System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting personal information, work experience, skills, and interests from a job change seeker; means for analyzing the inputted information and generating a profile of the job change seeker; means for automatically generating a resume based on the generated profile; means for matching the generated profile with a job opening database and recommending an optimal job type and company; means for analyzing responses to questions and answers and providing feedback for interview practice; and means for obtaining and presenting successful cases to the job change seeker.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] Modern work styles and values ​​regarding career development are rapidly changing, with many people seeking personal growth and fulfillment. Furthermore, economic fluctuations and changes in work styles are driving many people to consider changing jobs. Finding a job that suits them and improving their interview skills are extremely important for job seekers, but there is a lack of comprehensive support for these tasks. Therefore, there is a need for a system that helps job seekers find the best job based on their skills, experience, and interests, and guides them to success. [Means for solving the problem]

[0005] The present invention is a system that includes a means for inputting personal information, work history, skills, and interests from a job seeker, a means for analyzing the input information and generating a profile for the job seeker, a means for automatically generating a resume based on the generated profile, a means for comparing the generated profile with a job database and recommending optimal jobs and companies, a means for analyzing questions and answers and providing feedback for interview practice, and a means for acquiring and presenting success stories to the job seeker. This system enables job seekers to find optimal jobs and companies, effectively prepare for interviews, and learn from success stories, thereby supporting their entire job search.

[0006] A "job seeker" is someone who is looking to move from their current workplace to another in search of a new occupation or position.

[0007] "Personal information" refers to information necessary to identify a specific individual, such as name, age, location, and contact information.

[0008] "Work history" refers to historical information about work, such as the job content, place of employment, and period of employment.

[0009] "Skills" refers to the knowledge, abilities, and techniques required to perform a particular job or task.

[0010] "Interests" refers to the fields or job content that job seekers are particularly interested in.

[0011] "Profile" refers to a comprehensive portrait of a job seeker based on their personal information, work history, skills, and interests.

[0012] A "resume" is a document that summarizes a job seeker's work history and skills when searching for a new job.

[0013] A "job database" refers to a collection of data that compiles job information provided by companies and organizations.

[0014] "Interview practice" refers to an interactive practice session in which job seekers simulate an actual interview.

[0015] "Feedback" refers to a response that points out areas for improvement or good points in response to answers or behavior during interview practice. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information. The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, and interests, providing comprehensive support throughout the entire job search process.

[0038] System configuration

[0039] The system includes the following main elements:

[0040] 1. User terminal: Accepts user input and sends information to the server.

[0041] 2. Server: Analyzes user information, generates profiles, automatically generates resumes, recommends jobs, provides interview practice, and presents success stories.

[0042] 3. Database: Stores job listings, success stories, and profile information.

[0043] Program processing

[0044] Enter and submit user information

[0045] A user inputs their profile information, work history, skills, and interests into a terminal. The terminal formats this input information and sends it to a server. For example, a user inputs their name, age, location, past work history, skills, and current interests.

[0046] Data Analysis and Profiling

[0047] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, if a user has experience as a project manager, their leadership and project management skills will be emphasized.

[0048] Resume auto-generation

[0049] The server then uses the generated profile information to fill in a resume template, for example, converting success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[0050] Recommendations for suitable jobs and companies

[0051] The server compares the profile with a job database and lists the most suitable jobs and companies. For example, if a user has the skillset of a data scientist, it will recommend job openings at AI companies or companies specializing in data analysis.

[0052] Interview preparation support

[0053] The user starts an interview practice session on the device and interacts with a virtual interviewer. The device sends the user's answers to the server in real time. The server analyzes the user's answers and generates the next question and feedback. For example, it provides examples of appropriate answers and suggestions for improvement in response to the question, "What are your strengths?"

[0054] Presentation of success stories

[0055] The server retrieves interviews and stories of successful job-changers from the database and presents them to users. For example, job-changers can read about successful job-change cases in the same industry and use them as reference.

[0056] Through the above process, this system helps job seekers make optimal career choices and lead their job search to success.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[0060] Step 2:

[0061] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[0062] Step 3:

[0063] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[0064] Step 4:

[0065] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[0066] Step 5:

[0067] The server generates a profile based on the analysis results, which includes the user's past successes and key skill sets.

[0068] Step 6:

[0069] Based on the generated profile, the server fills in a resume template with information and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters.

[0070] Step 7:

[0071] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[0072] Step 8:

[0073] The server compares the job market database to find the best jobs and companies for the profile created. This matching process selects the best job opportunities based on skill sets and past work experience.

[0074] Step 9:

[0075] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[0076] Step 10:

[0077] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively with the user.

[0078] Step 11:

[0079] The device receives the user's response and sends it to the server in real time, where the server analyzes the response and generates the next question or feedback.

[0080] Step 12:

[0081] The server generates feedback for the next question and response from the analysis results and sends it to the terminal, where the user receives the feedback and prepares for the next question.

[0082] Step 13:

[0083] The server retrieves interviews and stories of successful job-changers from a database and sends them to the terminal to motivate users. Users can view these success stories and learn from them.

[0084] Through the above processing steps, this system helps job seekers make optimal career choices and guides them to a successful job search.

[0085] Example 1

[0086] 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."

[0087] Conventional career change support systems struggle to automatically generate resumes that fully reflect job seekers' skills and interests, or recommend the most suitable jobs and companies. Furthermore, they lack real-time feedback during interview practice sessions, preventing job seekers from effectively preparing for interviews. Furthermore, there is a lack of a way to provide job seekers with specific advice using success stories. To solve these issues, a detailed profile analysis of job seekers, automatic resume generation using a generative AI model, real-time interview feedback, and the presentation of success stories are required.

[0088] 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.

[0089] In this invention, the server includes: a means for generating a profile for a job seeker; a means for embedding information into a template based on the profile information generated using a generative AI model to automatically generate a resume; a means for recommending optimal jobs and companies; a means for interacting with a virtual interviewer, sending responses to the server in real time, and generating subsequent questions and feedback; and a means for extracting important key points from the user's work history and categorizing skills and interests using natural language processing technology for data analysis and profiling. This not only enables detailed profile analysis of job seekers, but also enables the automatic generation of resumes using the generative AI model and the recommendation of optimal jobs and companies. It also provides real-time feedback during practice interviews and provides specific advice to job seekers using success stories.

[0090] "Career seekers" refer to individuals who wish to change occupations.

[0091] "Personal information" refers to information that can identify a specific individual, such as name, age, or location.

[0092] "Work history" refers to information about past jobs, positions, and job content.

[0093] "Skills" refer to the techniques and abilities possessed in a particular job or field.

[0094] "Interest" refers to an interest in a particular field of work or occupation.

[0095] "Input means" refers to the interface or device through which a user provides information to the system.

[0096] "Means of analysis" refers to the software or algorithms used to process input information and convert it into meaningful data.

[0097] A "profile" refers to data that combines a job seeker's personal information, work history, skills, and interests.

[0098] A "resume" refers to a document that shows the work history and skills of a job seeker.

[0099] "Means of automatic generation" refers to the process by which a system automatically creates documents or information based on input data.

[0100] A "generative AI model" refers to a model that uses artificial intelligence technology to generate text and process information.

[0101] A "template" refers to a pre-prepared document or format into which information can be embedded.

[0102] "Job database" refers to a database system that stores multiple job information.

[0103] "Recommender" refers to algorithms or software that suggest the best options based on input criteria and profiles.

[0104] "Interview practice" refers to providing a virtual interview environment in which users can practice to prepare for an actual interview.

[0105] "Feedback" refers to information that provides users with suggestions for improvement or advice.

[0106] "Success stories" refer to specific examples or stories of other people who have changed jobs successfully.

[0107] "Virtual interviewer" refers to a program provided by the system that asks interview questions and evaluates the user's answers.

[0108] "Data analysis" refers to the process of processing input data using statistical methods and algorithms to extract useful information.

[0109] "Profiling" refers to the process of creating a profile that summarizes the characteristics and tendencies of individual users based on the results of data analysis.

[0110] This invention is a platform that utilizes generative AI to provide customized career advice and job information to job seekers. The system is broadly composed of three main components: a user terminal, a server, and a database.

[0111] The user terminal accepts input from job seekers. When users enter their personal information, work history, skills, and interests into the terminal, the terminal formats this information and sends it to the server. Specific hardware used is a PC or smartphone, and software used is a web browser or dedicated application.

[0112] The server receives the submitted information and processes it for data analysis and profiling. The received information is stored in a database and an analysis module is launched. Analysis is performed using Python natural language processing (NLP) libraries (e.g., NLTK and Spacy) and machine learning frameworks (e.g., scikit-learn and TensorFlow). The analysis module extracts important key points from the user's work history and categorizes their skills and interests.

[0113] For example, a user enters the following information:

[0114] Name: Yamada Taro

[0115] Age: 30

[0116] Location: metropolis

[0117] Work experience: 5 years as a project manager

[0118] Skills: Project management, leadership

[0119] Areas of interest: AI and Data Science

[0120] The server uses this information to extract key points such as:

[0121] Project management experience: 5 years

[0122] Key skills: Leadership, project management

[0123] Areas of interest: AI and Data Science

[0124] Based on the generated profile, the server automatically generates a resume. Using a generative AI model (e.g., GPT-4), the profile information is embedded in a resume template. An example of a prompt for specific sentence generation is shown below:

[0125] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0126] The server also compares the profile information with a job database to recommend suitable jobs and companies. The job database contains multiple job listings, which are matched using SQL queries. The server recommends the following job listings:

[0127] Data Scientist (Work location: large city, Company name: major IT company)

[0128] Project Manager (Location: Large city, Company: Consulting company)

[0129] Additionally, the server provides interview practice sessions to help users prepare for interviews. Users interact with a virtual interviewer on their device and send their answers to the server in real time. The server then analyzes the answers and generates the next questions and feedback. Google Cloud Speech-to-Text API is used for speech recognition, and a generative AI model (e.g., GPT-4) generates the feedback.

[0130] Finally, the server retrieves success stories from the database and presents them to the user. This allows the user to refer to successful cases in similar industries or occupations and develop specific career change strategies. For example, it could present interview articles and stories of successful job-changers in the same occupation.

[0131] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1: Enter and submit user information

[0134] Users input their personal information, work history, skills, and interests into the user terminal. Specific input information includes:

[0135] Name: Yamada Taro

[0136] Age: 30

[0137] Location: metropolis

[0138] Work experience: 5 years as a project manager

[0139] Skills: Project management, leadership

[0140] Areas of interest: AI and Data Science

[0141] The device formats this information (for example, in JSON format) and sends it to the server. As input, there is the data provided by the user, and as output, there is the formatted data sent to the server.

[0142] Step 2: Data analysis and profiling

[0143] The server stores the received user information in a database and launches an analysis module. The input is the transmitted data (user information), and the output is the analysis results. Natural language processing (NLP) techniques are used for the analysis, using Python libraries (NLTK and Spacy) and machine learning frameworks (scikit-learn and TensorFlow). Specifically, the server extracts the following key points from the user's work history:

[0144] Project management experience: 5 years

[0145] Key skills: Leadership, project management

[0146] Areas of interest: AI and Data Science

[0147] Step 3: Auto-generate your resume

[0148] The server automatically generates a resume based on the generated profile information. It uses the profile information as input and generates a resume as output. It uses a generative AI model (e.g., GPT-4) to embed the profile information into a resume template. Specific operations include using prompts such as:

[0149] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0150] This will generate a partial resume:

[0151] My name is Taro Yamada. I have five years of experience as a project manager and have successfully led large-scale projects using PMBOK and agile methods. I am particularly confident in my leadership and project management skills.

[0152] Step 4: Recommend suitable jobs and companies

[0153] The server compares the profile information with the job database and lists the most suitable jobs and companies for the user. The profile information and job database are used as input, and recommendations are generated as output. Specifically, the server uses SQL queries to recommend jobs such as:

[0154] Data Scientist (Work location: large city, Company name: major IT company)

[0155] Project Manager (Location: Large city, Company: Consulting company)

[0156] Step 5: Interview preparation assistance

[0157] The user starts an interview practice session on the user's device and interacts with the virtual interviewer. The user's answers are used as input, and the next question and feedback are generated as output. The device sends the user's answers to the server in real time. Specifically, the virtual interviewer asks questions such as:

[0158] "What are your strengths?"

[0159] If the user answers "Leadership," the server asks for more details:

[0160] "Please tell us a specific story. For example, how you led a team."

[0161] Step 6: Present success stories

[0162] The server retrieves interviews and stories of successful job-changers from a database and presents them to the user. Success story data is used as input, and success story information is displayed to the user as output. Specifically, the server presents the following success stories:

[0163] "A successful project manager: Hanako Yamada has successfully managed projects at a major IT company and is currently working as a data scientist."

[0164] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0165] (Application example 1)

[0166] 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."

[0167] In today's job-hunting environment, job seekers must obtain relevant job information from numerous sources and prepare to highlight their skills and experience. However, gathering information, creating resumes, and preparing for interviews requires a great deal of time and effort, making the job-hunting process difficult. Furthermore, opportunities to receive appropriate career advice are limited, making it difficult for job seekers to maintain their motivation. A particular problem is the lack of information analysis and customized career advice.

[0168] 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.

[0169] In this invention, the server includes means for inputting personal information, work history, skills, and interests from job seekers, means for analyzing the input information and generating a profile of the job seeker, means for automatically generating a resume based on the generated profile, means for comparing the generated profile with a job database and recommending optimal jobs and companies, and means for providing interactive career advice through real-time dialogue with a virtual advisor. This enables job seekers to efficiently and effectively advance their job search through automated data management and analysis and the provision of customized advice.

[0170] "Personal information" refers to information that can be used to identify an individual, such as the job seeker's name, age, address, and contact details.

[0171] "Work history" is information that indicates the job history and experience of a job seeker in the past.

[0172] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by job seekers.

[0173] "Interests" is information that indicates the job type or industry that a job seeker desires, and the field of work in which they are interested.

[0174] A "profile" is a comprehensive portrait of a job seeker that is generated by analyzing their personal information, work history, skills, and interests.

[0175] A resume is a document that a job seeker submits when looking for a new job, listing their work history, skills, educational background, etc.

[0176] A "job database" is a database that collects information about job openings, such as companies and job types.

[0177] The "best fit job type and company" refers to the job content and company that best suits the job seeker, selected based on the job seeker's profile information.

[0178] A "virtual advisor" is an artificial intelligence program designed to provide career advice through real-time dialogue.

[0179] "Interactive career advice" is a service that provides advice and information tailored to individual situations through dialogue with users.

[0180] The present invention is a system for comprehensively providing customized career advice and job information to job seekers. This system is constructed using the following hardware and software.

[0181] Hardware and Software

[0182] Hardware: Smartphone (iOS, Android)

[0183] software:

[0184] Frontend: React Native

[0185] Backend: Node.js, Express.js

[0186] Database: AWS DynamoDB

[0187] Generative AI models: OpenAI GPT-3, BERT

[0188] Implementation details

[0189] 1. Enter and submit user information

[0190] Users use a smartphone application to enter their profile information, work history, skills, and interests, which is then formatted into an appropriate data format, such as JSON, and sent to a back-end server.

[0191] 2. Data storage and analysis

[0192] The server stores the received user information in AWS DynamoDB. The stored data is analyzed by an analysis module running on Node.js and Express.js. The analysis module uses generative AI models (such as OpenAI GPT-3 and BERT) to extract key points from the user's work history and generate a profile.

[0193] 3. Auto-generate resumes

[0194] The server automatically fills in the resume template based on the profile information generated through the analysis, which is then converted into appropriate text based on the user's skills and success stories.

[0195] 4. Recommendations for suitable jobs and companies

[0196] The server compares the generated profile information with a job database and recommends suitable jobs and companies. The recommended job information is sent to the user's smartphone and can be viewed on the application.

[0197] 5. Interactive career advice

[0198] Within the application, users can engage in real-time interactions with a virtual advisor, who uses generative AI models to answer their questions and provide customized career advice.

[0199] 6. Presenting success stories

[0200] The server retrieves successful job-changing cases from the database and presents them to the user. This information serves as inspiration and reference material for the user's job-changing activities.

[0201] Examples and prompts

[0202] As a concrete example, consider a user who has experience as a project manager and is looking for a new career step. The user enters their work history into the application, which automatically generates a resume. The application then recommends suitable job listings and provides specific interview preparation advice from a virtual advisor.

[0203] Examples of prompts include:

[0204] "Auto-generate a resume for a project manager based on the user's work history."

[0205] "Recommend the best job openings for users with the following work experience."

[0206] This will enable job seekers to proceed with their job search efficiently and effectively.

[0207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0208] Step 1:

[0209] A user launches the application on their smartphone and enters their personal information, work history, skills, and interests, which are then formatted into an appropriate data format, such as JSON, and sent to the server.

[0210] Step 2:

[0211] The server stores the received user information in AWS DynamoDB. It checks whether the received data is in the correct format and starts the storage process. If successful, the server generates a status indicating that the data has been saved and sends a trigger to proceed to the next step.

[0212] Step 3:

[0213] The server analyzes the stored data and uses generative AI models (OpenAI GPT-3 and BERT) to extract key points from the user's work history. Specifically, it takes the text data of the work history as input and uses natural language processing technology to extract key skill sets and roles.

[0214] Step 4:

[0215] A resume template is automatically generated based on the profile information generated by the analysis. The server acquires the profile information, embeds the relevant information in a pre-prepared resume template, and automatically generates a resume. The generated resume is displayed to the user as a preview.

[0216] Step 5:

[0217] The server compares the profile information with a job database and recommends the most suitable jobs and companies. The comparison is performed using a matching algorithm to extract the most suitable job listings. The results of the comparison are sent to the user's smartphone and can be viewed on the application.

[0218] Step 6:

[0219] Within the application, users initiate real-time interactions with a virtual advisor, who uses generative AI models to quickly answer their questions and provide customized career advice. The conversation is sent to a server in real time for analysis.

[0220] Step 7:

[0221] The server retrieves successful job-changing cases from the database and presents them to the user. The successful cases are compared with the user's profile information, and the most relevant ones are selected and displayed. This allows the server to provide useful information for the user's job-changing activities.

[0222] 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.

[0223] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[0224] System configuration

[0225] The system includes the following main elements:

[0226] 1. User terminal: Accepts user input and sends information to the server.

[0227] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[0228] 3. Database: Stores job listings, success stories, and profile information.

[0229] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[0230] Program processing

[0231] Enter and submit user information

[0232] A user enters their profile information, work history, skills, and interests into an input form on the device. The device formats this information and sends it to the server. For example, a user enters their name, age, location, past work history, skills, and current areas of interest.

[0233] Data Analysis and Profiling

[0234] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of entry and reflects this in the profile. For example, if the emotion engine detects the user's enthusiasm when entering their work history, that information will also be included in the profile.

[0235] Resume auto-generation

[0236] The server fills in a resume template based on the generated profile information. It uses a sentence generation algorithm to automatically generate compelling resume content. It uses data from the emotion engine to generate content that highlights the user's interests and passions. For example, it converts success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[0237] Recommendations for suitable jobs and companies

[0238] The server compares the profile with a job database and lists the most suitable jobs and companies. It also takes into account data from the emotion engine and prioritizes job recommendations based on the user's particular interest and enthusiasm. For example, a user with a data scientist skill set will be recommended job openings at AI companies or companies specializing in data analysis.

[0239] Interview preparation support

[0240] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions interactively to the user. The device transmits the user's answers to the server in real time. The server analyzes the responses and uses emotional data from the emotion engine to generate the next question and feedback. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[0241] Presentation of success stories

[0242] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users. For example, job-seekers can read about successful job-change cases in the same industry and use them as reference.

[0243] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0244] The processing flow will be explained below.

[0245] Step 1:

[0246] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[0247] Step 2:

[0248] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[0249] Step 3:

[0250] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[0251] Step 4:

[0252] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[0253] Step 5:

[0254] The server uses an emotion engine to analyze the user's emotional state as they type. For example, when a user enters their work history, it can identify emotions such as excitement, interest, or anxiety based on the speed of their keystrokes, the content of their input, their facial expressions, and their tone of voice.

[0255] Step 6:

[0256] The server then generates a profile based on the analysis results and emotional data, which takes into account the user's emotional state as well as their past successes and key skill sets.

[0257] Step 7:

[0258] The server then fills in a resume template based on the generated profile, and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters and incorporating data from the sentiment engine.

[0259] Step 8:

[0260] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[0261] Step 9:

[0262] The server compares the job market database to create a list of jobs and companies that best fit the profile. This matching process selects the most suitable job listings based on the user's skill set and past work experience. It also takes into account emotional data and prioritizes job listings and companies that the user has shown interest in.

[0263] Step 10:

[0264] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[0265] Step 11:

[0266] The user starts an interview practice session from a terminal. The terminal acts as a virtual interviewer and asks questions interactively to the user. The emotion engine analyzes the user's emotions in real time as they answer and sends the results to the server.

[0267] Step 12:

[0268] The server analyzes the user's responses and emotional data to generate the next question or feedback. For example, if it detects that the user is nervous, it will provide advice to ease the tension. If a positive emotion is detected, it will generate a question that will bring out that emotion.

[0269] Step 13:

[0270] The server generates the next question and feedback based on the analysis results and emotion data, and sends them to the device. The user receives the feedback and prepares for the next question.

[0271] Step 14:

[0272] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users.

[0273] Through these processing steps, the system helps job seekers make optimal career choices and guides them to a successful job search. The combination of an emotion engine enables more personalized advice and support that takes into account the user's emotions.

[0274] Example 2

[0275] 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."

[0276] Conventional job change support systems have difficulty in providing adequate personalized advice and support because they are unable to consider the emotions of job seekers. Furthermore, when structuring and analyzing input information and matching resumes with job offers, the systems are unable to reflect the user's enthusiasm and interests, making it difficult to recommend the most suitable jobs and companies.

[0277] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting personal information, work history, skills, and interests from a job seeker; means for structuring the input information and transmitting it to the server; means for analyzing the input information and generating a profile of the job seeker; means for analyzing the job seeker's emotions from the input information using an emotion engine; means for generating a profile using the analysis results and emotion data; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers for interview practice and providing feedback; and means for acquiring and presenting success stories to the job seeker. This enables personalized job change support that takes emotions into consideration and makes it possible to recommend optimal jobs and companies that reflect the user's enthusiasm and interests.

[0278] A "job seeker" refers to an individual who wishes to leave their current workplace and move to a new one.

[0279] "Personal information" refers to information that can identify an individual, such as name, age, or address.

[0280] "Work history" refers to work history information such as past job content, position, and employment period.

[0281] "Skills" refer to the abilities and techniques required for a particular job or occupation.

[0282] "Interest" refers to the degree of concern or involvement in a particular area or field.

[0283] "Terminal" refers to a device or equipment through which a user inputs information.

[0284] "Server" refers to a computer system that receives input data and analyzes and processes it.

[0285] "Structuring" refers to organizing input data into a certain format so that it can be stored in a database.

[0286] "Analysis" refers to the detailed analysis of input data and the extraction of useful information.

[0287] "Profile" refers to a detailed profile of an individual created based on analyzed data and information.

[0288] An "emotion engine" refers to a software module that analyzes and extracts emotional data from user input and behavior.

[0289] "Emotion Data" refers to information about a user's emotional state analyzed by an emotion engine.

[0290] "Automatic resume generation" refers to the process of automatically creating an attractive and relevant resume based on generated profile information.

[0291] "Job Database" refers to a database in which job information is stored.

[0292] "Recommendation" refers to presenting the most suitable job types and companies to the user.

[0293] "Practice interview" refers to the process by which a user prepares by answering questions in a virtual interview environment.

[0294] "Feedback" refers to advice or confirmation provided in response to a user's actions or responses.

[0295] "Success stories" refer to the experiences and interviews of people who have successfully changed jobs in the past.

[0296] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[0297] System configuration

[0298] The system includes the following main elements:

[0299] 1. User terminal: Accepts user input and sends information to the server.

[0300] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[0301] 3. Database: Stores job listings, success stories, and profile information.

[0302] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[0303] Enter and submit user information

[0304] Users enter their profile information, work history, skills, and interests into an input form on their device. Specific input information includes name, age, location, past work history, skills, and current areas of interest. For example, users might enter the following: "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, interested in data science."

[0305] The device formats this input information and sends it to the server using an HTTP request, using a format such as JSON.

[0306] Data Analysis and Profiling

[0307] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, the job title "software engineer" might be tagged with information like "interest in data science."

[0308] Emotion recognition

[0309] The server starts the emotion engine and analyzes the input data received from the user. The input content is used to analyze the user's emotional state, and the results are reflected in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile.

[0310] Generate a profile

[0311] The server uses the analysis results and emotional data to generate a user profile. The profile consists of skill sets, experience, interests, and emotional information. A specific example might be "Taro Yamada, 30 years old, with five years of engineering experience and a strong interest and enthusiasm for data science."

[0312] Auto-generate resumes

[0313] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it generates a sentence such as, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadline."

[0314] Recommendations for suitable jobs and companies

[0315] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[0316] Interview preparation support

[0317] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[0318] Presentation of success stories

[0319] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[0320] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0322] Step 1: Enter your user information

[0323] Users enter their profile information, work history, skills, and interests into an input form on their device. Input information includes name, age, location, past work history, skills, and current areas of interest. For example, they might enter "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, and interested in data science." The input data is then structured and ready for the next step.

[0324] Step 2: Submit user information

[0325] The terminal structures the information entered by the user and sends it to the server using an HTTP request. Specifically, the data to be sent is expressed in JSON format or similar and formatted so that it can be analyzed on the server side. The input data is then sent to the next analysis step.

[0326] Step 3: Analyze user information

[0327] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. For example, it tags the job title "software engineer" with information such as "interest in data science." The analyzed data is then formatted into a user profile.

[0328] Step 4: Recognize emotions

[0329] The server starts the emotion engine and analyzes the input data received from the user. It analyzes the user's emotional state from the input content and reflects the results in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile. The emotional data obtained in this step is used in the next step.

[0330] Step 5: Generate a profile

[0331] The server uses the analysis results and emotion data to generate a user profile. The profile consists of skill sets, experiences, interests, and emotion information. For example, it may contain information such as "Taro Yamada, 30 years old, 5 years of engineering experience, high interest and enthusiasm for data science." The generated profile is used in the next step.

[0332] Step 6: Auto-generate your resume

[0333] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it might generate a sentence like, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadlines." The generated resume is then provided to the user.

[0334] Step 7: Recommend suitable jobs and companies

[0335] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[0336] Step 8: Interview preparation assistance

[0337] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[0338] Step 9: Present success stories

[0339] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[0340] Through these steps, the system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0341] (Application example 2)

[0342] 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."

[0343] Conventional job change support systems provided job information without considering the feelings of job seekers, resulting in a limited user experience and a lack of feedback and advice that reflected individual needs and feelings. They also lacked a mechanism for providing appropriate career advice and job recommendations specifically tailored to factory workers. This made it difficult for workers to effectively utilize their skills and find new career paths.

[0344] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0345] In this invention, the server includes: means for inputting the job seeker's personal information, work history, skills, and interests; means for analyzing the input information and generating a profile; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers and providing feedback for interview practice; means for acquiring success stories and presenting them to the job seeker; means for analyzing emotions and adjusting feedback and recommendations based on the job seeker's emotional state; and means for being installed in a robot and providing career advice to factory workers. This enables job seekers to receive job information and career advice tailored to their emotions and needs, making it possible to provide optimal career support, particularly for factory workers.

[0346] A "job seeker" is an individual who intends to leave their current job and take up a new one.

[0347] "Personal information" refers to information that identifies a specific individual, such as the job seeker's name, age, address, and contact information.

[0348] "Work history" refers to information about the type of work a job seeker has done in the past, the duration of that work, and the nature of the work.

[0349] "Skills" refers to the specialized knowledge, techniques, and abilities that job seekers possess.

[0350] "Interests" refers to information about the fields, industries, and job types that job seekers are interested in.

[0351] "Analysis" refers to the use of computer technology to analyze input information and extract its meaning and patterns.

[0352] A "profile" is a comprehensive data set generated based on a job seeker's personal information, work history, skills, interests, etc.

[0353] A resume is a document that lists the work history, skills, and qualifications of a job seeker.

[0354] A "job database" is a database that stores multiple job listings.

[0355] "Matching" is the process of comparing the generated profile with job information in the job database to find the best match.

[0356] "Recommendation" means suggesting suitable jobs and companies to job seekers based on the results of the comparison.

[0357] "Practice interviews" are mock question and answer sessions in preparation for the actual interview.

[0358] "Feedback" refers to evaluations and advice provided to job seekers during practice interviews, etc.

[0359] "Success stories" are the experiences and stories of other job seekers who have been successful in their job search, and are provided as reference information.

[0360] "Analyzing emotions" means measuring the emotional state of job seekers and analyzing the data based on that state.

[0361] A "robot" is a mechanical device that operates automatically and has the function of performing specific tasks at a factory or other work site.

[0362] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information, and is a system that combines an emotion engine. The system inputs the job seeker's personal information, work history, skills, and interests, analyzes this information, and generates a profile. It then automatically generates a resume based on the profile and compares it with a job database to recommend the most suitable jobs and companies. It also analyzes questions and answers for interview practice, providing real-time feedback, and presents success stories.

[0363] The system includes the following main elements:

[0364] 1. User Device:

[0365] It is a means for users to enter personal information, work experience, skills, and interests, which is then formatted and sent to a server. Examples include devices such as smartphones, PCs, and tablets.

[0366] 2. Server:

[0367] The server is responsible for centralizing and analyzing data. It analyzes the data received from users and generates a profile. Emotional data analyzed by the emotion engine is also reflected in the profile. Based on the generated profile, a resume is automatically generated and compared with a job database to recommend the most suitable job type and company. It also provides real-time feedback during interview practice and presents success stories.

[0368] 3. Database:

[0369] It includes a database for storing history information, job listings, and success stories. The server communicates with the database to retrieve and store the required information.

[0370] 4. Emotion Engine:

[0371] Analyzes the emotions of users when they input or respond. For example, analyzes the user's emotional state when they input and reflects the results in their profile. The emotion engine adjusts advice and feedback based on the user's emotions.

[0372] 5. Applications installed on the robot:

[0373] The application is installed on a robot to provide career advice to factory workers. It recommends suitable jobs and positions based on the worker's skills and experience. It also uses an emotion engine to recognize the worker's emotional state and provide appropriate feedback and advice in real time.

[0374] As a concrete example, consider the following prompt text entered by a user on a smartphone or tablet:

[0375] Example prompt sentence:

[0376] "I have been working on an automobile production line for five years. I am particularly good at operating and maintaining robots. I am interested in learning new skills and am also studying automation using AI. Please let me know if there are any job openings."

[0377] The system analyzes this input information, generates a profile, and automatically generates a resume. It also compares it with a job database to recommend the most suitable jobs and companies, and conducts interview practice sessions. It also presents success stories to motivate users. The emotion engine detects the user's emotions when they enter information and adjusts the feedback and advice provided based on that information.

[0378] By linking with the emotion engine and database, the server can provide more personalized career advice, allowing job seekers to receive the most appropriate job information and career support tailored to their needs and emotions. Similar support can also be provided to factory workers.

[0379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0380] Step 1:

[0381] The user enters the job seeker's personal information, work experience, skills, and interests. For example, the user enters information using prompts on a smartphone or tablet. The entered information is formatted by the device and sent to the server. The entered data may include, for example, name, age, address, past work experience, skills, and areas of interest.

[0382] input:

[0383] Personal information (name, age, address)

[0384] Work history (past job content, period)

[0385] Skills (specialized knowledge, techniques)

[0386] Areas of Interest

[0387] output:

[0388] Formatted data sent to the server

[0389] Step 2:

[0390] The server analyzes the received user information and generates a profile. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of input and reflects that data in the profile.

[0391] input:

[0392] User information (personal information, work history, skills, areas of interest)

[0393] Emotional data (emotional state at the time of input)

[0394] output:

[0395] Generated User Profile

[0396] Step 3:

[0397] The server automatically generates a resume based on the generated profile. It embeds the profile data into a resume template and uses a text generation algorithm to create an appealing resume. It also uses emotional data to generate content that emphasizes the user's interests and passions.

[0398] input:

[0399] Generated User Profile

[0400] Emotional Data

[0401] output:

[0402] Auto-generated resume

[0403] Step 4:

[0404] The server compares the created profile with a job database and recommends the most suitable jobs and companies. It also takes into account emotional data and prioritizes jobs that the user has shown particular interest or enthusiasm for.

[0405] input:

[0406] Generated User Profile

[0407] Job Database

[0408] output:

[0409] List of recommended jobs and companies

[0410] Step 5:

[0411] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively to the user, whose answers are sent to the server in real time.

[0412] input:

[0413] User interview answers

[0414] output:

[0415] Submitted response data

[0416] Step 6:

[0417] The server analyzes the user's interview responses and generates the next question and feedback using the emotion data from the emotion engine. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[0418] input:

[0419] Interview response data

[0420] Emotional Data

[0421] output:

[0422] Next Questions and Feedback

[0423] Step 7:

[0424] The server retrieves success stories from the database and presents them to the user. Based on the data from the emotion engine, it selects success stories that are likely to interest the user.

[0425] input:

[0426] Emotional Data

[0427] Success story database

[0428] output:

[0429] Success stories presented

[0430] Step 8:

[0431] The application installed on the robot provides career advice to workers, recommending suitable tasks and jobs based on their skills and experience, and using an emotion engine to recognize the worker's emotional state and provide feedback and advice in real time.

[0432] input:

[0433] Worker skills, experience, and emotional data

[0434] output:

[0435] Career advice and feedback

[0436] 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.

[0437] 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.

[0438] 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.

[0439] [Second embodiment]

[0440] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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).

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] In the smart glasses 214, 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.

[0451] 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."

[0452] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information. The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, and interests, providing comprehensive support throughout the entire job search process.

[0453] System configuration

[0454] The system includes the following main elements:

[0455] 1. User terminal: Accepts user input and sends information to the server.

[0456] 2. Server: Analyzes user information, generates profiles, automatically generates resumes, recommends jobs, provides interview practice, and presents success stories.

[0457] 3. Database: Stores job listings, success stories, and profile information.

[0458] Program processing

[0459] Enter and submit user information

[0460] A user inputs their profile information, work history, skills, and interests into a terminal. The terminal formats this input information and sends it to a server. For example, a user inputs their name, age, location, past work history, skills, and current interests.

[0461] Data Analysis and Profiling

[0462] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, if a user has experience as a project manager, their leadership and project management skills will be emphasized.

[0463] Resume auto-generation

[0464] The server then uses the generated profile information to fill in a resume template, for example, converting success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[0465] Recommendations for suitable jobs and companies

[0466] The server compares the profile with a job database and lists the most suitable jobs and companies. For example, if a user has the skillset of a data scientist, it will recommend job openings at AI companies or companies specializing in data analysis.

[0467] Interview preparation support

[0468] The user starts an interview practice session on the device and interacts with a virtual interviewer. The device sends the user's answers to the server in real time. The server analyzes the user's answers and generates the next question and feedback. For example, it provides examples of appropriate answers and suggestions for improvement in response to the question, "What are your strengths?"

[0469] Presentation of success stories

[0470] The server retrieves interviews and stories of successful job-changers from the database and presents them to users. For example, job-changers can read about successful job-change cases in the same industry and use them as reference.

[0471] Through the above process, this system helps job seekers make optimal career choices and lead their job search to success.

[0472] The processing flow will be explained below.

[0473] Step 1:

[0474] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[0475] Step 2:

[0476] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[0477] Step 3:

[0478] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[0479] Step 4:

[0480] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[0481] Step 5:

[0482] The server generates a profile based on the analysis results, which includes the user's past successes and key skill sets.

[0483] Step 6:

[0484] Based on the generated profile, the server fills in a resume template with information and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters.

[0485] Step 7:

[0486] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[0487] Step 8:

[0488] The server compares the job market database to find the best jobs and companies for the profile created. This matching process selects the best job opportunities based on skill sets and past work experience.

[0489] Step 9:

[0490] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[0491] Step 10:

[0492] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively with the user.

[0493] Step 11:

[0494] The device receives the user's response and sends it to the server in real time, where the server analyzes the response and generates the next question or feedback.

[0495] Step 12:

[0496] The server generates feedback for the next question and response from the analysis results and sends it to the terminal, where the user receives the feedback and prepares for the next question.

[0497] Step 13:

[0498] The server retrieves interviews and stories of successful job-changers from a database and sends them to the terminal to motivate users. Users can view these success stories and learn from them.

[0499] Through the above processing steps, this system helps job seekers make optimal career choices and guides them to a successful job search.

[0500] Example 1

[0501] 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."

[0502] Conventional career change support systems struggle to automatically generate resumes that fully reflect job seekers' skills and interests, or recommend the most suitable jobs and companies. Furthermore, they lack real-time feedback during interview practice sessions, preventing job seekers from effectively preparing for interviews. Furthermore, there is a lack of a way to provide job seekers with specific advice using success stories. To solve these issues, a detailed profile analysis of job seekers, automatic resume generation using a generative AI model, real-time interview feedback, and the presentation of success stories are required.

[0503] 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.

[0504] In this invention, the server includes: a means for generating a profile for a job seeker; a means for embedding information into a template based on the profile information generated using a generative AI model to automatically generate a resume; a means for recommending optimal jobs and companies; a means for interacting with a virtual interviewer, sending responses to the server in real time, and generating subsequent questions and feedback; and a means for extracting important key points from the user's work history and categorizing skills and interests using natural language processing technology for data analysis and profiling. This not only enables detailed profile analysis of job seekers, but also enables the automatic generation of resumes using the generative AI model and the recommendation of optimal jobs and companies. It also provides real-time feedback during practice interviews and provides specific advice to job seekers using success stories.

[0505] "Career seekers" refer to individuals who wish to change occupations.

[0506] "Personal information" refers to information that can identify a specific individual, such as name, age, or location.

[0507] "Work history" refers to information about past jobs, positions, and job content.

[0508] "Skills" refer to the techniques and abilities possessed in a particular job or field.

[0509] "Interest" refers to an interest in a particular field of work or occupation.

[0510] "Input means" refers to the interface or device through which a user provides information to the system.

[0511] "Means of analysis" refers to the software or algorithms used to process input information and convert it into meaningful data.

[0512] A "profile" refers to data that combines a job seeker's personal information, work history, skills, and interests.

[0513] A "resume" refers to a document that shows the work history and skills of a job seeker.

[0514] "Means of automatic generation" refers to the process by which a system automatically creates documents or information based on input data.

[0515] A "generative AI model" refers to a model that uses artificial intelligence technology to generate text and process information.

[0516] A "template" refers to a pre-prepared document or format into which information can be embedded.

[0517] "Job database" refers to a database system that stores multiple job information.

[0518] "Recommender" refers to algorithms or software that suggest the best options based on input criteria and profiles.

[0519] "Interview practice" refers to providing a virtual interview environment in which users can practice to prepare for an actual interview.

[0520] "Feedback" refers to information that provides users with suggestions for improvement or advice.

[0521] "Success stories" refer to specific examples or stories of other people who have changed jobs successfully.

[0522] "Virtual interviewer" refers to a program provided by the system that asks interview questions and evaluates the user's answers.

[0523] "Data analysis" refers to the process of processing input data using statistical methods and algorithms to extract useful information.

[0524] "Profiling" refers to the process of creating a profile that summarizes the characteristics and tendencies of individual users based on the results of data analysis.

[0525] This invention is a platform that utilizes generative AI to provide customized career advice and job information to job seekers. The system is broadly composed of three main components: a user terminal, a server, and a database.

[0526] The user terminal accepts input from job seekers. When users enter their personal information, work history, skills, and interests into the terminal, the terminal formats this information and sends it to the server. Specific hardware used is a PC or smartphone, and software used is a web browser or dedicated application.

[0527] The server receives the submitted information and processes it for data analysis and profiling. The received information is stored in a database and an analysis module is launched. Analysis is performed using Python natural language processing (NLP) libraries (e.g., NLTK and Spacy) and machine learning frameworks (e.g., scikit-learn and TensorFlow). The analysis module extracts important key points from the user's work history and categorizes their skills and interests.

[0528] For example, a user enters the following information:

[0529] Name: Yamada Taro

[0530] Age: 30

[0531] Location: metropolis

[0532] Work experience: 5 years as a project manager

[0533] Skills: Project management, leadership

[0534] Areas of interest: AI and Data Science

[0535] The server uses this information to extract key points such as:

[0536] Project management experience: 5 years

[0537] Key skills: Leadership, project management

[0538] Areas of interest: AI and Data Science

[0539] Based on the generated profile, the server automatically generates a resume. Using a generative AI model (e.g., GPT-4), the profile information is embedded in a resume template. An example of a prompt for specific sentence generation is shown below:

[0540] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0541] The server also compares the profile information with a job database to recommend suitable jobs and companies. The job database contains multiple job listings, which are matched using SQL queries. The server recommends the following job listings:

[0542] Data Scientist (Work location: large city, Company name: major IT company)

[0543] Project Manager (Location: Large city, Company: Consulting company)

[0544] Additionally, the server provides interview practice sessions to help users prepare for interviews. Users interact with a virtual interviewer on their device and send their answers to the server in real time. The server then analyzes the answers and generates the next questions and feedback. Google Cloud Speech-to-Text API is used for speech recognition, and a generative AI model (e.g., GPT-4) generates the feedback.

[0545] Finally, the server retrieves success stories from the database and presents them to the user. This allows the user to refer to successful cases in similar industries or occupations and develop specific career change strategies. For example, it could present interview articles and stories of successful job-changers in the same occupation.

[0546] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0548] Step 1: Enter and submit user information

[0549] Users input their personal information, work history, skills, and interests into the user terminal. Specific input information includes:

[0550] Name: Yamada Taro

[0551] Age: 30

[0552] Location: metropolis

[0553] Work experience: 5 years as a project manager

[0554] Skills: Project management, leadership

[0555] Areas of interest: AI and Data Science

[0556] The device formats this information (for example, in JSON format) and sends it to the server. As input, there is the data provided by the user, and as output, there is the formatted data sent to the server.

[0557] Step 2: Data analysis and profiling

[0558] The server stores the received user information in a database and launches an analysis module. The input is the transmitted data (user information), and the output is the analysis results. Natural language processing (NLP) techniques are used for the analysis, using Python libraries (NLTK and Spacy) and machine learning frameworks (scikit-learn and TensorFlow). Specifically, the server extracts the following key points from the user's work history:

[0559] Project management experience: 5 years

[0560] Key skills: Leadership, project management

[0561] Areas of interest: AI and Data Science

[0562] Step 3: Auto-generate your resume

[0563] The server automatically generates a resume based on the generated profile information. It uses the profile information as input and generates a resume as output. It uses a generative AI model (e.g., GPT-4) to embed the profile information into a resume template. Specific operations include using prompts such as:

[0564] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0565] This will generate a partial resume:

[0566] My name is Taro Yamada. I have five years of experience as a project manager and have successfully led large-scale projects using PMBOK and agile methods. I am particularly confident in my leadership and project management skills.

[0567] Step 4: Recommend suitable jobs and companies

[0568] The server compares the profile information with the job database and lists the most suitable jobs and companies for the user. The profile information and job database are used as input, and recommendations are generated as output. Specifically, the server uses SQL queries to recommend jobs such as:

[0569] Data Scientist (Work location: large city, Company name: major IT company)

[0570] Project Manager (Location: Large city, Company: Consulting company)

[0571] Step 5: Interview preparation assistance

[0572] The user starts an interview practice session on the user's device and interacts with the virtual interviewer. The user's answers are used as input, and the next question and feedback are generated as output. The device sends the user's answers to the server in real time. Specifically, the virtual interviewer asks questions such as:

[0573] "What are your strengths?"

[0574] If the user answers "Leadership," the server asks for more details:

[0575] "Please tell us a specific story. For example, how you led a team."

[0576] Step 6: Present success stories

[0577] The server retrieves interviews and stories of successful job-changers from a database and presents them to the user. Success story data is used as input, and success story information is displayed to the user as output. Specifically, the server presents the following success stories:

[0578] "A successful project manager: Hanako Yamada has successfully managed projects at a major IT company and is currently working as a data scientist."

[0579] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0580] (Application example 1)

[0581] 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."

[0582] In today's job-hunting environment, job seekers must obtain relevant job information from numerous sources and prepare to highlight their skills and experience. However, gathering information, creating resumes, and preparing for interviews requires a great deal of time and effort, making the job-hunting process difficult. Furthermore, opportunities to receive appropriate career advice are limited, making it difficult for job seekers to maintain their motivation. A particular problem is the lack of information analysis and customized career advice.

[0583] 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.

[0584] In this invention, the server includes means for inputting personal information, work history, skills, and interests from job seekers, means for analyzing the input information and generating a profile of the job seeker, means for automatically generating a resume based on the generated profile, means for comparing the generated profile with a job database and recommending optimal jobs and companies, and means for providing interactive career advice through real-time dialogue with a virtual advisor. This enables job seekers to efficiently and effectively advance their job search through automated data management and analysis and the provision of customized advice.

[0585] "Personal information" refers to information that can be used to identify an individual, such as the job seeker's name, age, address, and contact details.

[0586] "Work history" is information that indicates the job history and experience of a job seeker in the past.

[0587] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by job seekers.

[0588] "Interests" is information that indicates the job type or industry that a job seeker desires, and the field of work in which they are interested.

[0589] A "profile" is a comprehensive portrait of a job seeker that is generated by analyzing their personal information, work history, skills, and interests.

[0590] A resume is a document that a job seeker submits when looking for a new job, listing their work history, skills, educational background, etc.

[0591] A "job database" is a database that collects information about job openings, such as companies and job types.

[0592] The "best fit job type and company" refers to the job content and company that best suits the job seeker, selected based on the job seeker's profile information.

[0593] A "virtual advisor" is an artificial intelligence program designed to provide career advice through real-time dialogue.

[0594] "Interactive career advice" is a service that provides advice and information tailored to individual situations through dialogue with users.

[0595] The present invention is a system for comprehensively providing customized career advice and job information to job seekers. This system is constructed using the following hardware and software.

[0596] Hardware and Software

[0597] Hardware: Smartphone (iOS, Android)

[0598] software:

[0599] Frontend: React Native

[0600] Backend: Node.js, Express.js

[0601] Database: AWS DynamoDB

[0602] Generative AI models: OpenAI GPT-3, BERT

[0603] Implementation details

[0604] 1. Enter and submit user information

[0605] Users use a smartphone application to enter their profile information, work history, skills, and interests, which is then formatted into an appropriate data format, such as JSON, and sent to a back-end server.

[0606] 2. Data storage and analysis

[0607] The server stores the received user information in AWS DynamoDB. The stored data is analyzed by an analysis module running on Node.js and Express.js. The analysis module uses generative AI models (such as OpenAI GPT-3 and BERT) to extract key points from the user's work history and generate a profile.

[0608] 3. Auto-generate resumes

[0609] The server automatically fills in the resume template based on the profile information generated through the analysis, which is then converted into appropriate text based on the user's skills and success stories.

[0610] 4. Recommendations for suitable jobs and companies

[0611] The server compares the generated profile information with a job database and recommends suitable jobs and companies. The recommended job information is sent to the user's smartphone and can be viewed on the application.

[0612] 5. Interactive career advice

[0613] Within the application, users can engage in real-time interactions with a virtual advisor, who uses generative AI models to answer their questions and provide customized career advice.

[0614] 6. Presenting success stories

[0615] The server retrieves successful job-changing cases from the database and presents them to the user. This information serves as inspiration and reference material for the user's job-changing activities.

[0616] Examples and prompts

[0617] As a concrete example, consider a user who has experience as a project manager and is looking for a new career step. The user enters their work history into the application, which automatically generates a resume. The application then recommends suitable job listings and provides specific interview preparation advice from a virtual advisor.

[0618] Examples of prompts include:

[0619] "Auto-generate a resume for a project manager based on the user's work history."

[0620] "Recommend the best job openings for users with the following work experience."

[0621] This will enable job seekers to proceed with their job search efficiently and effectively.

[0622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0623] Step 1:

[0624] A user launches the application on their smartphone and enters their personal information, work history, skills, and interests, which are then formatted into an appropriate data format, such as JSON, and sent to the server.

[0625] Step 2:

[0626] The server stores the received user information in AWS DynamoDB. It checks whether the received data is in the correct format and starts the storage process. If successful, the server generates a status indicating that the data has been saved and sends a trigger to proceed to the next step.

[0627] Step 3:

[0628] The server analyzes the stored data and uses generative AI models (OpenAI GPT-3 and BERT) to extract key points from the user's work history. Specifically, it takes the text data of the work history as input and uses natural language processing technology to extract key skill sets and roles.

[0629] Step 4:

[0630] A resume template is automatically generated based on the profile information generated by the analysis. The server acquires the profile information, embeds the relevant information in a pre-prepared resume template, and automatically generates a resume. The generated resume is displayed to the user as a preview.

[0631] Step 5:

[0632] The server compares the profile information with a job database and recommends the most suitable jobs and companies. The comparison is performed using a matching algorithm to extract the most suitable job listings. The results of the comparison are sent to the user's smartphone and can be viewed on the application.

[0633] Step 6:

[0634] Within the application, users initiate real-time interactions with a virtual advisor, who uses generative AI models to quickly answer their questions and provide customized career advice. The conversation is sent to a server in real time for analysis.

[0635] Step 7:

[0636] The server retrieves successful job-changing cases from the database and presents them to the user. The successful cases are compared with the user's profile information, and the most relevant ones are selected and displayed. This allows the server to provide useful information for the user's job-changing activities.

[0637] 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.

[0638] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[0639] System configuration

[0640] The system includes the following main elements:

[0641] 1. User terminal: Accepts user input and sends information to the server.

[0642] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[0643] 3. Database: Stores job listings, success stories, and profile information.

[0644] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[0645] Program processing

[0646] Enter and submit user information

[0647] A user enters their profile information, work history, skills, and interests into an input form on the device. The device formats this information and sends it to the server. For example, a user enters their name, age, location, past work history, skills, and current areas of interest.

[0648] Data Analysis and Profiling

[0649] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of entry and reflects this in the profile. For example, if the emotion engine detects the user's enthusiasm when entering their work history, that information will also be included in the profile.

[0650] Resume auto-generation

[0651] The server fills in a resume template based on the generated profile information. It uses a sentence generation algorithm to automatically generate compelling resume content. It uses data from the emotion engine to generate content that highlights the user's interests and passions. For example, it converts success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[0652] Recommendations for suitable jobs and companies

[0653] The server compares the profile with a job database and lists the most suitable jobs and companies. It also takes into account data from the emotion engine and prioritizes job recommendations based on the user's particular interest and enthusiasm. For example, a user with a data scientist skill set will be recommended job openings at AI companies or companies specializing in data analysis.

[0654] Interview preparation support

[0655] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions interactively to the user. The device transmits the user's answers to the server in real time. The server analyzes the responses and uses emotional data from the emotion engine to generate the next question and feedback. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[0656] Presentation of success stories

[0657] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users. For example, job-seekers can read about successful job-change cases in the same industry and use them as reference.

[0658] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0659] The processing flow will be explained below.

[0660] Step 1:

[0661] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[0662] Step 2:

[0663] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[0664] Step 3:

[0665] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[0666] Step 4:

[0667] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[0668] Step 5:

[0669] The server uses an emotion engine to analyze the user's emotional state as they type. For example, when a user enters their work history, it can identify emotions such as excitement, interest, or anxiety based on the speed of their keystrokes, the content of their input, their facial expressions, and their tone of voice.

[0670] Step 6:

[0671] The server then generates a profile based on the analysis results and emotional data, which takes into account the user's emotional state as well as their past successes and key skill sets.

[0672] Step 7:

[0673] The server then fills in a resume template based on the generated profile, and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters and incorporating data from the sentiment engine.

[0674] Step 8:

[0675] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[0676] Step 9:

[0677] The server compares the job market database to create a list of jobs and companies that best fit the profile. This matching process selects the most suitable job listings based on the user's skill set and past work experience. It also takes into account emotional data and prioritizes job listings and companies that the user has shown interest in.

[0678] Step 10:

[0679] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[0680] Step 11:

[0681] The user starts an interview practice session from a terminal. The terminal acts as a virtual interviewer and asks questions interactively to the user. The emotion engine analyzes the user's emotions in real time as they answer and sends the results to the server.

[0682] Step 12:

[0683] The server analyzes the user's responses and emotional data to generate the next question or feedback. For example, if it detects that the user is nervous, it will provide advice to ease the tension. If a positive emotion is detected, it will generate a question that will bring out that emotion.

[0684] Step 13:

[0685] The server generates the next question and feedback based on the analysis results and emotion data, and sends them to the device. The user receives the feedback and prepares for the next question.

[0686] Step 14:

[0687] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users.

[0688] Through these processing steps, the system helps job seekers make optimal career choices and guides them to a successful job search. The combination of an emotion engine enables more personalized advice and support that takes into account the user's emotions.

[0689] Example 2

[0690] 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."

[0691] Conventional job change support systems have difficulty in providing adequate personalized advice and support because they are unable to consider the emotions of job seekers. Furthermore, when structuring and analyzing input information and matching resumes with job offers, the systems are unable to reflect the user's enthusiasm and interests, making it difficult to recommend the most suitable jobs and companies.

[0692] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting personal information, work history, skills, and interests from a job seeker; means for structuring the input information and transmitting it to the server; means for analyzing the input information and generating a profile of the job seeker; means for analyzing the job seeker's emotions from the input information using an emotion engine; means for generating a profile using the analysis results and emotion data; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers for interview practice and providing feedback; and means for acquiring and presenting success stories to the job seeker. This enables personalized job change support that takes emotions into consideration and makes it possible to recommend optimal jobs and companies that reflect the user's enthusiasm and interests.

[0693] A "job seeker" refers to an individual who wishes to leave their current workplace and move to a new one.

[0694] "Personal information" refers to information that can identify an individual, such as name, age, or address.

[0695] "Work history" refers to work history information such as past job content, position, and employment period.

[0696] "Skills" refer to the abilities and techniques required for a particular job or occupation.

[0697] "Interest" refers to the degree of concern or involvement in a particular area or field.

[0698] "Terminal" refers to a device or equipment through which a user inputs information.

[0699] "Server" refers to a computer system that receives input data and analyzes and processes it.

[0700] "Structuring" refers to organizing input data into a certain format so that it can be stored in a database.

[0701] "Analysis" refers to the detailed analysis of input data and the extraction of useful information.

[0702] "Profile" refers to a detailed profile of an individual created based on analyzed data and information.

[0703] An "emotion engine" refers to a software module that analyzes and extracts emotional data from user input and behavior.

[0704] "Emotion Data" refers to information about a user's emotional state analyzed by an emotion engine.

[0705] "Automatic resume generation" refers to the process of automatically creating an attractive and relevant resume based on generated profile information.

[0706] "Job Database" refers to a database in which job information is stored.

[0707] "Recommendation" refers to presenting the most suitable job types and companies to the user.

[0708] "Practice interview" refers to the process by which a user prepares by answering questions in a virtual interview environment.

[0709] "Feedback" refers to advice or confirmation provided in response to a user's actions or responses.

[0710] "Success stories" refer to the experiences and interviews of people who have successfully changed jobs in the past.

[0711] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[0712] System configuration

[0713] The system includes the following main elements:

[0714] 1. User terminal: Accepts user input and sends information to the server.

[0715] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[0716] 3. Database: Stores job listings, success stories, and profile information.

[0717] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[0718] Enter and submit user information

[0719] Users enter their profile information, work history, skills, and interests into an input form on their device. Specific input information includes name, age, location, past work history, skills, and current areas of interest. For example, users might enter the following: "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, interested in data science."

[0720] The device formats this input information and sends it to the server using an HTTP request, using a format such as JSON.

[0721] Data Analysis and Profiling

[0722] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, the job title "software engineer" might be tagged with information like "interest in data science."

[0723] Emotion recognition

[0724] The server starts the emotion engine and analyzes the input data received from the user. The input content is used to analyze the user's emotional state, and the results are reflected in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile.

[0725] Generate a profile

[0726] The server uses the analysis results and emotional data to generate a user profile. The profile consists of skill sets, experience, interests, and emotional information. A specific example might be "Taro Yamada, 30 years old, with five years of engineering experience and a strong interest and enthusiasm for data science."

[0727] Auto-generate resumes

[0728] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it generates a sentence such as, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadline."

[0729] Recommendations for suitable jobs and companies

[0730] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[0731] Interview preparation support

[0732] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[0733] Presentation of success stories

[0734] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[0735] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0736] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0737] Step 1: Enter your user information

[0738] Users enter their profile information, work history, skills, and interests into an input form on their device. Input information includes name, age, location, past work history, skills, and current areas of interest. For example, they might enter "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, and interested in data science." The input data is then structured and ready for the next step.

[0739] Step 2: Submit user information

[0740] The terminal structures the information entered by the user and sends it to the server using an HTTP request. Specifically, the data to be sent is expressed in JSON format or similar and formatted so that it can be analyzed on the server side. The input data is then sent to the next analysis step.

[0741] Step 3: Analyze user information

[0742] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. For example, it tags the job title "software engineer" with information such as "interest in data science." The analyzed data is then formatted into a user profile.

[0743] Step 4: Recognize emotions

[0744] The server starts the emotion engine and analyzes the input data received from the user. It analyzes the user's emotional state from the input content and reflects the results in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile. The emotional data obtained in this step is used in the next step.

[0745] Step 5: Generate a profile

[0746] The server uses the analysis results and emotion data to generate a user profile. The profile consists of skill sets, experiences, interests, and emotion information. For example, it may contain information such as "Taro Yamada, 30 years old, 5 years of engineering experience, high interest and enthusiasm for data science." The generated profile is used in the next step.

[0747] Step 6: Auto-generate your resume

[0748] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it might generate a sentence like, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadlines." The generated resume is then provided to the user.

[0749] Step 7: Recommend suitable jobs and companies

[0750] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[0751] Step 8: Interview preparation assistance

[0752] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[0753] Step 9: Present success stories

[0754] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[0755] Through these steps, the system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[0756] (Application example 2)

[0757] 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."

[0758] Conventional job change support systems provided job information without considering the feelings of job seekers, resulting in a limited user experience and a lack of feedback and advice that reflected individual needs and feelings. They also lacked a mechanism for providing appropriate career advice and job recommendations specifically tailored to factory workers. This made it difficult for workers to effectively utilize their skills and find new career paths.

[0759] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0760] In this invention, the server includes: means for inputting the job seeker's personal information, work history, skills, and interests; means for analyzing the input information and generating a profile; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers and providing feedback for interview practice; means for acquiring success stories and presenting them to the job seeker; means for analyzing emotions and adjusting feedback and recommendations based on the job seeker's emotional state; and means for being installed in a robot and providing career advice to factory workers. This enables job seekers to receive job information and career advice tailored to their emotions and needs, making it possible to provide optimal career support, particularly for factory workers.

[0761] A "job seeker" is an individual who intends to leave their current job and take up a new one.

[0762] "Personal information" refers to information that identifies a specific individual, such as the job seeker's name, age, address, and contact information.

[0763] "Work history" refers to information about the type of work a job seeker has done in the past, the duration of that work, and the nature of the work.

[0764] "Skills" refers to the specialized knowledge, techniques, and abilities that job seekers possess.

[0765] "Interests" refers to information about the fields, industries, and job types that job seekers are interested in.

[0766] "Analysis" refers to the use of computer technology to analyze input information and extract its meaning and patterns.

[0767] A "profile" is a comprehensive data set generated based on a job seeker's personal information, work history, skills, interests, etc.

[0768] A resume is a document that lists the work history, skills, and qualifications of a job seeker.

[0769] A "job database" is a database that stores multiple job listings.

[0770] "Matching" is the process of comparing the generated profile with job information in the job database to find the best match.

[0771] "Recommendation" means suggesting suitable jobs and companies to job seekers based on the results of the comparison.

[0772] "Practice interviews" are mock question and answer sessions in preparation for the actual interview.

[0773] "Feedback" refers to evaluations and advice provided to job seekers during practice interviews, etc.

[0774] "Success stories" are the experiences and stories of other job seekers who have been successful in their job search, and are provided as reference information.

[0775] "Analyzing emotions" means measuring the emotional state of job seekers and analyzing the data based on that state.

[0776] A "robot" is a mechanical device that operates automatically and has the function of performing specific tasks at a factory or other work site.

[0777] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information, and is a system that combines an emotion engine. The system inputs the job seeker's personal information, work history, skills, and interests, analyzes this information, and generates a profile. It then automatically generates a resume based on the profile and compares it with a job database to recommend the most suitable jobs and companies. It also analyzes questions and answers for interview practice, providing real-time feedback, and presents success stories.

[0778] The system includes the following main elements:

[0779] 1. User Device:

[0780] It is a means for users to enter personal information, work experience, skills, and interests, which is then formatted and sent to a server. Examples include devices such as smartphones, PCs, and tablets.

[0781] 2. Server:

[0782] The server is responsible for centralizing and analyzing data. It analyzes the data received from users and generates a profile. Emotional data analyzed by the emotion engine is also reflected in the profile. Based on the generated profile, a resume is automatically generated and compared with a job database to recommend the most suitable job type and company. It also provides real-time feedback during interview practice and presents success stories.

[0783] 3. Database:

[0784] It includes a database for storing history information, job listings, and success stories. The server communicates with the database to retrieve and store the required information.

[0785] 4. Emotion Engine:

[0786] Analyzes the emotions of users when they input or respond. For example, analyzes the user's emotional state when they input and reflects the results in their profile. The emotion engine adjusts advice and feedback based on the user's emotions.

[0787] 5. Applications installed on the robot:

[0788] The application is installed on a robot to provide career advice to factory workers. It recommends suitable jobs and positions based on the worker's skills and experience. It also uses an emotion engine to recognize the worker's emotional state and provide appropriate feedback and advice in real time.

[0789] As a concrete example, consider the following prompt text entered by a user on a smartphone or tablet:

[0790] Example prompt sentence:

[0791] "I have been working on an automobile production line for five years. I am particularly good at operating and maintaining robots. I am interested in learning new skills and am also studying automation using AI. Please let me know if there are any job openings."

[0792] The system analyzes this input information, generates a profile, and automatically generates a resume. It also compares it with a job database to recommend the most suitable jobs and companies, and conducts interview practice sessions. It also presents success stories to motivate users. The emotion engine detects the user's emotions when they enter information and adjusts the feedback and advice provided based on that information.

[0793] By linking with the emotion engine and database, the server can provide more personalized career advice, allowing job seekers to receive the most appropriate job information and career support tailored to their needs and emotions. Similar support can also be provided to factory workers.

[0794] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0795] Step 1:

[0796] The user enters the job seeker's personal information, work experience, skills, and interests. For example, the user enters information using prompts on a smartphone or tablet. The entered information is formatted by the device and sent to the server. The entered data may include, for example, name, age, address, past work experience, skills, and areas of interest.

[0797] input:

[0798] Personal information (name, age, address)

[0799] Work history (past job content, period)

[0800] Skills (specialized knowledge, techniques)

[0801] Areas of Interest

[0802] output:

[0803] Formatted data sent to the server

[0804] Step 2:

[0805] The server analyzes the received user information and generates a profile. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of input and reflects that data in the profile.

[0806] input:

[0807] User information (personal information, work history, skills, areas of interest)

[0808] Emotional data (emotional state at the time of input)

[0809] output:

[0810] Generated User Profile

[0811] Step 3:

[0812] The server automatically generates a resume based on the generated profile. It embeds the profile data into a resume template and uses a text generation algorithm to create an appealing resume. It also uses emotional data to generate content that emphasizes the user's interests and passions.

[0813] input:

[0814] Generated User Profile

[0815] Emotional Data

[0816] output:

[0817] Auto-generated resume

[0818] Step 4:

[0819] The server compares the created profile with a job database and recommends the most suitable jobs and companies. It also takes into account emotional data and prioritizes jobs that the user has shown particular interest or enthusiasm for.

[0820] input:

[0821] Generated User Profile

[0822] Job Database

[0823] output:

[0824] List of recommended jobs and companies

[0825] Step 5:

[0826] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively to the user, whose answers are sent to the server in real time.

[0827] input:

[0828] User interview answers

[0829] output:

[0830] Submitted response data

[0831] Step 6:

[0832] The server analyzes the user's interview responses and generates the next question and feedback using the emotion data from the emotion engine. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[0833] input:

[0834] Interview response data

[0835] Emotional Data

[0836] output:

[0837] Next Questions and Feedback

[0838] Step 7:

[0839] The server retrieves success stories from the database and presents them to the user. Based on the data from the emotion engine, it selects success stories that are likely to interest the user.

[0840] input:

[0841] Emotional Data

[0842] Success story database

[0843] output:

[0844] Success stories presented

[0845] Step 8:

[0846] The application installed on the robot provides career advice to workers, recommending suitable tasks and jobs based on their skills and experience, and using an emotion engine to recognize the worker's emotional state and provide feedback and advice in real time.

[0847] input:

[0848] Worker skills, experience, and emotional data

[0849] output:

[0850] Career advice and feedback

[0851] 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.

[0852] 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.

[0853] 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.

[0854] [Third embodiment]

[0855] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0856] 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.

[0857] 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).

[0858] 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.

[0859] 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.

[0860] 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).

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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."

[0867] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information. The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, and interests, providing comprehensive support throughout the entire job search process.

[0868] System configuration

[0869] The system includes the following main elements:

[0870] 1. User terminal: Accepts user input and sends information to the server.

[0871] 2. Server: Analyzes user information, generates profiles, automatically generates resumes, recommends jobs, provides interview practice, and presents success stories.

[0872] 3. Database: Stores job listings, success stories, and profile information.

[0873] Program processing

[0874] Enter and submit user information

[0875] A user inputs their profile information, work history, skills, and interests into a terminal. The terminal formats this input information and sends it to a server. For example, a user inputs their name, age, location, past work history, skills, and current interests.

[0876] Data Analysis and Profiling

[0877] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, if a user has experience as a project manager, their leadership and project management skills will be emphasized.

[0878] Resume auto-generation

[0879] The server then uses the generated profile information to fill in a resume template, for example, converting success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[0880] Recommendations for suitable jobs and companies

[0881] The server compares the profile with a job database and lists the most suitable jobs and companies. For example, if a user has the skillset of a data scientist, it will recommend job openings at AI companies or companies specializing in data analysis.

[0882] Interview preparation support

[0883] The user starts an interview practice session on the device and interacts with a virtual interviewer. The device sends the user's answers to the server in real time. The server analyzes the user's answers and generates the next question and feedback. For example, it provides examples of appropriate answers and suggestions for improvement in response to the question, "What are your strengths?"

[0884] Presentation of success stories

[0885] The server retrieves interviews and stories of successful job-changers from the database and presents them to users. For example, job-changers can read about successful job-change cases in the same industry and use them as reference.

[0886] Through the above process, this system helps job seekers make optimal career choices and lead their job search to success.

[0887] The processing flow will be explained below.

[0888] Step 1:

[0889] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[0890] Step 2:

[0891] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[0892] Step 3:

[0893] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[0894] Step 4:

[0895] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[0896] Step 5:

[0897] The server generates a profile based on the analysis results, which includes the user's past successes and key skill sets.

[0898] Step 6:

[0899] Based on the generated profile, the server fills in a resume template with information and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters.

[0900] Step 7:

[0901] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[0902] Step 8:

[0903] The server compares the job market database to find the best jobs and companies for the profile created. This matching process selects the best job opportunities based on skill sets and past work experience.

[0904] Step 9:

[0905] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[0906] Step 10:

[0907] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively with the user.

[0908] Step 11:

[0909] The device receives the user's response and sends it to the server in real time, where the server analyzes the response and generates the next question or feedback.

[0910] Step 12:

[0911] The server generates feedback for the next question and response from the analysis results and sends it to the terminal, where the user receives the feedback and prepares for the next question.

[0912] Step 13:

[0913] The server retrieves interviews and stories of successful job-changers from a database and sends them to the terminal to motivate users. Users can view these success stories and learn from them.

[0914] Through the above processing steps, this system helps job seekers make optimal career choices and guides them to a successful job search.

[0915] Example 1

[0916] 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."

[0917] Conventional career change support systems struggle to automatically generate resumes that fully reflect job seekers' skills and interests, or recommend the most suitable jobs and companies. Furthermore, they lack real-time feedback during interview practice sessions, preventing job seekers from effectively preparing for interviews. Furthermore, there is a lack of a way to provide job seekers with specific advice using success stories. To solve these issues, a detailed profile analysis of job seekers, automatic resume generation using a generative AI model, real-time interview feedback, and the presentation of success stories are required.

[0918] 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.

[0919] In this invention, the server includes: a means for generating a profile for a job seeker; a means for embedding information into a template based on the profile information generated using a generative AI model to automatically generate a resume; a means for recommending optimal jobs and companies; a means for interacting with a virtual interviewer, sending responses to the server in real time, and generating subsequent questions and feedback; and a means for extracting important key points from the user's work history and categorizing skills and interests using natural language processing technology for data analysis and profiling. This not only enables detailed profile analysis of job seekers, but also enables the automatic generation of resumes using the generative AI model and the recommendation of optimal jobs and companies. It also provides real-time feedback during practice interviews and provides specific advice to job seekers using success stories.

[0920] "Career seekers" refer to individuals who wish to change occupations.

[0921] "Personal information" refers to information that can identify a specific individual, such as name, age, or location.

[0922] "Work history" refers to information about past jobs, positions, and job content.

[0923] "Skills" refer to the techniques and abilities possessed in a particular job or field.

[0924] "Interest" refers to an interest in a particular field of work or occupation.

[0925] "Input means" refers to the interface or device through which a user provides information to the system.

[0926] "Means of analysis" refers to the software or algorithms used to process input information and convert it into meaningful data.

[0927] A "profile" refers to data that combines a job seeker's personal information, work history, skills, and interests.

[0928] A "resume" refers to a document that shows the work history and skills of a job seeker.

[0929] "Means of automatic generation" refers to the process by which a system automatically creates documents or information based on input data.

[0930] A "generative AI model" refers to a model that uses artificial intelligence technology to generate text and process information.

[0931] A "template" refers to a pre-prepared document or format into which information can be embedded.

[0932] "Job database" refers to a database system that stores multiple job information.

[0933] "Recommender" refers to algorithms or software that suggest the best options based on input criteria and profiles.

[0934] "Interview practice" refers to providing a virtual interview environment in which users can practice to prepare for an actual interview.

[0935] "Feedback" refers to information that provides users with suggestions for improvement or advice.

[0936] "Success stories" refer to specific examples or stories of other people who have changed jobs successfully.

[0937] "Virtual interviewer" refers to a program provided by the system that asks interview questions and evaluates the user's answers.

[0938] "Data analysis" refers to the process of processing input data using statistical methods and algorithms to extract useful information.

[0939] "Profiling" refers to the process of creating a profile that summarizes the characteristics and tendencies of individual users based on the results of data analysis.

[0940] This invention is a platform that utilizes generative AI to provide customized career advice and job information to job seekers. The system is broadly composed of three main components: a user terminal, a server, and a database.

[0941] The user terminal accepts input from job seekers. When users enter their personal information, work history, skills, and interests into the terminal, the terminal formats this information and sends it to the server. Specific hardware used is a PC or smartphone, and software used is a web browser or dedicated application.

[0942] The server receives the submitted information and processes it for data analysis and profiling. The received information is stored in a database and an analysis module is launched. Analysis is performed using Python natural language processing (NLP) libraries (e.g., NLTK and Spacy) and machine learning frameworks (e.g., scikit-learn and TensorFlow). The analysis module extracts important key points from the user's work history and categorizes their skills and interests.

[0943] For example, a user enters the following information:

[0944] Name: Yamada Taro

[0945] Age: 30

[0946] Location: metropolis

[0947] Work experience: 5 years as a project manager

[0948] Skills: Project management, leadership

[0949] Areas of interest: AI and Data Science

[0950] The server uses this information to extract key points such as:

[0951] Project management experience: 5 years

[0952] Key skills: Leadership, project management

[0953] Areas of interest: AI and Data Science

[0954] Based on the generated profile, the server automatically generates a resume. Using a generative AI model (e.g., GPT-4), the profile information is embedded in a resume template. An example of a prompt for specific sentence generation is shown below:

[0955] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0956] The server also compares the profile information with a job database to recommend suitable jobs and companies. The job database contains multiple job listings, which are matched using SQL queries. The server recommends the following job listings:

[0957] Data Scientist (Work location: large city, Company name: major IT company)

[0958] Project Manager (Location: Large city, Company: Consulting company)

[0959] Additionally, the server provides interview practice sessions to help users prepare for interviews. Users interact with a virtual interviewer on their device and send their answers to the server in real time. The server then analyzes the answers and generates the next questions and feedback. Google Cloud Speech-to-Text API is used for speech recognition, and a generative AI model (e.g., GPT-4) generates the feedback.

[0960] Finally, the server retrieves success stories from the database and presents them to the user. This allows the user to refer to successful cases in similar industries or occupations and develop specific career change strategies. For example, it could present interview articles and stories of successful job-changers in the same occupation.

[0961] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0962] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0963] Step 1: Enter and submit user information

[0964] Users input their personal information, work history, skills, and interests into the user terminal. Specific input information includes:

[0965] Name: Yamada Taro

[0966] Age: 30

[0967] Location: metropolis

[0968] Work experience: 5 years as a project manager

[0969] Skills: Project management, leadership

[0970] Areas of interest: AI and Data Science

[0971] The device formats this information (for example, in JSON format) and sends it to the server. As input, there is the data provided by the user, and as output, there is the formatted data sent to the server.

[0972] Step 2: Data analysis and profiling

[0973] The server stores the received user information in a database and launches an analysis module. The input is the transmitted data (user information), and the output is the analysis results. Natural language processing (NLP) techniques are used for the analysis, using Python libraries (NLTK and Spacy) and machine learning frameworks (scikit-learn and TensorFlow). Specifically, the server extracts the following key points from the user's work history:

[0974] Project management experience: 5 years

[0975] Key skills: Leadership, project management

[0976] Areas of interest: AI and Data Science

[0977] Step 3: Auto-generate your resume

[0978] The server automatically generates a resume based on the generated profile information. It uses the profile information as input and generates a resume as output. It uses a generative AI model (e.g., GPT-4) to embed the profile information into a resume template. Specific operations include using prompts such as:

[0979] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[0980] This will generate a partial resume:

[0981] My name is Taro Yamada. I have five years of experience as a project manager and have successfully led large-scale projects using PMBOK and agile methods. I am particularly confident in my leadership and project management skills.

[0982] Step 4: Recommend suitable jobs and companies

[0983] The server compares the profile information with the job database and lists the most suitable jobs and companies for the user. The profile information and job database are used as input, and recommendations are generated as output. Specifically, the server uses SQL queries to recommend jobs such as:

[0984] Data Scientist (Work location: large city, Company name: major IT company)

[0985] Project Manager (Location: Large city, Company: Consulting company)

[0986] Step 5: Interview preparation assistance

[0987] The user starts an interview practice session on the user's device and interacts with the virtual interviewer. The user's answers are used as input, and the next question and feedback are generated as output. The device sends the user's answers to the server in real time. Specifically, the virtual interviewer asks questions such as:

[0988] "What are your strengths?"

[0989] If the user answers "Leadership," the server asks for more details:

[0990] "Please tell us a specific story. For example, how you led a team."

[0991] Step 6: Present success stories

[0992] The server retrieves interviews and stories of successful job-changers from a database and presents them to the user. Success story data is used as input, and success story information is displayed to the user as output. Specifically, the server presents the following success stories:

[0993] "A successful project manager: Hanako Yamada has successfully managed projects at a major IT company and is currently working as a data scientist."

[0994] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[0995] (Application example 1)

[0996] 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."

[0997] In today's job-hunting environment, job seekers must obtain relevant job information from numerous sources and prepare to highlight their skills and experience. However, gathering information, creating resumes, and preparing for interviews requires a great deal of time and effort, making the job-hunting process difficult. Furthermore, opportunities to receive appropriate career advice are limited, making it difficult for job seekers to maintain their motivation. A particular problem is the lack of information analysis and customized career advice.

[0998] 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.

[0999] In this invention, the server includes means for inputting personal information, work history, skills, and interests from job seekers, means for analyzing the input information and generating a profile of the job seeker, means for automatically generating a resume based on the generated profile, means for comparing the generated profile with a job database and recommending optimal jobs and companies, and means for providing interactive career advice through real-time dialogue with a virtual advisor. This enables job seekers to efficiently and effectively advance their job search through automated data management and analysis and the provision of customized advice.

[1000] "Personal information" refers to information that can be used to identify an individual, such as the job seeker's name, age, address, and contact details.

[1001] "Work history" is information that indicates the job history and experience of a job seeker in the past.

[1002] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by job seekers.

[1003] "Interests" is information that indicates the job type or industry that a job seeker desires, and the field of work in which they are interested.

[1004] A "profile" is a comprehensive portrait of a job seeker that is generated by analyzing their personal information, work history, skills, and interests.

[1005] A resume is a document that a job seeker submits when looking for a new job, listing their work history, skills, educational background, etc.

[1006] A "job database" is a database that collects information about job openings, such as companies and job types.

[1007] The "best fit job type and company" refers to the job content and company that best suits the job seeker, selected based on the job seeker's profile information.

[1008] A "virtual advisor" is an artificial intelligence program designed to provide career advice through real-time dialogue.

[1009] "Interactive career advice" is a service that provides advice and information tailored to individual situations through dialogue with users.

[1010] The present invention is a system for comprehensively providing customized career advice and job information to job seekers. This system is constructed using the following hardware and software.

[1011] Hardware and Software

[1012] Hardware: Smartphone (iOS, Android)

[1013] software:

[1014] Frontend: React Native

[1015] Backend: Node.js, Express.js

[1016] Database: AWS DynamoDB

[1017] Generative AI models: OpenAI GPT-3, BERT

[1018] Implementation details

[1019] 1. Enter and submit user information

[1020] Users use a smartphone application to enter their profile information, work history, skills, and interests, which is then formatted into an appropriate data format, such as JSON, and sent to a back-end server.

[1021] 2. Data storage and analysis

[1022] The server stores the received user information in AWS DynamoDB. The stored data is analyzed by an analysis module running on Node.js and Express.js. The analysis module uses generative AI models (such as OpenAI GPT-3 and BERT) to extract key points from the user's work history and generate a profile.

[1023] 3. Auto-generate resumes

[1024] The server automatically fills in the resume template based on the profile information generated through the analysis, which is then converted into appropriate text based on the user's skills and success stories.

[1025] 4. Recommendations for suitable jobs and companies

[1026] The server compares the generated profile information with a job database and recommends suitable jobs and companies. The recommended job information is sent to the user's smartphone and can be viewed on the application.

[1027] 5. Interactive career advice

[1028] Within the application, users can engage in real-time interactions with a virtual advisor, who uses generative AI models to answer their questions and provide customized career advice.

[1029] 6. Presenting success stories

[1030] The server retrieves successful job-changing cases from the database and presents them to the user. This information serves as inspiration and reference material for the user's job-changing activities.

[1031] Examples and prompts

[1032] As a concrete example, consider a user who has experience as a project manager and is looking for a new career step. The user enters their work history into the application, which automatically generates a resume. The application then recommends suitable job listings and provides specific interview preparation advice from a virtual advisor.

[1033] Examples of prompts include:

[1034] "Auto-generate a resume for a project manager based on the user's work history."

[1035] "Recommend the best job openings for users with the following work experience."

[1036] This will enable job seekers to proceed with their job search efficiently and effectively.

[1037] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1038] Step 1:

[1039] A user launches the application on their smartphone and enters their personal information, work history, skills, and interests, which are then formatted into an appropriate data format, such as JSON, and sent to the server.

[1040] Step 2:

[1041] The server stores the received user information in AWS DynamoDB. It checks whether the received data is in the correct format and starts the storage process. If successful, the server generates a status indicating that the data has been saved and sends a trigger to proceed to the next step.

[1042] Step 3:

[1043] The server analyzes the stored data and uses generative AI models (OpenAI GPT-3 and BERT) to extract key points from the user's work history. Specifically, it takes the text data of the work history as input and uses natural language processing technology to extract key skill sets and roles.

[1044] Step 4:

[1045] A resume template is automatically generated based on the profile information generated by the analysis. The server acquires the profile information, embeds the relevant information in a pre-prepared resume template, and automatically generates a resume. The generated resume is displayed to the user as a preview.

[1046] Step 5:

[1047] The server compares the profile information with a job database and recommends the most suitable jobs and companies. The comparison is performed using a matching algorithm to extract the most suitable job listings. The results of the comparison are sent to the user's smartphone and can be viewed on the application.

[1048] Step 6:

[1049] Within the application, users initiate real-time interactions with a virtual advisor, who uses generative AI models to quickly answer their questions and provide customized career advice. The conversation is sent to a server in real time for analysis.

[1050] Step 7:

[1051] The server retrieves successful job-changing cases from the database and presents them to the user. The successful cases are compared with the user's profile information, and the most relevant ones are selected and displayed. This allows the server to provide useful information for the user's job-changing activities.

[1052] 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.

[1053] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[1054] System configuration

[1055] The system includes the following main elements:

[1056] 1. User terminal: Accepts user input and sends information to the server.

[1057] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[1058] 3. Database: Stores job listings, success stories, and profile information.

[1059] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[1060] Program processing

[1061] Enter and submit user information

[1062] A user enters their profile information, work history, skills, and interests into an input form on the device. The device formats this information and sends it to the server. For example, a user enters their name, age, location, past work history, skills, and current areas of interest.

[1063] Data Analysis and Profiling

[1064] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of entry and reflects this in the profile. For example, if the emotion engine detects the user's enthusiasm when entering their work history, that information will also be included in the profile.

[1065] Resume auto-generation

[1066] The server fills in a resume template based on the generated profile information. It uses a sentence generation algorithm to automatically generate compelling resume content. It uses data from the emotion engine to generate content that highlights the user's interests and passions. For example, it converts success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[1067] Recommendations for suitable jobs and companies

[1068] The server compares the profile with a job database and lists the most suitable jobs and companies. It also takes into account data from the emotion engine and prioritizes job recommendations based on the user's particular interest and enthusiasm. For example, a user with a data scientist skill set will be recommended job openings at AI companies or companies specializing in data analysis.

[1069] Interview preparation support

[1070] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions interactively to the user. The device transmits the user's answers to the server in real time. The server analyzes the responses and uses emotional data from the emotion engine to generate the next question and feedback. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[1071] Presentation of success stories

[1072] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users. For example, job-seekers can read about successful job-change cases in the same industry and use them as reference.

[1073] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1074] The processing flow will be explained below.

[1075] Step 1:

[1076] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[1077] Step 2:

[1078] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[1079] Step 3:

[1080] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[1081] Step 4:

[1082] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[1083] Step 5:

[1084] The server uses an emotion engine to analyze the user's emotional state as they type. For example, when a user enters their work history, it can identify emotions such as excitement, interest, or anxiety based on the speed of their keystrokes, the content of their input, their facial expressions, and their tone of voice.

[1085] Step 6:

[1086] The server then generates a profile based on the analysis results and emotional data, which takes into account the user's emotional state as well as their past successes and key skill sets.

[1087] Step 7:

[1088] The server then fills in a resume template based on the generated profile, and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters and incorporating data from the sentiment engine.

[1089] Step 8:

[1090] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[1091] Step 9:

[1092] The server compares the job market database to create a list of jobs and companies that best fit the profile. This matching process selects the most suitable job listings based on the user's skill set and past work experience. It also takes into account emotional data and prioritizes job listings and companies that the user has shown interest in.

[1093] Step 10:

[1094] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[1095] Step 11:

[1096] The user starts an interview practice session from a terminal. The terminal acts as a virtual interviewer and asks questions interactively to the user. The emotion engine analyzes the user's emotions in real time as they answer and sends the results to the server.

[1097] Step 12:

[1098] The server analyzes the user's responses and emotional data to generate the next question or feedback. For example, if it detects that the user is nervous, it will provide advice to ease the tension. If a positive emotion is detected, it will generate a question that will bring out that emotion.

[1099] Step 13:

[1100] The server generates the next question and feedback based on the analysis results and emotion data, and sends them to the device. The user receives the feedback and prepares for the next question.

[1101] Step 14:

[1102] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users.

[1103] Through these processing steps, the system helps job seekers make optimal career choices and guides them to a successful job search. The combination of an emotion engine enables more personalized advice and support that takes into account the user's emotions.

[1104] Example 2

[1105] 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."

[1106] Conventional job change support systems have difficulty in providing adequate personalized advice and support because they are unable to consider the emotions of job seekers. Furthermore, when structuring and analyzing input information and matching resumes with job offers, the systems are unable to reflect the user's enthusiasm and interests, making it difficult to recommend the most suitable jobs and companies.

[1107] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting personal information, work history, skills, and interests from a job seeker; means for structuring the input information and transmitting it to the server; means for analyzing the input information and generating a profile of the job seeker; means for analyzing the job seeker's emotions from the input information using an emotion engine; means for generating a profile using the analysis results and emotion data; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers for interview practice and providing feedback; and means for acquiring and presenting success stories to the job seeker. This enables personalized job change support that takes emotions into consideration and makes it possible to recommend optimal jobs and companies that reflect the user's enthusiasm and interests.

[1108] A "job seeker" refers to an individual who wishes to leave their current workplace and move to a new one.

[1109] "Personal information" refers to information that can identify an individual, such as name, age, or address.

[1110] "Work history" refers to work history information such as past job content, position, and employment period.

[1111] "Skills" refer to the abilities and techniques required for a particular job or occupation.

[1112] "Interest" refers to the degree of concern or involvement in a particular area or field.

[1113] "Terminal" refers to a device or equipment through which a user inputs information.

[1114] "Server" refers to a computer system that receives input data and analyzes and processes it.

[1115] "Structuring" refers to organizing input data into a certain format so that it can be stored in a database.

[1116] "Analysis" refers to the detailed analysis of input data and the extraction of useful information.

[1117] "Profile" refers to a detailed profile of an individual created based on analyzed data and information.

[1118] An "emotion engine" refers to a software module that analyzes and extracts emotional data from user input and behavior.

[1119] "Emotion Data" refers to information about a user's emotional state analyzed by an emotion engine.

[1120] "Automatic resume generation" refers to the process of automatically creating an attractive and relevant resume based on generated profile information.

[1121] "Job Database" refers to a database in which job information is stored.

[1122] "Recommendation" refers to presenting the most suitable job types and companies to the user.

[1123] "Practice interview" refers to the process by which a user prepares by answering questions in a virtual interview environment.

[1124] "Feedback" refers to advice or confirmation provided in response to a user's actions or responses.

[1125] "Success stories" refer to the experiences and interviews of people who have successfully changed jobs in the past.

[1126] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[1127] System configuration

[1128] The system includes the following main elements:

[1129] 1. User terminal: Accepts user input and sends information to the server.

[1130] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[1131] 3. Database: Stores job listings, success stories, and profile information.

[1132] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[1133] Enter and submit user information

[1134] Users enter their profile information, work history, skills, and interests into an input form on their device. Specific input information includes name, age, location, past work history, skills, and current areas of interest. For example, users might enter the following: "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, interested in data science."

[1135] The device formats this input information and sends it to the server using an HTTP request, using a format such as JSON.

[1136] Data Analysis and Profiling

[1137] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, the job title "software engineer" might be tagged with information like "interest in data science."

[1138] Emotion recognition

[1139] The server starts the emotion engine and analyzes the input data received from the user. The input content is used to analyze the user's emotional state, and the results are reflected in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile.

[1140] Generate a profile

[1141] The server uses the analysis results and emotional data to generate a user profile. The profile consists of skill sets, experience, interests, and emotional information. A specific example might be "Taro Yamada, 30 years old, with five years of engineering experience and a strong interest and enthusiasm for data science."

[1142] Auto-generate resumes

[1143] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it generates a sentence such as, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadline."

[1144] Recommendations for suitable jobs and companies

[1145] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[1146] Interview preparation support

[1147] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[1148] Presentation of success stories

[1149] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[1150] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1151] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1152] Step 1: Enter your user information

[1153] Users enter their profile information, work history, skills, and interests into an input form on their device. Input information includes name, age, location, past work history, skills, and current areas of interest. For example, they might enter "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, and interested in data science." The input data is then structured and ready for the next step.

[1154] Step 2: Submit user information

[1155] The terminal structures the information entered by the user and sends it to the server using an HTTP request. Specifically, the data to be sent is expressed in JSON format or similar and formatted so that it can be analyzed on the server side. The input data is then sent to the next analysis step.

[1156] Step 3: Analyze user information

[1157] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. For example, it tags the job title "software engineer" with information such as "interest in data science." The analyzed data is then formatted into a user profile.

[1158] Step 4: Recognize emotions

[1159] The server starts the emotion engine and analyzes the input data received from the user. It analyzes the user's emotional state from the input content and reflects the results in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile. The emotional data obtained in this step is used in the next step.

[1160] Step 5: Generate a profile

[1161] The server uses the analysis results and emotion data to generate a user profile. The profile consists of skill sets, experiences, interests, and emotion information. For example, it may contain information such as "Taro Yamada, 30 years old, 5 years of engineering experience, high interest and enthusiasm for data science." The generated profile is used in the next step.

[1162] Step 6: Auto-generate your resume

[1163] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it might generate a sentence like, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadlines." The generated resume is then provided to the user.

[1164] Step 7: Recommend suitable jobs and companies

[1165] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[1166] Step 8: Interview preparation assistance

[1167] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[1168] Step 9: Present success stories

[1169] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[1170] Through these steps, the system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1171] (Application example 2)

[1172] 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."

[1173] Conventional job change support systems provided job information without considering the feelings of job seekers, resulting in a limited user experience and a lack of feedback and advice that reflected individual needs and feelings. They also lacked a mechanism for providing appropriate career advice and job recommendations specifically tailored to factory workers. This made it difficult for workers to effectively utilize their skills and find new career paths.

[1174] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1175] In this invention, the server includes: means for inputting the job seeker's personal information, work history, skills, and interests; means for analyzing the input information and generating a profile; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers and providing feedback for interview practice; means for acquiring success stories and presenting them to the job seeker; means for analyzing emotions and adjusting feedback and recommendations based on the job seeker's emotional state; and means for being installed in a robot and providing career advice to factory workers. This enables job seekers to receive job information and career advice tailored to their emotions and needs, making it possible to provide optimal career support, particularly for factory workers.

[1176] A "job seeker" is an individual who intends to leave their current job and take up a new one.

[1177] "Personal information" refers to information that identifies a specific individual, such as the job seeker's name, age, address, and contact information.

[1178] "Work history" refers to information about the type of work a job seeker has done in the past, the duration of that work, and the nature of the work.

[1179] "Skills" refers to the specialized knowledge, techniques, and abilities that job seekers possess.

[1180] "Interests" refers to information about the fields, industries, and job types that job seekers are interested in.

[1181] "Analysis" refers to the use of computer technology to analyze input information and extract its meaning and patterns.

[1182] A "profile" is a comprehensive data set generated based on a job seeker's personal information, work history, skills, interests, etc.

[1183] A resume is a document that lists the work history, skills, and qualifications of a job seeker.

[1184] A "job database" is a database that stores multiple job listings.

[1185] "Matching" is the process of comparing the generated profile with job information in the job database to find the best match.

[1186] "Recommendation" means suggesting suitable jobs and companies to job seekers based on the results of the comparison.

[1187] "Practice interviews" are mock question and answer sessions in preparation for the actual interview.

[1188] "Feedback" refers to evaluations and advice provided to job seekers during practice interviews, etc.

[1189] "Success stories" are the experiences and stories of other job seekers who have been successful in their job search, and are provided as reference information.

[1190] "Analyzing emotions" means measuring the emotional state of job seekers and analyzing the data based on that state.

[1191] A "robot" is a mechanical device that operates automatically and has the function of performing specific tasks at a factory or other work site.

[1192] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information, and is a system that combines an emotion engine. The system inputs the job seeker's personal information, work history, skills, and interests, analyzes this information, and generates a profile. It then automatically generates a resume based on the profile and compares it with a job database to recommend the most suitable jobs and companies. It also analyzes questions and answers for interview practice, providing real-time feedback, and presents success stories.

[1193] The system includes the following main elements:

[1194] 1. User Device:

[1195] It is a means for users to enter personal information, work experience, skills, and interests, which is then formatted and sent to a server. Examples include devices such as smartphones, PCs, and tablets.

[1196] 2. Server:

[1197] The server is responsible for centralizing and analyzing data. It analyzes the data received from users and generates a profile. Emotional data analyzed by the emotion engine is also reflected in the profile. Based on the generated profile, a resume is automatically generated and compared with a job database to recommend the most suitable job type and company. It also provides real-time feedback during interview practice and presents success stories.

[1198] 3. Database:

[1199] It includes a database for storing history information, job listings, and success stories. The server communicates with the database to retrieve and store the required information.

[1200] 4. Emotion Engine:

[1201] Analyzes the emotions of users when they input or respond. For example, analyzes the user's emotional state when they input and reflects the results in their profile. The emotion engine adjusts advice and feedback based on the user's emotions.

[1202] 5. Applications installed on the robot:

[1203] The application is installed on a robot to provide career advice to factory workers. It recommends suitable jobs and positions based on the worker's skills and experience. It also uses an emotion engine to recognize the worker's emotional state and provide appropriate feedback and advice in real time.

[1204] As a concrete example, consider the following prompt text entered by a user on a smartphone or tablet:

[1205] Example prompt sentence:

[1206] "I have been working on an automobile production line for five years. I am particularly good at operating and maintaining robots. I am interested in learning new skills and am also studying automation using AI. Please let me know if there are any job openings."

[1207] The system analyzes this input information, generates a profile, and automatically generates a resume. It also compares it with a job database to recommend the most suitable jobs and companies, and conducts interview practice sessions. It also presents success stories to motivate users. The emotion engine detects the user's emotions when they enter information and adjusts the feedback and advice provided based on that information.

[1208] By linking with the emotion engine and database, the server can provide more personalized career advice, allowing job seekers to receive the most appropriate job information and career support tailored to their needs and emotions. Similar support can also be provided to factory workers.

[1209] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1210] Step 1:

[1211] The user enters the job seeker's personal information, work experience, skills, and interests. For example, the user enters information using prompts on a smartphone or tablet. The entered information is formatted by the device and sent to the server. The entered data may include, for example, name, age, address, past work experience, skills, and areas of interest.

[1212] input:

[1213] Personal information (name, age, address)

[1214] Work history (past job content, period)

[1215] Skills (specialized knowledge, techniques)

[1216] Areas of Interest

[1217] output:

[1218] Formatted data sent to the server

[1219] Step 2:

[1220] The server analyzes the received user information and generates a profile. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of input and reflects that data in the profile.

[1221] input:

[1222] User information (personal information, work history, skills, areas of interest)

[1223] Emotional data (emotional state at the time of input)

[1224] output:

[1225] Generated User Profile

[1226] Step 3:

[1227] The server automatically generates a resume based on the generated profile. It embeds the profile data into a resume template and uses a text generation algorithm to create an appealing resume. It also uses emotional data to generate content that emphasizes the user's interests and passions.

[1228] input:

[1229] Generated User Profile

[1230] Emotional Data

[1231] output:

[1232] Auto-generated resume

[1233] Step 4:

[1234] The server compares the created profile with a job database and recommends the most suitable jobs and companies. It also takes into account emotional data and prioritizes jobs that the user has shown particular interest or enthusiasm for.

[1235] input:

[1236] Generated User Profile

[1237] Job Database

[1238] output:

[1239] List of recommended jobs and companies

[1240] Step 5:

[1241] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively to the user, whose answers are sent to the server in real time.

[1242] input:

[1243] User interview answers

[1244] output:

[1245] Submitted response data

[1246] Step 6:

[1247] The server analyzes the user's interview responses and generates the next question and feedback using the emotion data from the emotion engine. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[1248] input:

[1249] Interview response data

[1250] Emotional Data

[1251] output:

[1252] Next Questions and Feedback

[1253] Step 7:

[1254] The server retrieves success stories from the database and presents them to the user. Based on the data from the emotion engine, it selects success stories that are likely to interest the user.

[1255] input:

[1256] Emotional Data

[1257] Success story database

[1258] output:

[1259] Success stories presented

[1260] Step 8:

[1261] The application installed on the robot provides career advice to workers, recommending suitable tasks and jobs based on their skills and experience, and using an emotion engine to recognize the worker's emotional state and provide feedback and advice in real time.

[1262] input:

[1263] Worker skills, experience, and emotional data

[1264] output:

[1265] Career advice and feedback

[1266] 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.

[1267] 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.

[1268] 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.

[1269] [Fourth embodiment]

[1270] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1271] 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.

[1272] 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).

[1273] 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.

[1274] 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.

[1275] 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).

[1276] 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.

[1277] 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.

[1278] 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.

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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."

[1283] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information. The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, and interests, providing comprehensive support throughout the entire job search process.

[1284] System configuration

[1285] The system includes the following main elements:

[1286] 1. User terminal: Accepts user input and sends information to the server.

[1287] 2. Server: Analyzes user information, generates profiles, automatically generates resumes, recommends jobs, provides interview practice, and presents success stories.

[1288] 3. Database: Stores job listings, success stories, and profile information.

[1289] Program processing

[1290] Enter and submit user information

[1291] A user inputs their profile information, work history, skills, and interests into a terminal. The terminal formats this input information and sends it to a server. For example, a user inputs their name, age, location, past work history, skills, and current interests.

[1292] Data Analysis and Profiling

[1293] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, if a user has experience as a project manager, their leadership and project management skills will be emphasized.

[1294] Resume auto-generation

[1295] The server then uses the generated profile information to fill in a resume template, for example, converting success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[1296] Recommendations for suitable jobs and companies

[1297] The server compares the profile with a job database and lists the most suitable jobs and companies. For example, if a user has the skillset of a data scientist, it will recommend job openings at AI companies or companies specializing in data analysis.

[1298] Interview preparation support

[1299] The user starts an interview practice session on the device and interacts with a virtual interviewer. The device sends the user's answers to the server in real time. The server analyzes the user's answers and generates the next question and feedback. For example, it provides examples of appropriate answers and suggestions for improvement in response to the question, "What are your strengths?"

[1300] Presentation of success stories

[1301] The server retrieves interviews and stories of successful job-changers from the database and presents them to users. For example, job-changers can read about successful job-change cases in the same industry and use them as reference.

[1302] Through the above process, this system helps job seekers make optimal career choices and lead their job search to success.

[1303] The processing flow will be explained below.

[1304] Step 1:

[1305] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[1306] Step 2:

[1307] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[1308] Step 3:

[1309] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[1310] Step 4:

[1311] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[1312] Step 5:

[1313] The server generates a profile based on the analysis results, which includes the user's past successes and key skill sets.

[1314] Step 6:

[1315] Based on the generated profile, the server fills in a resume template with information and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters.

[1316] Step 7:

[1317] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[1318] Step 8:

[1319] The server compares the job market database to find the best jobs and companies for the profile created. This matching process selects the best job opportunities based on skill sets and past work experience.

[1320] Step 9:

[1321] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[1322] Step 10:

[1323] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively with the user.

[1324] Step 11:

[1325] The device receives the user's response and sends it to the server in real time, where the server analyzes the response and generates the next question or feedback.

[1326] Step 12:

[1327] The server generates feedback for the next question and response from the analysis results and sends it to the terminal, where the user receives the feedback and prepares for the next question.

[1328] Step 13:

[1329] The server retrieves interviews and stories of successful job-changers from a database and sends them to the terminal to motivate users. Users can view these success stories and learn from them.

[1330] Through the above processing steps, this system helps job seekers make optimal career choices and guides them to a successful job search.

[1331] Example 1

[1332] 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."

[1333] Conventional career change support systems struggle to automatically generate resumes that fully reflect job seekers' skills and interests, or recommend the most suitable jobs and companies. Furthermore, they lack real-time feedback during interview practice sessions, preventing job seekers from effectively preparing for interviews. Furthermore, there is a lack of a way to provide job seekers with specific advice using success stories. To solve these issues, a detailed profile analysis of job seekers, automatic resume generation using a generative AI model, real-time interview feedback, and the presentation of success stories are required.

[1334] 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.

[1335] In this invention, the server includes: a means for generating a profile for a job seeker; a means for embedding information into a template based on the profile information generated using a generative AI model to automatically generate a resume; a means for recommending optimal jobs and companies; a means for interacting with a virtual interviewer, sending responses to the server in real time, and generating subsequent questions and feedback; and a means for extracting important key points from the user's work history and categorizing skills and interests using natural language processing technology for data analysis and profiling. This not only enables detailed profile analysis of job seekers, but also enables the automatic generation of resumes using the generative AI model and the recommendation of optimal jobs and companies. It also provides real-time feedback during practice interviews and provides specific advice to job seekers using success stories.

[1336] "Career seekers" refer to individuals who wish to change occupations.

[1337] "Personal information" refers to information that can identify a specific individual, such as name, age, or location.

[1338] "Work history" refers to information about past jobs, positions, and job content.

[1339] "Skills" refer to the techniques and abilities possessed in a particular job or field.

[1340] "Interest" refers to an interest in a particular field of work or occupation.

[1341] "Input means" refers to the interface or device through which a user provides information to the system.

[1342] "Means of analysis" refers to the software or algorithms used to process input information and convert it into meaningful data.

[1343] A "profile" refers to data that combines a job seeker's personal information, work history, skills, and interests.

[1344] A "resume" refers to a document that shows the work history and skills of a job seeker.

[1345] "Means of automatic generation" refers to the process by which a system automatically creates documents or information based on input data.

[1346] A "generative AI model" refers to a model that uses artificial intelligence technology to generate text and process information.

[1347] A "template" refers to a pre-prepared document or format into which information can be embedded.

[1348] "Job database" refers to a database system that stores multiple job information.

[1349] "Recommender" refers to algorithms or software that suggest the best options based on input criteria and profiles.

[1350] "Interview practice" refers to providing a virtual interview environment in which users can practice to prepare for an actual interview.

[1351] "Feedback" refers to information that provides users with suggestions for improvement or advice.

[1352] "Success stories" refer to specific examples or stories of other people who have changed jobs successfully.

[1353] "Virtual interviewer" refers to a program provided by the system that asks interview questions and evaluates the user's answers.

[1354] "Data analysis" refers to the process of processing input data using statistical methods and algorithms to extract useful information.

[1355] "Profiling" refers to the process of creating a profile that summarizes the characteristics and tendencies of individual users based on the results of data analysis.

[1356] This invention is a platform that utilizes generative AI to provide customized career advice and job information to job seekers. The system is broadly composed of three main components: a user terminal, a server, and a database.

[1357] The user terminal accepts input from job seekers. When users enter their personal information, work history, skills, and interests into the terminal, the terminal formats this information and sends it to the server. Specific hardware used is a PC or smartphone, and software used is a web browser or dedicated application.

[1358] The server receives the submitted information and processes it for data analysis and profiling. The received information is stored in a database and an analysis module is launched. Analysis is performed using Python natural language processing (NLP) libraries (e.g., NLTK and Spacy) and machine learning frameworks (e.g., scikit-learn and TensorFlow). The analysis module extracts important key points from the user's work history and categorizes their skills and interests.

[1359] For example, a user enters the following information:

[1360] Name: Yamada Taro

[1361] Age: 30

[1362] Location: metropolis

[1363] Work experience: 5 years as a project manager

[1364] Skills: Project management, leadership

[1365] Areas of interest: AI and Data Science

[1366] The server uses this information to extract key points such as:

[1367] Project management experience: 5 years

[1368] Key skills: Leadership, project management

[1369] Areas of interest: AI and Data Science

[1370] Based on the generated profile, the server automatically generates a resume. Using a generative AI model (e.g., GPT-4), the profile information is embedded in a resume template. An example of a prompt for specific sentence generation is shown below:

[1371] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[1372] The server also compares the profile information with a job database to recommend suitable jobs and companies. The job database contains multiple job listings, which are matched using SQL queries. The server recommends the following job listings:

[1373] Data Scientist (Work location: large city, Company name: major IT company)

[1374] Project Manager (Location: Large city, Company: Consulting company)

[1375] Additionally, the server provides interview practice sessions to help users prepare for interviews. Users interact with a virtual interviewer on their device and send their answers to the server in real time. The server then analyzes the answers and generates the next questions and feedback. Google Cloud Speech-to-Text API is used for speech recognition, and a generative AI model (e.g., GPT-4) generates the feedback.

[1376] Finally, the server retrieves success stories from the database and presents them to the user. This allows the user to refer to successful cases in similar industries or occupations and develop specific career change strategies. For example, it could present interview articles and stories of successful job-changers in the same occupation.

[1377] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[1378] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1379] Step 1: Enter and submit user information

[1380] Users input their personal information, work history, skills, and interests into the user terminal. Specific input information includes:

[1381] Name: Yamada Taro

[1382] Age: 30

[1383] Location: metropolis

[1384] Work experience: 5 years as a project manager

[1385] Skills: Project management, leadership

[1386] Areas of interest: AI and Data Science

[1387] The device formats this information (for example, in JSON format) and sends it to the server. As input, there is the data provided by the user, and as output, there is the formatted data sent to the server.

[1388] Step 2: Data analysis and profiling

[1389] The server stores the received user information in a database and launches an analysis module. The input is the transmitted data (user information), and the output is the analysis results. Natural language processing (NLP) techniques are used for the analysis, using Python libraries (NLTK and Spacy) and machine learning frameworks (scikit-learn and TensorFlow). Specifically, the server extracts the following key points from the user's work history:

[1390] Project management experience: 5 years

[1391] Key skills: Leadership, project management

[1392] Areas of interest: AI and Data Science

[1393] Step 3: Auto-generate your resume

[1394] The server automatically generates a resume based on the generated profile information. It uses the profile information as input and generates a resume as output. It uses a generative AI model (e.g., GPT-4) to embed the profile information into a resume template. Specific operations include using prompts such as:

[1395] "Generate a resume statement highlighting your leadership and project management skills based on a success story as a project manager. Success Story: 'I managed large-scale projects to achieve results on time.'"

[1396] This will generate a partial resume:

[1397] My name is Taro Yamada. I have five years of experience as a project manager and have successfully led large-scale projects using PMBOK and agile methods. I am particularly confident in my leadership and project management skills.

[1398] Step 4: Recommend suitable jobs and companies

[1399] The server compares the profile information with the job database and lists the most suitable jobs and companies for the user. The profile information and job database are used as input, and recommendations are generated as output. Specifically, the server uses SQL queries to recommend jobs such as:

[1400] Data Scientist (Work location: large city, Company name: major IT company)

[1401] Project Manager (Location: Large city, Company: Consulting company)

[1402] Step 5: Interview preparation assistance

[1403] The user starts an interview practice session on the user's device and interacts with the virtual interviewer. The user's answers are used as input, and the next question and feedback are generated as output. The device sends the user's answers to the server in real time. Specifically, the virtual interviewer asks questions such as:

[1404] "What are your strengths?"

[1405] If the user answers "Leadership," the server asks for more details:

[1406] "Please tell us a specific story. For example, how you led a team."

[1407] Step 6: Present success stories

[1408] The server retrieves interviews and stories of successful job-changers from a database and presents them to the user. Success story data is used as input, and success story information is displayed to the user as output. Specifically, the server presents the following success stories:

[1409] "A successful project manager: Hanako Yamada has successfully managed projects at a major IT company and is currently working as a data scientist."

[1410] Through the above processing steps, this system helps job seekers make optimal career choices and lead their job search to success.

[1411] (Application example 1)

[1412] 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."

[1413] In today's job-hunting environment, job seekers must obtain relevant job information from numerous sources and prepare to highlight their skills and experience. However, gathering information, creating resumes, and preparing for interviews requires a great deal of time and effort, making the job-hunting process difficult. Furthermore, opportunities to receive appropriate career advice are limited, making it difficult for job seekers to maintain their motivation. A particular problem is the lack of information analysis and customized career advice.

[1414] 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.

[1415] In this invention, the server includes means for inputting personal information, work history, skills, and interests from job seekers, means for analyzing the input information and generating a profile of the job seeker, means for automatically generating a resume based on the generated profile, means for comparing the generated profile with a job database and recommending optimal jobs and companies, and means for providing interactive career advice through real-time dialogue with a virtual advisor. This enables job seekers to efficiently and effectively advance their job search through automated data management and analysis and the provision of customized advice.

[1416] "Personal information" refers to information that can be used to identify an individual, such as the job seeker's name, age, address, and contact details.

[1417] "Work history" is information that indicates the job history and experience of a job seeker in the past.

[1418] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by job seekers.

[1419] "Interests" is information that indicates the job type or industry that a job seeker desires, and the field of work in which they are interested.

[1420] A "profile" is a comprehensive portrait of a job seeker that is generated by analyzing their personal information, work history, skills, and interests.

[1421] A resume is a document that a job seeker submits when looking for a new job, listing their work history, skills, educational background, etc.

[1422] A "job database" is a database that collects information about job openings, such as companies and job types.

[1423] The "best fit job type and company" refers to the job content and company that best suits the job seeker, selected based on the job seeker's profile information.

[1424] A "virtual advisor" is an artificial intelligence program designed to provide career advice through real-time dialogue.

[1425] "Interactive career advice" is a service that provides advice and information tailored to individual situations through dialogue with users.

[1426] The present invention is a system for comprehensively providing customized career advice and job information to job seekers. This system is constructed using the following hardware and software.

[1427] Hardware and Software

[1428] Hardware: Smartphone (iOS, Android)

[1429] software:

[1430] Frontend: React Native

[1431] Backend: Node.js, Express.js

[1432] Database: AWS DynamoDB

[1433] Generative AI models: OpenAI GPT-3, BERT

[1434] Implementation details

[1435] 1. Enter and submit user information

[1436] Users use a smartphone application to enter their profile information, work history, skills, and interests, which is then formatted into an appropriate data format, such as JSON, and sent to a back-end server.

[1437] 2. Data storage and analysis

[1438] The server stores the received user information in AWS DynamoDB. The stored data is analyzed by an analysis module running on Node.js and Express.js. The analysis module uses generative AI models (such as OpenAI GPT-3 and BERT) to extract key points from the user's work history and generate a profile.

[1439] 3. Auto-generate resumes

[1440] The server automatically fills in the resume template based on the profile information generated through the analysis, which is then converted into appropriate text based on the user's skills and success stories.

[1441] 4. Recommendations for suitable jobs and companies

[1442] The server compares the generated profile information with a job database and recommends suitable jobs and companies. The recommended job information is sent to the user's smartphone and can be viewed on the application.

[1443] 5. Interactive career advice

[1444] Within the application, users can engage in real-time interactions with a virtual advisor, who uses generative AI models to answer their questions and provide customized career advice.

[1445] 6. Presenting success stories

[1446] The server retrieves successful job-changing cases from the database and presents them to the user. This information serves as inspiration and reference material for the user's job-changing activities.

[1447] Examples and prompts

[1448] As a concrete example, consider a user who has experience as a project manager and is looking for a new career step. The user enters their work history into the application, which automatically generates a resume. The application then recommends suitable job listings and provides specific interview preparation advice from a virtual advisor.

[1449] Examples of prompts include:

[1450] "Auto-generate a resume for a project manager based on the user's work history."

[1451] "Recommend the best job openings for users with the following work experience."

[1452] This will enable job seekers to proceed with their job search efficiently and effectively.

[1453] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1454] Step 1:

[1455] A user launches the application on their smartphone and enters their personal information, work history, skills, and interests, which are then formatted into an appropriate data format, such as JSON, and sent to the server.

[1456] Step 2:

[1457] The server stores the received user information in AWS DynamoDB. It checks whether the received data is in the correct format and starts the storage process. If successful, the server generates a status indicating that the data has been saved and sends a trigger to proceed to the next step.

[1458] Step 3:

[1459] The server analyzes the stored data and uses generative AI models (OpenAI GPT-3 and BERT) to extract key points from the user's work history. Specifically, it takes the text data of the work history as input and uses natural language processing technology to extract key skill sets and roles.

[1460] Step 4:

[1461] A resume template is automatically generated based on the profile information generated by the analysis. The server acquires the profile information, embeds the relevant information in a pre-prepared resume template, and automatically generates a resume. The generated resume is displayed to the user as a preview.

[1462] Step 5:

[1463] The server compares the profile information with a job database and recommends the most suitable jobs and companies. The comparison is performed using a matching algorithm to extract the most suitable job listings. The results of the comparison are sent to the user's smartphone and can be viewed on the application.

[1464] Step 6:

[1465] Within the application, users initiate real-time interactions with a virtual advisor, who uses generative AI models to quickly answer their questions and provide customized career advice. The conversation is sent to a server in real time for analysis.

[1466] Step 7:

[1467] The server retrieves successful job-changing cases from the database and presents them to the user. The successful cases are compared with the user's profile information, and the most relevant ones are selected and displayed. This allows the server to provide useful information for the user's job-changing activities.

[1468] 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.

[1469] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[1470] System configuration

[1471] The system includes the following main elements:

[1472] 1. User terminal: Accepts user input and sends information to the server.

[1473] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[1474] 3. Database: Stores job listings, success stories, and profile information.

[1475] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[1476] Program processing

[1477] Enter and submit user information

[1478] A user enters their profile information, work history, skills, and interests into an input form on the device. The device formats this information and sends it to the server. For example, a user enters their name, age, location, past work history, skills, and current areas of interest.

[1479] Data Analysis and Profiling

[1480] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of entry and reflects this in the profile. For example, if the emotion engine detects the user's enthusiasm when entering their work history, that information will also be included in the profile.

[1481] Resume auto-generation

[1482] The server fills in a resume template based on the generated profile information. It uses a sentence generation algorithm to automatically generate compelling resume content. It uses data from the emotion engine to generate content that highlights the user's interests and passions. For example, it converts success stories and specific skill sets as a project manager into compelling sentences to automatically generate a resume.

[1483] Recommendations for suitable jobs and companies

[1484] The server compares the profile with a job database and lists the most suitable jobs and companies. It also takes into account data from the emotion engine and prioritizes job recommendations based on the user's particular interest and enthusiasm. For example, a user with a data scientist skill set will be recommended job openings at AI companies or companies specializing in data analysis.

[1485] Interview preparation support

[1486] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions interactively to the user. The device transmits the user's answers to the server in real time. The server analyzes the responses and uses emotional data from the emotion engine to generate the next question and feedback. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[1487] Presentation of success stories

[1488] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users. For example, job-seekers can read about successful job-change cases in the same industry and use them as reference.

[1489] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1490] The processing flow will be explained below.

[1491] Step 1:

[1492] Users log into the system and enter their profile information, work history, skills, and interests into an input form on their terminal.

[1493] Step 2:

[1494] The terminal formats the information entered by the user and transmits it to the server using a secure protocol.

[1495] Step 3:

[1496] The server stores the received user information in a database. This data storage process is necessary to use the user information for subsequent analysis.

[1497] Step 4:

[1498] The server starts the data analysis module to analyze the user's work history, skills, and interests in detail. Specifically, it extracts key points from the work history and categorizes the skills and interests.

[1499] Step 5:

[1500] The server uses an emotion engine to analyze the user's emotional state as they type. For example, when a user enters their work history, it can identify emotions such as excitement, interest, or anxiety based on the speed of their keystrokes, the content of their input, their facial expressions, and their tone of voice.

[1501] Step 6:

[1502] The server then generates a profile based on the analysis results and emotional data, which takes into account the user's emotional state as well as their past successes and key skill sets.

[1503] Step 7:

[1504] The server then fills in a resume template based on the generated profile, and uses a text generation algorithm to automatically generate compelling resume text designed to appeal to recruiters and incorporating data from the sentiment engine.

[1505] Step 8:

[1506] The server sends the generated resume to the terminal and presents it to the user, who can then review it and make any necessary corrections.

[1507] Step 9:

[1508] The server compares the job market database to create a list of jobs and companies that best fit the profile. This matching process selects the most suitable job listings based on the user's skill set and past work experience. It also takes into account emotional data and prioritizes job listings and companies that the user has shown interest in.

[1509] Step 10:

[1510] The server sends the job listings to the terminal and presents them to the user, who then checks the information and considers whether to apply.

[1511] Step 11:

[1512] The user starts an interview practice session from a terminal. The terminal acts as a virtual interviewer and asks questions interactively to the user. The emotion engine analyzes the user's emotions in real time as they answer and sends the results to the server.

[1513] Step 12:

[1514] The server analyzes the user's responses and emotional data to generate the next question or feedback. For example, if it detects that the user is nervous, it will provide advice to ease the tension. If a positive emotion is detected, it will generate a question that will bring out that emotion.

[1515] Step 13:

[1516] The server generates the next question and feedback based on the analysis results and emotion data, and sends them to the device. The user receives the feedback and prepares for the next question.

[1517] Step 14:

[1518] The server retrieves interviews and stories of successful job-changers from a database and sends them to the device to motivate users. Using data from the emotion engine, it selects success stories that are likely to interest users.

[1519] Through these processing steps, the system helps job seekers make optimal career choices and guides them to a successful job search. The combination of an emotion engine enables more personalized advice and support that takes into account the user's emotions.

[1520] Example 2

[1521] 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."

[1522] Conventional job change support systems have difficulty in providing adequate personalized advice and support because they are unable to consider the emotions of job seekers. Furthermore, when structuring and analyzing input information and matching resumes with job offers, the systems are unable to reflect the user's enthusiasm and interests, making it difficult to recommend the most suitable jobs and companies.

[1523] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting personal information, work history, skills, and interests from a job seeker; means for structuring the input information and transmitting it to the server; means for analyzing the input information and generating a profile of the job seeker; means for analyzing the job seeker's emotions from the input information using an emotion engine; means for generating a profile using the analysis results and emotion data; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers for interview practice and providing feedback; and means for acquiring and presenting success stories to the job seeker. This enables personalized job change support that takes emotions into consideration and makes it possible to recommend optimal jobs and companies that reflect the user's enthusiasm and interests.

[1524] A "job seeker" refers to an individual who wishes to leave their current workplace and move to a new one.

[1525] "Personal information" refers to information that can identify an individual, such as name, age, or address.

[1526] "Work history" refers to work history information such as past job content, position, and employment period.

[1527] "Skills" refer to the abilities and techniques required for a particular job or occupation.

[1528] "Interest" refers to the degree of concern or involvement in a particular area or field.

[1529] "Terminal" refers to a device or equipment through which a user inputs information.

[1530] "Server" refers to a computer system that receives input data and analyzes and processes it.

[1531] "Structuring" refers to organizing input data into a certain format so that it can be stored in a database.

[1532] "Analysis" refers to the detailed analysis of input data and the extraction of useful information.

[1533] "Profile" refers to a detailed profile of an individual created based on analyzed data and information.

[1534] An "emotion engine" refers to a software module that analyzes and extracts emotional data from user input and behavior.

[1535] "Emotion Data" refers to information about a user's emotional state analyzed by an emotion engine.

[1536] "Automatic resume generation" refers to the process of automatically creating an attractive and relevant resume based on generated profile information.

[1537] "Job Database" refers to a database in which job information is stored.

[1538] "Recommendation" refers to presenting the most suitable job types and companies to the user.

[1539] "Practice interview" refers to the process by which a user prepares by answering questions in a virtual interview environment.

[1540] "Feedback" refers to advice or confirmation provided in response to a user's actions or responses.

[1541] "Success stories" refer to the experiences and interviews of people who have successfully changed jobs in the past.

[1542] This invention is a system that combines a platform that utilizes generative AI to provide job seekers with customized career advice and job information, with an emotion engine that recognizes user emotions.The system recommends the most suitable jobs and companies based on the job seeker's skills, experience, interests, and emotions, providing comprehensive support for the entire job search process.

[1543] System configuration

[1544] The system includes the following main elements:

[1545] 1. User terminal: Accepts user input and sends information to the server.

[1546] 2. Server: Analyzes user information and performs profile generation, automatic resume generation, job recommendations, interview practice, presentation of success stories, and emotion recognition.

[1547] 3. Database: Stores job listings, success stories, and profile information.

[1548] 4. Emotion engine: Analyzes the emotions in the user's input and responses and provides that information to the server.

[1549] Enter and submit user information

[1550] Users enter their profile information, work history, skills, and interests into an input form on their device. Specific input information includes name, age, location, past work history, skills, and current areas of interest. For example, users might enter the following: "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, interested in data science."

[1551] The device formats this input information and sends it to the server using an HTTP request, using a format such as JSON.

[1552] Data Analysis and Profiling

[1553] The server stores the received user information in a database and launches an analysis module, which extracts key points from the user's work history and categorizes their skills and interests. For example, the job title "software engineer" might be tagged with information like "interest in data science."

[1554] Emotion recognition

[1555] The server starts the emotion engine and analyzes the input data received from the user. The input content is used to analyze the user's emotional state, and the results are reflected in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile.

[1556] Generate a profile

[1557] The server uses the analysis results and emotional data to generate a user profile. The profile consists of skill sets, experience, interests, and emotional information. A specific example might be "Taro Yamada, 30 years old, with five years of engineering experience and a strong interest and enthusiasm for data science."

[1558] Auto-generate resumes

[1559] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it generates a sentence such as, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadline."

[1560] Recommendations for suitable jobs and companies

[1561] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[1562] Interview preparation support

[1563] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[1564] Presentation of success stories

[1565] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[1566] Through the above process, this system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1567] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1568] Step 1: Enter your user information

[1569] Users enter their profile information, work history, skills, and interests into an input form on their device. Input information includes name, age, location, past work history, skills, and current areas of interest. For example, they might enter "Taro Yamada, 30 years old, Tokyo, 5 years of work experience as a software engineer, proficient in Python and Java, and interested in data science." The input data is then structured and ready for the next step.

[1570] Step 2: Submit user information

[1571] The terminal structures the information entered by the user and sends it to the server using an HTTP request. Specifically, the data to be sent is expressed in JSON format or similar and formatted so that it can be analyzed on the server side. The input data is then sent to the next analysis step.

[1572] Step 3: Analyze user information

[1573] The server stores the received user information in a database and launches an analysis module. The analysis module extracts key points from the user's work history and categorizes their skills and interests. For example, it tags the job title "software engineer" with information such as "interest in data science." The analyzed data is then formatted into a user profile.

[1574] Step 4: Recognize emotions

[1575] The server starts the emotion engine and analyzes the input data received from the user. It analyzes the user's emotional state from the input content and reflects the results in the profile. For example, if emotions such as "excitement" or "enthusiasm" are found in the input data, that information is also included in the profile. The emotional data obtained in this step is used in the next step.

[1576] Step 5: Generate a profile

[1577] The server uses the analysis results and emotion data to generate a user profile. The profile consists of skill sets, experiences, interests, and emotion information. For example, it may contain information such as "Taro Yamada, 30 years old, 5 years of engineering experience, high interest and enthusiasm for data science." The generated profile is used in the next step.

[1578] Step 6: Auto-generate your resume

[1579] The server then fills in a resume template based on the generated profile information. Using a generative AI model, it automatically generates an attractive resume that highlights the user's skills and experience. For example, it might generate a sentence like, "Taro Yamada has demonstrated leadership in many projects and successfully completed them within the deadlines." The generated resume is then provided to the user.

[1580] Step 7: Recommend suitable jobs and companies

[1581] The server compares the generated profile with a job database and lists the most suitable jobs and companies. It also takes into account the user's interests and passions obtained from the emotion engine to recommend the most suitable job for the user. For example, it may present job information in the form of "Taro Yamada, who has data science skills, is recommended for a position at an AI company."

[1582] Step 8: Interview preparation assistance

[1583] The user initiates an interview practice session from their device. The device acts as a virtual interviewer, asking questions and transmitting the user's answers in real time to the server. The server analyzes the responses and generates the next question and feedback, using emotional data from the emotion engine. For example, feedback such as "Yamada-san, please relax a bit and answer again" may be provided.

[1584] Step 9: Present success stories

[1585] The server retrieves interview articles and stories of successful job-changers from the database and sends them to the device. Using data from the emotion engine, it selects success stories that are likely to interest the user. For example, it might present an interview article about someone who, like Yamada, successfully changed jobs in the field of data science. Please read it.

[1586] Through these steps, the system helps job seekers make optimal career choices and guides them to a successful job search. By combining it with an emotion engine, it is possible to provide more personalized advice and support that takes into account the user's emotions.

[1587] (Application example 2)

[1588] 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."

[1589] Conventional job change support systems provided job information without considering the feelings of job seekers, resulting in a limited user experience and a lack of feedback and advice that reflected individual needs and feelings. They also lacked a mechanism for providing appropriate career advice and job recommendations specifically tailored to factory workers. This made it difficult for workers to effectively utilize their skills and find new career paths.

[1590] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1591] In this invention, the server includes: means for inputting the job seeker's personal information, work history, skills, and interests; means for analyzing the input information and generating a profile; means for automatically generating a resume based on the generated profile; means for comparing the generated profile with a job database and recommending optimal jobs and companies; means for analyzing questions and answers and providing feedback for interview practice; means for acquiring success stories and presenting them to the job seeker; means for analyzing emotions and adjusting feedback and recommendations based on the job seeker's emotional state; and means for being installed in a robot and providing career advice to factory workers. This enables job seekers to receive job information and career advice tailored to their emotions and needs, making it possible to provide optimal career support, particularly for factory workers.

[1592] A "job seeker" is an individual who intends to leave their current job and take up a new one.

[1593] "Personal information" refers to information that identifies a specific individual, such as the job seeker's name, age, address, and contact information.

[1594] "Work history" refers to information about the type of work a job seeker has done in the past, the duration of that work, and the nature of the work.

[1595] "Skills" refers to the specialized knowledge, techniques, and abilities that job seekers possess.

[1596] "Interests" refers to information about the fields, industries, and job types that job seekers are interested in.

[1597] "Analysis" refers to the use of computer technology to analyze input information and extract its meaning and patterns.

[1598] A "profile" is a comprehensive data set generated based on a job seeker's personal information, work history, skills, interests, etc.

[1599] A resume is a document that lists the work history, skills, and qualifications of a job seeker.

[1600] A "job database" is a database that stores multiple job listings.

[1601] "Matching" is the process of comparing the generated profile with job information in the job database to find the best match.

[1602] "Recommendation" means suggesting suitable jobs and companies to job seekers based on the results of the comparison.

[1603] "Practice interviews" are mock question and answer sessions in preparation for the actual interview.

[1604] "Feedback" refers to evaluations and advice provided to job seekers during practice interviews, etc.

[1605] "Success stories" are the experiences and stories of other job seekers who have been successful in their job search, and are provided as reference information.

[1606] "Analyzing emotions" means measuring the emotional state of job seekers and analyzing the data based on that state.

[1607] A "robot" is a mechanical device that operates automatically and has the function of performing specific tasks at a factory or other work site.

[1608] This invention is a platform that utilizes generative AI to provide job seekers with customized career advice and job information, and is a system that combines an emotion engine. The system inputs the job seeker's personal information, work history, skills, and interests, analyzes this information, and generates a profile. It then automatically generates a resume based on the profile and compares it with a job database to recommend the most suitable jobs and companies. It also analyzes questions and answers for interview practice, providing real-time feedback, and presents success stories.

[1609] The system includes the following main elements:

[1610] 1. User Device:

[1611] It is a means for users to enter personal information, work experience, skills, and interests, which is then formatted and sent to a server. Examples include devices such as smartphones, PCs, and tablets.

[1612] 2. Server:

[1613] The server is responsible for centralizing and analyzing data. It analyzes the data received from users and generates a profile. Emotional data analyzed by the emotion engine is also reflected in the profile. Based on the generated profile, a resume is automatically generated and compared with a job database to recommend the most suitable job type and company. It also provides real-time feedback during interview practice and presents success stories.

[1614] 3. Database:

[1615] It includes a database for storing history information, job listings, and success stories. The server communicates with the database to retrieve and store the required information.

[1616] 4. Emotion Engine:

[1617] Analyzes the emotions of users when they input or respond. For example, analyzes the user's emotional state when they input and reflects the results in their profile. The emotion engine adjusts advice and feedback based on the user's emotions.

[1618] 5. Applications installed on the robot:

[1619] The application is installed on a robot to provide career advice to factory workers. It recommends suitable jobs and positions based on the worker's skills and experience. It also uses an emotion engine to recognize the worker's emotional state and provide appropriate feedback and advice in real time.

[1620] As a concrete example, consider the following prompt text entered by a user on a smartphone or tablet:

[1621] Example prompt sentence:

[1622] "I have been working on an automobile production line for five years. I am particularly good at operating and maintaining robots. I am interested in learning new skills and am also studying automation using AI. Please let me know if there are any job openings."

[1623] The system analyzes this input information, generates a profile, and automatically generates a resume. It also compares it with a job database to recommend the most suitable jobs and companies, and conducts interview practice sessions. It also presents success stories to motivate users. The emotion engine detects the user's emotions when they enter information and adjusts the feedback and advice provided based on that information.

[1624] By linking with the emotion engine and database, the server can provide more personalized career advice, allowing job seekers to receive the most appropriate job information and career support tailored to their needs and emotions. Similar support can also be provided to factory workers.

[1625] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1626] Step 1:

[1627] The user enters the job seeker's personal information, work experience, skills, and interests. For example, the user enters information using prompts on a smartphone or tablet. The entered information is formatted by the device and sent to the server. The entered data may include, for example, name, age, address, past work experience, skills, and areas of interest.

[1628] input:

[1629] Personal information (name, age, address)

[1630] Work history (past job content, period)

[1631] Skills (specialized knowledge, techniques)

[1632] Areas of Interest

[1633] output:

[1634] Formatted data sent to the server

[1635] Step 2:

[1636] The server analyzes the received user information and generates a profile. The analysis module extracts key points from the user's work history and categorizes their skills and interests. It also uses an emotion engine to analyze the user's emotional state at the time of input and reflects that data in the profile.

[1637] input:

[1638] User information (personal information, work history, skills, areas of interest)

[1639] Emotional data (emotional state at the time of input)

[1640] output:

[1641] Generated User Profile

[1642] Step 3:

[1643] The server automatically generates a resume based on the generated profile. It embeds the profile data into a resume template and uses a text generation algorithm to create an appealing resume. It also uses emotional data to generate content that emphasizes the user's interests and passions.

[1644] input:

[1645] Generated User Profile

[1646] Emotional Data

[1647] output:

[1648] Auto-generated resume

[1649] Step 4:

[1650] The server compares the created profile with a job database and recommends the most suitable jobs and companies. It also takes into account emotional data and prioritizes jobs that the user has shown particular interest or enthusiasm for.

[1651] input:

[1652] Generated User Profile

[1653] Job Database

[1654] output:

[1655] List of recommended jobs and companies

[1656] Step 5:

[1657] The user initiates an interview practice session from a terminal, which acts as a virtual interviewer and asks questions interactively to the user, whose answers are sent to the server in real time.

[1658] input:

[1659] User interview answers

[1660] output:

[1661] Submitted response data

[1662] Step 6:

[1663] The server analyzes the user's interview responses and generates the next question and feedback using the emotion data from the emotion engine. For example, if the user feels anxious or nervous, the server provides feedback such as "Relax and think again."

[1664] input:

[1665] Interview response data

[1666] Emotional Data

[1667] output:

[1668] Next Questions and Feedback

[1669] Step 7:

[1670] The server retrieves success stories from the database and presents them to the user. Based on the data from the emotion engine, it selects success stories that are likely to interest the user.

[1671] input:

[1672] Emotional Data

[1673] Success story database

[1674] output:

[1675] Success stories presented

[1676] Step 8:

[1677] The application installed on the robot provides career advice to workers, recommending suitable tasks and jobs based on their skills and experience, and using an emotion engine to recognize the worker's emotional state and provide feedback and advice in real time.

[1678] input:

[1679] Worker skills, experience, and emotional data

[1680] output:

[1681] Career advice and feedback

[1682] 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.

[1683] 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.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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).

[1689] 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.

[1690] 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."

[1691] 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.

[1692] 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).

[1693] 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.

[1694] 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.

[1695] 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.

[1696] 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.

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] 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.

[1703] The following is further disclosed regarding the above embodiment.

[1704] (Claim 1)

[1705] A means for job seekers to enter personal information, work history, skills, and interests;

[1706] A means for analyzing the input information and generating a profile of the job seeker;

[1707] means for automatically generating a resume based on the generated profile;

[1708] A means of matching the generated profile with a job database and recommending the most suitable jobs and companies;

[1709] A means of analyzing question and answer responses and providing feedback for practice interviews;

[1710] A means to obtain success stories and present them to job seekers,

[1711] A system including:

[1712] (Claim 2)

[1713] 2. The system according to claim 1, wherein key points are extracted from the job seeker's past work history by the profile generation means.

[1714] (Claim 3)

[1715] 10. The system of claim 1, wherein the means for providing feedback for the interview practice analyzes questions and answers in real time and generates feedback for the next question and response.

[1716] "Example 1"

[1717] (Claim 1)

[1718] A means for job seekers to enter personal information, work history, skills, and interests;

[1719] A means for analyzing the input information and generating a profile of the job seeker;

[1720] means for automatically generating a resume based on the generated profile;

[1721] A means of matching the generated profile with a job database and recommending the most suitable jobs and companies;

[1722] A means of analyzing question and answer responses and providing feedback for practice interviews;

[1723] A means to obtain success stories and present them to job seekers,

[1724] A means for filling a template with information based on profile information generated using a generative AI model to automatically generate a resume;

[1725] a means for interacting with a virtual interviewer, transmitting answers to a server in real time, and generating next questions and feedback for the practice interview;

[1726] A means of extracting key points from users' work histories and categorizing their skills and interests using natural language processing techniques for data analysis and profiling;

[1727] A system including:

[1728] (Claim 2)

[1729] 2. The system according to claim 1, wherein key points are extracted from the job seeker's past work history by the profile generation means.

[1730] (Claim 3)

[1731] 10. The system of claim 1, wherein the means for providing feedback for the interview practice analyzes questions and answers in real time and generates feedback for the next question and response.

[1732] "Application Example 1"

[1733] (Claim 1)

[1734] A means for job seekers to enter personal information, work history, skills, and interests;

[1735] A means for analyzing the input information and generating a profile of the job seeker;

[1736] means for automatically generating a resume based on the generated profile;

[1737] A means of matching the generated profile with a job database and recommending the most suitable jobs and companies;

[1738] A means of analyzing question and answer responses and providing feedback for practice interviews;

[1739] A means to obtain success stories and present them to job seekers,

[1740] a means of providing interactive career advice through real-time interactions with virtual advisors;

[1741] A system including:

[1742] (Claim 2)

[1743] 2. The system according to claim 1, wherein key points are extracted from the job seeker's past work history by the profile generation means.

[1744] (Claim 3)

[1745] 10. The system of claim 1, wherein the means for providing feedback for the interview practice analyzes questions and answers in real time and generates feedback for the next question and response.

[1746] "Example 2: Combining Emotion Engines"

[1747] (Claim 1)

[1748] A means for job seekers to enter personal information, work history, skills, and interests;

[1749] means for structuring the input information and transmitting it to a server;

[1750] A means for analyzing the input information and generating a profile of the job seeker;

[1751] A means for analyzing the emotions of job seekers from input information using an emotion engine;

[1752] means for generating a profile using the analysis results and emotion data;

[1753] means for automatically generating a resume based on the generated profile;

[1754] A means of matching the generated profile with a job database and recommending the most suitable jobs and companies;

[1755] A means of analyzing question and answer responses and providing feedback for practice interviews;

[1756] A means to obtain success stories and present them to job seekers,

[1757] A system including:

[1758] (Claim 2)

[1759] 2. The system according to claim 1, wherein the profile generation means extracts key points from past work history, and the emotion engine analyzes the emotional state at the time of input and reflects the results in the profile.

[1760] (Claim 3)

[1761] 10. The system of claim 1, wherein the means for providing feedback for the practice interview analyzes the questions and answers in real time and also utilizes emotion data from the emotion engine to generate feedback for the next question and response.

[1762] "Application example 2 when combining emotion engines"

[1763] (Claim 1)

[1764] A means for job seekers to enter personal information, work history, skills, and interests;

[1765] A means for analyzing the input information and generating a profile of the job seeker;

[1766] means for automatically generating a resume based on the generated profile;

[1767] A means of matching the generated profile with a job database and recommending the most suitable jobs and companies;

[1768] A means of analyzing question and answer responses and providing feedback for practice interviews;

[1769] A means to obtain success stories and present them to job seekers,

[1770] A means of analyzing emotions and tailoring feedback and recommendations based on the job seeker's emotional state; and

[1771] A means to be installed on the robot and to provide career advice to workers working in the factory;

[1772] A system including:

[1773] (Claim 2)

[1774] 2. The system according to claim 1, wherein key points are extracted from the job seeker's past work history by the profile generation means.

[1775] (Claim 3)

[1776] 10. The system of claim 1, wherein the means for providing feedback for the interview practice analyzes questions and answers in real time and generates feedback for the next question and response. [Explanation of symbols]

[1777] 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 means for job seekers to enter personal information, work history, skills, and interests; A means for analyzing the input information and generating a profile of the job seeker; means for automatically generating a resume based on the generated profile; A means of matching the generated profile with a job database and recommending the most suitable jobs and companies; A means of analyzing question and answer responses and providing feedback for practice interviews; A means to obtain success stories and present them to job seekers, A system including:

2. 2. The system according to claim 1, wherein key points are extracted from the job applicant's past work history by the profile generation means.

3. 10. The system of claim 1, wherein the means for providing feedback for the interview practice analyzes questions and answers in real time and generates feedback for the next question and response.

Images