine determines that the user tends to get nervous, relaxation techniques such as "take several deep breaths before the interview" are also included.

[1681] Prompt Sentence Examples

[1682] "Based on the user's input skillset and desired location, select the most suitable job offers from a database and prioritize them according to the user's current emotional state.

[1683] Skill Set: Project Management

[1684] Desired work location: Major city

[1685] "For the job posting selected by the user, generate advice on resume writing and interview preparation based on the analysis results of the sentiment engine.

[1686] Selective Job: Project Manager position at a specific company

[1687] Emotional state: Tendency

[1688] In this way, users can obtain job information that best suits their desired conditions, and also receive advice tailored to their own emotional state, allowing them to proceed with their job search efficiently and with peace of mind.

[1689] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1690] Step 1:

[1691] The user enters information. The user accesses the service's website or application and enters their name, email address, password, work history, skill set, desired job search conditions, etc. on the registration screen. The entered information is sent from the device to the server.

[1692] Input: Name, email address, password, work history, skill set, desired job conditions

[1693] Output: User information (sent to server)

[1694] What happens: A user fills in a form and clicks the submit button.

[1695] Step 2:

[1696] The server receives and stores the information. The server receives the information sent by the user and stores it in a database. The stored data converts the employment history data into a unified format and standardizes the skill set information.

[1697] Input: User information

[1698] Output: Standardized user information (stored in a database)

[1699] What happens: A server-side script processes the received information and stores it in a database.

[1700] Step 3:

[1701] The server analyzes the information. The server uses a natural language processing engine (such as SpaCy or Google Cloud Natural Language API) to analyze the user information stored in the database. Based on the analyzed data, a matching algorithm (such as Collaborative Filtering or Content-Based Filtering) is used to select the most suitable job information.

[1702] Input: Standardized user information

[1703] Output: Analysis results (data based on the user's skill set and desired conditions)

[1704] What it does: A natural language processing engine analyzes the user's input data to understand its meaning and intent.

[1705] Step 4:

[1706] The server performs emotion analysis using an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's input information and behavioral history to identify their emotional state (excitement, stress, relief, etc.).

[1707] Input: User comments and behavior history

[1708] Output: Emotion analysis results (identification of emotional state)

[1709] Specific operation: The emotion engine analyzes the user's text and behavioral patterns to calculate their emotional state.

[1710] Step 5:

[1711] The server generates matching results. The server combines the analysis results and the emotion engine results to generate the optimal job listings for the user. For users in a stressed state, job listings with low-stress working environments are prioritized.

[1712] Input: Analysis results, emotion analysis results

[1713] Output: A list of the best jobs

[1714] How it works: A server-side matching algorithm searches the database and aggregates jobs that match your criteria.

[1715] Step 6:

[1716] The server sends the job listing. The server then sends the generated job listing to the terminal, which displays it to the user. The user can then check the displayed job listing and view detailed information.

[1717] Input: Best Job Listings

[1718] Output: Display of job information (displayed on terminal)

[1719] Specific operation: The application on the terminal displays the job list received from the server on the screen.

[1720] Step 7:

[1721] The user selects the job information that interests them most from the displayed job information, and sends the selected information to the server via their terminal.

[1722] Input: User selected job posting

[1723] Output: Selected job information (sent to server)

[1724] Specific operation: The user clicks on the job posting that interests them and presses the select button.

[1725] Step 8:

[1726] The server generates career change advice. The server generates specific career change advice based on the selected job information. The advice includes how to write a resume and how to prepare for an interview, and also reflects the results of the emotion engine.

[1727] Input: Selected job postings, sentiment analysis results

[1728] Output: Job change advice

[1729] Specific operation: The server-side program generates appropriate advice based on job information and the user's emotional state.

[1730] Step 9:

[1731] The terminal displays the advice for job hunting. The terminal receives the advice from the server and displays it to the user. This allows the user to prepare for specific job hunting activities.

[1732] Input: Career change advice

[1733] Output: Display of job change advice (displayed on the terminal)

[1734] Specific operation: The application on the terminal displays the advice received from the server on the screen.

[1735] Through the above processing steps, the user can obtain job information that best suits their desired conditions, receive advice tailored to their own emotional state, and proceed with their job search efficiently and with peace of mind.

[1736] (Application example 2)

[1737] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1738] While conventional job-change support systems can provide job information based on a user's skill set and desired conditions, it is difficult to provide job information and advice that takes into account the user's emotional state. Furthermore, users have limited means to check the actual work environment in advance, making it difficult to understand the corporate culture and workplace atmosphere of the new employer, which increases the likelihood of mismatches after changing jobs. This creates a challenge for users, as they are unable to feel at ease when searching for a new job.

[1739] 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: means for a user to input a skill set and desired job-changing conditions; means for receiving the information input by the user and storing it in a database; means for analyzing the stored information and selecting optimal job offers based on a matching algorithm; means for transmitting the selected job offers to the user's terminal; means for displaying the job offers on the terminal; means for the user to select the displayed job offers; means for the server to generate job-changing advice based on the selected job offers and send it to the terminal; means for recognizing the user's emotions; means for customizing and providing job offers based on the recognized emotions; means for allowing the user to tour a company's work environment in a virtual space; and means for displaying the job-changing advice on the terminal. This makes it possible to provide job offers and customized job-changing advice that take the user's emotional state into consideration. Furthermore, the virtual space allows the user to tour a company's work environment in advance, preventing mismatches with potential job seekers and allowing the user to proceed with their job-changing search with peace of mind.

[1740] A "skill set" is a collection of specialized abilities and techniques possessed by a user.

[1741] "Desired conditions for changing jobs" refers to the type of job, work location, working conditions, and other requirements that a user desires in a new job.

[1742] "Server" means a computer system that processes information received from users and stores and analyzes data.

[1743] A "database" is a digital storage device that systematically stores user input information and job information.

[1744] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's skill set and desired job change conditions.

[1745] "Emotion recognition" is a technology that analyzes a user's emotional state from their facial expressions and behavior.

[1746] A "virtual space" is a virtual three-dimensional environment generated by computer simulation.

[1747] "Career change advice" is advice on applying for and preparing for interviews for jobs selected by the user.

[1748] A "terminal" is an electronic device through which a user inputs information and receives output from a system.

[1749] A specific system for implementing this invention provides optimal job information based on the user's skill set and desired job-changing conditions, and also provides job-changing advice that takes into account the user's emotional state. Below, we will create a program for this system and explain its processing in natural language.

[1750] System Configuration

[1751] 1. Server:

[1752] The server receives the skill set and desired job conditions entered by the user and stores them in a database.

[1753] The database stores all user and job information in an organized manner.

[1754] The server analyzes the received information using natural language processing and selects the most suitable job information using a matching algorithm.

[1755] It is equipped with an emotion recognition engine that analyzes the user's emotional state from their facial expressions and behavior.

[1756] Job information selected based on a matching algorithm is customized taking into account the user's emotional state and sent to the terminal.

[1757] 2. Terminal:

[1758] It provides an interface for users to input their skill sets and desired job search conditions.

[1759] Job information sent from the server is displayed, and the user can select from it.

[1760] The job change advice sent from the server is displayed, and appropriate advice is provided to the user.

[1761] Users can access the virtual space through their devices and tour the corporate work environment.

[1762] Main hardware and software used

[1763] Hardware: The server is a computer system with a powerful processor and large storage capacity. The user device is an electronic device such as a smartphone, tablet, or smart glasses.

[1764] Software: Python libraries (e.g., nltk, spaCy) are used for natural language processing. Libraries such as OpenCV and TensorFlow are used for emotion recognition. The virtual space is built using the Unity engine.

[1765] Specific examples

[1766] A user uses a smartphone to enter their skill set (e.g., engineering, project management) and desired job conditions (e.g., work location: Tokyo) into the application. This information is sent to the server and stored in a database. The server analyzes the received information using natural language processing and selects the most suitable job information (e.g., project manager position) from the database. An emotion recognition engine analyzes the user's facial expression data and detects their current emotional state (e.g., high stress).

[1767] For example, if a user is feeling stressed, the server will customize the display to prioritize job listings that encourage relaxation. Additionally, while the user is touring the workplace in the virtual space, the server will change the appropriate explanations and guidance based on the user's emotional state. If the user is interested in a selected job listing, the server will provide customized advice on how to change jobs (e.g., "Take several deep breaths before the interview") based on that information.

[1768] Example prompt sentence:

[1769] Create prompts that help users surface relevant job listings and generate customized career advice based on sentiment data.

[1770] User skills: Engineering, Project Management

[1771] Preferred location: Tokyo

[1772] I am dissatisfied with my current work situation

[1773] This allows users to receive emotional support and proceed with their job search with peace of mind.

[1774] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1775] Step 1:

[1776] The user inputs their skill set and desired job search conditions. Using the interface of a device such as a smartphone or tablet, the user inputs their work history, skill set (e.g., engineering, project management), and desired job search conditions (e.g., work location in Tokyo). The input information is sent from the device to the server.

[1777] Step 2:

[1778] The server receives the information sent by the user and stores it in a database. When the server receives the user's input information, it converts it into a standard format and stores it in a database. This database is used to systematically manage all user information and job information. Pre-processing is performed to format the input data and prepare the storage location.

[1779] Step 3:

[1780] The server analyzes the stored information using natural language processing (NLP). The server uses NLP techniques to analyze the user's work history, skill set, and desired job conditions to extract the user's strengths and characteristics. This analysis uses Python libraries (e.g., nltk, spaCy) to analyze the text of the input data and structure it.

[1781] Step 4:

[1782] The server selects the most suitable job offer based on a matching algorithm. The analyzed user information is compared with the job information in the database, and the matching algorithm (e.g., recommender system) selects the most suitable job offer for the user. The matching algorithm compares the user's requirements with the job offer requirements and lists the most suitable offers.

[1783] Step 5:

[1784] The server customizes the selected job listings using an emotion recognition engine. The server recognizes the user's emotional state in real time and customizes the job listings based on that. Emotion recognition involves capturing facial expression data and analyzing it using an AI model (e.g., an emotion recognition model using TensorFlow). If the user is feeling stressed, job listings that help them relax will be prioritized.

[1785] Step 6:

[1786] The server selects and sends customized job information to the terminal. The customized job information is then sent from the server to the user's terminal. The terminal outputs the received information in a format that is displayed to the user. The user can view the most suitable job information on the terminal screen.

[1787] Step 7:

[1788] The user selects the job information they are interested in from the displayed job information. The user looks at the list of job information displayed on the terminal and selects the information they are interested in. The selected information is then sent back to the server from the terminal.

[1789] Step 8:

[1790] The server generates career change advice based on the selected job information. The server generates career change advice based on the job information selected by the user and the emotion recognition results. This advice is created by an AI model (e.g., using a natural language generation model) and includes specific advice, such as how to calm nerves before an interview.

[1791] Step 9:

[1792] The server sends the generated job change advice to the terminal. The job change advice is sent from the server to the user's terminal, and the terminal displays it. The user can refer to the advice and conduct more effective job change activities.

[1793] Step 10:

[1794] Users can tour a company's work environment in a virtual space. Using their devices, users can access the virtual space and experience a realistic tour of the company's work environment. The virtual space was built using the Unity engine and is designed to allow users to tour interactively. During the tour, an emotion recognition system monitors the user's reactions and changes the route as necessary.

[1795] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1796] 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.

[1797] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1798] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1799] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1800] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1801] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1802] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1803] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1804] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1805] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1806] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1807] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1808] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1809] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1810] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1811] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1812] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1813] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1814] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1815] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1816] The following is further disclosed regarding the above embodiment.

[1817] (Claim 1)

[1818] A way for users to input their skill sets and desired job search conditions,

[1819] a means for receiving the information input by the user in a server and storing the information in a database;

[1820] A means for analyzing the stored information in the server and selecting the most suitable job offer based on a matching algorithm;

[1821] A means for transmitting the selected job information in the server to a user's terminal;

[1822] means for displaying the job information on a terminal;

[1823] a means for a user to select displayed job listings;

[1824] A means for generating job change advice based on the selected job offer in the server and transmitting the advice to the terminal;

[1825] a means for displaying the job change advice on a terminal;

[1826] A system including:

[1827] (Claim 2)

[1828] Further includes a means for analyzing the user's skill set and desired job conditions through natural language processing;

[1829] 10. The system of claim 1.

[1830] (Claim 3)

[1831] The system further includes a means for customizing advice based on the content of job information and the skill set desired by companies in order to generate career change advice in response to a user's selection.

[1832] 10. The system of claim 1.

[1833] "Example 1"

[1834] (Claim 1)

[1835] a means for a user to input information;

[1836] means for receiving the user-entered information at a server and storing it in a data storage;

[1837] A means for analyzing the stored information in the server and selecting the most suitable job based on a matching algorithm;

[1838] means for transmitting the selected job information to a user's device in the server;

[1839] means for displaying the job information on the device;

[1840] a means for a user to select displayed job information;

[1841] means for generating, in a server, job change advice based on the selected job and transmitting the advice to the device;

[1842] means for displaying the job change advice in the device;

[1843] A system including:

[1844] (Claim 2)

[1845] 10. The system of claim 1, further comprising: means for analyzing the user's information through natural language processing.

[1846] (Claim 3)

[1847] 10. The system of claim 1, further comprising: means for customizing advice based on the content of the job information and the skill set desired by the company, in order to generate career change advice in response to a user selection.

[1848] "Application Example 1"

[1849] (Claim 1)

[1850] A way for users to input their skill sets and desired job search conditions,

[1851] a means for receiving the information input by the user in a server and storing the information in a database;

[1852] A means for analyzing the stored information in the server and selecting the most suitable job offer based on a matching algorithm;

[1853] A means for transmitting the selected job information in the server to a user's terminal;

[1854] means for displaying the job information on a terminal;

[1855] a means for a user to select displayed job listings;

[1856] A means for generating job change advice based on the selected job offer in the server and transmitting the advice to the terminal;

[1857] a means for displaying the job change advice on a terminal;

[1858] A means to input information and display job change advice via a smartphone app at a physical store,

[1859] A system including:

[1860] (Claim 2)

[1861] Further includes a means for analyzing the user's skill set and desired job conditions through natural language processing;

[1862] 10. The system of claim 1.

[1863] (Claim 3)

[1864] The system further includes a means for customizing advice based on the content of job information and the skill set required by companies in order to generate career change advice in response to a user's selection.

[1865] 10. The system of claim 1.

[1866] (Claim 4)

[1867] Further comprising a means for generating job information and career change advice using the generation of prompt sentences by the generative AI model;

[1868] 10. The system of claim 1.

[1869] "Example 2: Combining Emotion Engines"

[1870] (Claim 1)

[1871] A way for users to input their skill sets and desired job search conditions,

[1872] a means for receiving the information input by the user in a server and storing the information in a database;

[1873] means for converting the stored information into a standard format at a server;

[1874] A means for analyzing the stored information in the server using a natural language processing engine and selecting the most suitable job offer based on a matching algorithm;

[1875] a means for using an emotion engine at a server to customize the selected job listings based on the user's emotional state;

[1876] A means for transmitting the customized job information in the server to a user's terminal;

[1877] means for displaying the job information on a terminal;

[1878] a means for a user to select displayed job listings;

[1879] a means for generating job change advice based on the selected job offer in the server and transmitting the advice, which also reflects the user's emotional state, to the terminal;

[1880] a means for displaying the job change advice on a terminal;

[1881] A system including:

[1882] (Claim 2)

[1883] Further includes a means for analyzing the user's skill set and desired job conditions through natural language processing;

[1884] 10. The system of claim 1.

[1885] (Claim 3)

[1886] The system further includes a means for customizing advice based on the content of job information and the skill set desired by companies in order to generate career change advice in response to a user's selection.

[1887] 10. The system of claim 1.

[1888] "Application example 2 when combining emotion engines"

[1889] (Claim 1)

[1890] A way for users to input their skill sets and desired job search conditions,

[1891] a means for receiving the information input by the user in a server and storing the information in a database;

[1892] A means for analyzing the stored information in the server and selecting the most suitable job offer based on a matching algorithm;

[1893] A means for transmitting the selected job information in the server to a user's terminal;

[1894] means for displaying the job information on a terminal;

[1895] a means for a user to select displayed job listings;

[1896] A means for generating job change advice based on the selected job offer in the server and transmitting the advice to the terminal;

[1897] means for recognizing a user's emotion;

[1898] A means to customize and provide job information based on perceived emotions;

[1899] A means to allow users to tour a company's work environment in a virtual space,

[1900] a means for displaying the job change advice on a terminal;

[1901] A system including:

[1902] (Claim 2)

[1903] 10. The system of claim 1, further comprising means for analyzing the user's skill set and desired job conditions by natural language processing.

[1904] (Claim 3)

[1905] 10. The system of claim 1, further comprising: means for customizing the advice based on the content of the job posting and the skill set desired by the company, in response to a user selection, to generate the career change advice. [Explanation of symbols]

[1906] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A way for users to input their skill sets and desired job search conditions, a means for receiving the information input by the user in a server and storing the information in a database; A means for analyzing the stored information in the server and selecting the most suitable job offer based on a matching algorithm; A means for transmitting the selected job information in the server to a user's terminal; means for displaying the job information on a terminal; a means for a user to select displayed job listings; A means for generating job change advice based on the selected job offer in the server and transmitting the advice to the terminal; a means for displaying the job change advice on a terminal; A system including:

2. Further includes a means for analyzing the user's skill set and desired job conditions through natural language processing; The system of claim 1 .

3. The system further includes a means for customizing advice based on the content of job information and the skill set desired by companies in order to generate career change advice in response to a user's selection. The system of claim 1 .

Images