system

Abstract

We provide the system. [Solution] A means for receiving user input information and storing said information in a database, A means for analyzing the input information using natural language processing technology and evaluating the user's suitability, Based on the aforementioned evaluation results, a means for suggesting suitable occupations to the user, A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a society facing the problems of labor shortage due to the low birthrate and aging population and low labor productivity per person, it is an object to provide a system that can eliminate the mismatch between an individual's aptitude and desire. In particular, there is a need for means to effectively obtain information necessary to determine one's own aptitude in career selection and build an optimal career. At present, the means for an individual to access appropriate career information are limited, and the mechanism for efficiently connecting the employing company and the individual is insufficient.

Means for Solving the Problems

[0005] This invention provides a system that receives user input information and analyzes that information using natural language processing technology. This system has the function of evaluating the user's aptitude and suggesting suitable occupations. Furthermore, it obtains the recruitment status of the suggested occupations from external sources and provides this information to the user in real time. In addition, based on the user's approval, it discloses the user's information to companies and receives recruitment information, thereby facilitating matching between job seekers and companies. This system enables efficient matching between individuals and companies, resulting in appropriate personnel placement.

[0006] A "user" refers to an individual or group that utilizes the system and is the entity that provides information regarding occupational aptitude.

[0007] "Input information" refers to information provided by the user, including data such as name, work experience, areas of interest, skills, and desired job type.

[0008] A "database" refers to a digital system with a structure for storing and managing information obtained from users, occupational information obtained from external sources, success stories, and so on.

[0009] "Natural language processing" refers to the technology that enables computers to understand, interpret, and generate human language, and the processes used to analyze user input.

[0010] "Aptitude assessment" refers to the process of using natural language processing technology to analyze a user's characteristics, interests, skills, etc., and then determining which occupation is the most suitable based on that analysis.

[0011] "Job suggestion" refers to the act of providing a user with a list of specific occupations that are recommended as suitable based on the results of an aptitude assessment.

[0012] "External information sources" refer to data providers or platforms located outside the system that the system uses to acquire information such as job openings and recruitment status.

[0013] "Scout information" refers to information about job postings and recruitment offers sent from companies to users.

[0014] "Approval" refers to a user's expression of consent, allowing the system to disclose their information to a company. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the 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.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0029] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is an AI-powered interactive career aptitude system aimed at supporting users in making appropriate career choices. The system performs an aptitude assessment based on user input regarding their experience, skills, and interests. It then analyzes this information through natural language processing and presents suitable career options to the user.

[0037] First, users access the system using their device and register personal information, work experience, and areas of interest. This data is sent to the server in real time and stored in a database. Users then begin interacting with the AI ​​in voice or text format, and the AI ​​collects their input and guides the conversation to extract the necessary information.

[0038] The server uses natural language processing technology to analyze user input and perform an aptitude assessment. The analysis results undergo further review and data matching to generate a list of the most suitable occupations for the user. The presented list includes job types that match the user's interests and related success stories.

[0039] As a concrete example, if a recent graduate user inputs information into this system and selects environmental science as their area of ​​particular interest, the system will identify an appropriate occupational category based on that information. For instance, it might suggest a job as a climate change analyst, and simultaneously provide success stories of related career paths and advice on acquiring skills for further career advancement.

[0040] Furthermore, users can check the current recruitment status for jobs they are interested in. The server collaborates with external sources to retrieve the latest recruitment information and provides it to the user. In addition, with the user's permission, the user's profile information is made public to companies, and they await recruitment offers.

[0041] Thus, the present invention provides an effective means to effectively connect users and companies and reduce mismatches in career choices.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users access the system using their devices and register for an account. They enter basic information, work experience, and areas of interest, and the device sends this information to the server.

[0045] Step 2:

[0046] The server stores the received user information in a database. During this process, it performs basic checks to verify the completeness and accuracy of the information.

[0047] Step 3:

[0048] The user initiates an interactive assessment with the AI ​​using their device. The AI ​​utilizes natural language processing technology to generate questions based on the user's profile.

[0049] Step 4:

[0050] The user answers questions from the AI, providing detailed information about their interests and skills. The device sends these answers to the server in real time.

[0051] Step 5:

[0052] The server analyzes the user's responses and uses a machine learning algorithm to perform an aptitude assessment. The assessment results are temporarily stored in a database.

[0053] Step 6:

[0054] The server generates a list of suitable occupations for the user based on the aptitude assessment results. This list, along with past success stories and information on the skills required for each occupation, is sent to the terminal.

[0055] Step 7:

[0056] Users view a list of jobs presented via their device and check the details. If necessary, they are provided with options to check the job availability for those jobs.

[0057] Step 8:

[0058] The server retrieves relevant job postings from external sources and displays the results on the terminal. The user then uses this information to make a career choice decision.

[0059] Step 9:

[0060] If the user consents, their device will be configured to share their profile information with companies. The server manages this, allowing companies to send recruitment information.

[0061] Step 10:

[0062] The server receives the recruitment information and notifies the user. The user checks the offer details through their device and decides on their next course of action.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In today's labor market, a mismatch between individual aptitudes and market demand is common, making it difficult to choose the right job. This can lead to poor career decisions, resulting in decreased job satisfaction and stagnation in career development. This problem is particularly serious for new job seekers with limited experience and skills, highlighting the need for new technological approaches to address these challenges.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for receiving information from the user's terminal and storing the information in a storage device, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for presenting suitable occupations to the user based on the evaluation results using a generative AI model. This makes it possible to analyze the user's skills and interests in detail and support them in making the optimal career choice.

[0068] A "user" is an individual or legal entity that utilizes the system, inputs information, and receives vocational aptitude assessments and suggestions based on that input.

[0069] A "terminal" is an electronic device used by a user to input information or receive results, and primarily refers to computing devices such as computers and smartphones.

[0070] "Information" refers to data such as a user's personal profile, work experience, and areas of interest, which the system uses for analysis.

[0071] A "storage device" refers to a database or storage medium for permanently storing received information, and is a device that enables secure storage and rapid access to information.

[0072] "Natural language processing technology" refers to computational techniques for analyzing text data from users and understanding the meaning of language, and includes machine learning and text mining.

[0073] A "generative AI model" is a computational model that uses artificial intelligence technology to generate new data and suggestions, and plays a role in evaluating occupational suitability based on user input information.

[0074] "Assessing suitability" is the process of analyzing a user's abilities and interests and determining their suitability for a particular occupation based on that analysis.

[0075] "Means" refers to the technical elements or methods incorporated into a system to achieve a specific function.

[0076] "Occupation" refers to the specific tasks or positions recommended to the user as a result of the occupational aptitude assessment.

[0077] An "external information source" is a source for obtaining information from databases or servers located outside the system, and is used to retrieve job postings.

[0078] This invention is an interactive career aptitude system that provides support to users in selecting appropriate occupations. The system utilizes generative AI models and natural language processing technology to suggest optimal occupations to the user. The following describes its specific embodiments.

[0079] Users access the system using a device, such as a computer or smartphone. Users log in or register and enter their personal information, work experience, and areas of interest. This data is transmitted to the server via the device. The HTTPS protocol is used for secure communication over the internet.

[0080] The server stores the received data in a database, which serves as a storage device. This database can be a common relational database system, such as MySQL® or PostgreSQL. Subsequently, the server uses natural language processing (NLP) techniques to analyze the user's input and evaluate the user's suitability. Specific NLP libraries used include spaCy and Google® Cloud Natural Language API.

[0081] The server uses an AI model based on the analysis results to generate a list of suitable occupations for the user. This model matches past occupational data with the user's profile and suggests occupations based on the user's interests and skills. The suggested occupations include job descriptions and success stories related to the user's interests.

[0082] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the proposed occupation. This utilizes external job posting APIs, such as those provided by job posting platforms. The proposed occupation and the latest job postings are then presented to the user via their device.

[0083] As a concrete example, suppose a recent graduate accesses this system and enters their area of ​​interest, "environmental science." In this case, the system suggests professions such as climate change analyst or environmental consultant, and also provides advice on related success stories and necessary skills.

[0084] An example of a prompt message could be, "I'm a recent graduate and I'm interested in environmental science. What kind of job would suit me?" In this way, the system effectively supports the user in their career selection.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] Users access the system using a terminal and enter their personal information, work experience, and areas of interest. The data is submitted by pressing a submit button through the user interface. Basic format checks are performed to ensure the information is in the correct format for transmission to the server. The output is user data in the correct format.

[0088] Step 2:

[0089] The server receives user data sent from the terminal and stores it in a storage device (database). During this process, the data is inserted into the database using SQL statements and stored securely. The input is user data, and the output is a confirmation that the data has been successfully saved to the database.

[0090] Step 3:

[0091] The server retrieves stored user information and begins analysis using natural language processing techniques. Specifically, it tokenizes text data obtained from the database, extracts keywords, and classifies the content. Here, the input information is the user's raw data, and a user profile is generated as output.

[0092] Step 4:

[0093] The server uses a generative AI model to evaluate occupational suitability based on the user profile obtained through analysis. The generative AI model has learned from past data patterns and has the ability to suggest the most suitable occupational category for the user's interests and skills. Profile data is used as input, and a list of suitable occupations for the user is generated as output.

[0094] Step 5:

[0095] The server accesses external information sources and retrieves the latest job postings corresponding to the generated occupation list. It queries various external job databases via API and filters the relevant job postings. The input is an occupation list, and the output is a collection of the latest job postings.

[0096] Step 6:

[0097] The server sends the generated job list and the latest job postings back to the terminal and displays them to the user. The user can view detailed information and job availability for recommended jobs through the terminal screen. The input is data from the server, and the output is the information displayed on the user interface.

[0098] Step 7:

[0099] Based on the suggested job information, the user decides whether to make their profile public to companies. If they choose to make it public, the server updates the user's settings, enabling them to receive recruitment offers from companies. The input is the user's selection, and the output is an update to the profile's public status.

[0100] (Application Example 1)

[0101] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0102] In modern society, with the increasing diversity and complexity of career choices, it is difficult for individual users to find a suitable job. Furthermore, challenges include a lack of appropriate career paths, insufficient information on skill acquisition, and poor matching between career options and actual workplaces. There is also a need for increased efficiency in face-to-face counseling at physical locations.

[0103] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0104] This invention includes a server that provides means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's aptitude, means for suggesting suitable occupations based on the evaluation results and providing relevant career paths and skill acquisition information, means for providing a function that allows visitors to receive vocational aptitude tests using terminals installed in stores, and means for obtaining the recruitment status of suitable occupations from external information sources. As a result, users can discover the occupation that is most suitable for them and obtain specific career plans and skill improvement measures for that occupation. Furthermore, effective career selection support is realized through dialogue with advisors at physical stores.

[0105] A "user" refers to an individual who uses the system to undergo a career aptitude assessment.

[0106] "Input information" refers to information provided by the user, including data on their work experience, interests, skills, etc.

[0107] A "database" is an information management system that stores user input information and allows it to be referenced and updated as needed.

[0108] "Natural language processing technology" is a technology that enables computers to understand and interpret human language, and is used to analyze user input and evaluate aptitude.

[0109] "Occupational aptitude assessment" is an analytical process that identifies the most suitable occupation based on a user's skills and interests.

[0110] A "career path" is a systematically planned route outlining the stages of progression in a particular profession.

[0111] "Skill acquisition information" refers to information that provides users with specific guidelines and advice for acquiring the skills necessary for a particular occupation.

[0112] A "store-installed terminal" is an electronic device installed in a physical store that users can use to take a career aptitude test.

[0113] "External information sources" refer to information providers or platforms outside the system that are linked to provide current job openings.

[0114] To realize this invention, the server first receives user input information and stores it in a database in an appropriate format. The server then uses natural language processing technology to analyze the user's input and evaluates their vocational aptitude based on that analysis. For this purpose, natural language processing APIs such as the Google Cloud Natural Language API may be used.

[0115] Terminals installed in physical stores provide users with a means to take a career aptitude test. Users access the terminal and input information via voice or text. The terminal transmits this data to a server in real time and displays a list of the most suitable occupations for the user. The list also includes relevant career path and skills acquisition information.

[0116] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the listed occupations and provides them to users through their terminals. This allows users to obtain real-time job information for occupations they are interested in.

[0117] As a concrete example, consider a user who majored in environmental science at university. The user enters "I am interested in a career related to the environment" into the terminal. The program, as a result of its analysis, suggests the career of "climate change analyst" and provides information on related career paths and future skill acquisition.

[0118] As an example of a prompt, a user might input, "I want to work in the field of data science after graduating from university. What kind of job would suit me?" In response to this input, appropriate job suggestions and related information would be provided.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The user accesses their device and launches a career aptitude assessment application. The user inputs information about their work experience, interests, and skills in text or voice format. The input data is transmitted from the device to the server in real time. The input data format is standardized and converted into a format easily processed by the server.

[0122] Step 2:

[0123] The server stores the received input information in a database. This process verifies the accuracy and completeness of the input information and checks for any missing information. After verification, the information is stored in the database according to the data model.

[0124] Step 3:

[0125] The server analyzes the stored data using natural language processing technology. Specifically, it uses the Google Cloud Natural Language API to extract keywords related to the user's interests and skills and identify potential related occupations. Through this analysis, an assessment of the user's suitability for different occupations is performed.

[0126] Step 4:

[0127] The server generates a list of suitable occupations for the user based on the analysis results. The generated list includes career paths and skill acquisition information related to each occupation. The list is constructed by retrieving information from a database.

[0128] Step 5:

[0129] The generated list of occupations is provided to the user via the device. The information is displayed in the format specified by the user (text or audio). The user can browse this list and view detailed information about occupations that interest them.

[0130] Step 6:

[0131] The server interacts with external information sources to obtain the latest job postings. It queries external information sources to retrieve the latest job information and temporarily stores it in the database.

[0132] Step 7:

[0133] The device displays the latest job postings to the user. Based on the information presented, the user can check the application status of jobs they are interested in and decide on further actions.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention combines an AI-powered interactive career aptitude system with an emotion engine. Users access the system using a terminal and provide information about their career aptitude. This information includes basic profile data as well as skills and interests.

[0136] The system is hosted on a server and analyzes user input using an emotion engine. The emotion engine analyzes the user's input data and recognizes the user's emotional state. Based on this, it adjusts the dialogue appropriately in response to user feedback and corrects the aptitude evaluation results.

[0137] For example, if a user is feeling anxious about future career choices, the emotion engine detects this anxiety, and the server responds by providing reassuring career suggestions and more detailed success stories. This interaction is designed to allow users to use the system in a more relaxed manner.

[0138] Furthermore, the server evaluates the user's aptitude and, taking into account their emotional state, generates a list of suitable occupations. This list, along with relevant job postings, is presented to the user's device. Additionally, an emotion engine monitors how the user reacts to the aptitude assessment and job suggestions, dynamically optimizing the evaluation process and user experience through feedback.

[0139] Finally, with the user's consent, the system makes their profile public to companies and allows them to receive recruitment information in real time. This enables users to quickly access suitable occupations through the system. The integration of these functions significantly improves the user experience in career selection and optimizes matching with companies.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user logs into the system using their device. After logging in, a screen appears where the user can enter profile information, work experience, and areas of interest, and the user enters the required information.

[0143] Step 2:

[0144] The terminal sends the input information to the server, which then stores that information in a database. Simultaneously, the stored information is sent to the emotion engine to begin analysis.

[0145] Step 3:

[0146] The emotion engine analyzes user input data and uses natural language processing to recognize the user's emotional state. This emotional state data is then used in the evaluation process.

[0147] Step 4:

[0148] The server uses the analysis results from the emotion engine to execute a process to evaluate the user's suitability and generate an suitability score. Considering emotional data allows for a more accurate evaluation.

[0149] Step 5:

[0150] The server generates a list of suitable occupations for the user based on the aptitude assessment results. It adjusts the suggestion method and content according to the user's emotional state, providing reassuring occupational suggestions.

[0151] Step 6:

[0152] Users can view a list of jobs presented on their device and see related job postings and success stories. They can also request further information based on their interests.

[0153] Step 7:

[0154] The emotion engine monitors in real time how users react to career suggestions and information displays, and provides feedback via the device to help improve the user experience.

[0155] Step 8:

[0156] If a user is interested in a particular occupation, they should configure their device to allow receiving recruitment offers from companies related to that occupation.

[0157] Step 9:

[0158] The server verifies the settings and, based on the user's consent, publishes profile information to companies. It receives recruitment information from companies and immediately notifies the user via their device.

[0159] Step 10:

[0160] Users can check recruitment information via their devices and plan their next career steps. This allows users to continue receiving support for optimal career choices through the system.

[0161] (Example 2)

[0162] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0163] Modern vocational aptitude assessment systems require not only evaluations based on the user's skills and experience, but also more sophisticated career suggestions that take into account the user's emotional state. However, conventional systems have the problem of not being able to accurately grasp the user's emotions and dynamically adjust the content of the dialogue and career suggestions accordingly. Therefore, there is a need for a means to provide users with the most suitable career choices.

[0164] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0165] In this invention, the server includes means for receiving user input information and storing it in data storage; means for determining the user's emotional state using an emotion analysis model with natural language processing technology; means for analyzing the input information and emotional state and evaluating the user's suitability; and means for generating job suggestions that correspond to the user's emotions using a generative AI model and presenting suitable jobs to the user based on the evaluation results. This makes it possible to optimize job suggestions and evaluation processes that take the user's emotions into consideration.

[0166] "User input information" refers to basic profile data, skills, and interests provided by users accessing the system.

[0167] "Natural language processing technology" is a technology that enables computers to understand, analyze, and respond to human language, and is also used for analyzing emotional states.

[0168] An "emotion analysis model" is an algorithm or machine learning-based analysis method that recognizes and classifies emotional states from user input information.

[0169] A "generative AI model" is a model that utilizes artificial intelligence to generate appropriate career suggestions based on the user's emotional state.

[0170] "Data storage" refers to a system component used to store user input information and analysis results.

[0171] "Evaluation results" are the outcomes derived by the aptitude evaluation system based on the user's input information and emotional state, and form the basis of career suggestions.

[0172] "Career suggestion" is a process that presents users with career options deemed most suitable based on their aptitude assessment results.

[0173] "Scout information" refers to data about employment opportunities and recruitment information that companies send to users.

[0174] This invention is an interactive vocational aptitude assessment system that combines natural language processing technology and an emotion analysis model to recognize the user's emotional state and provide optimal vocational suggestions. Specific embodiments are described below.

[0175] Users access the system using a device and input their profile information, skills, and interests. The device collects this information and transmits it to the server via a secure communication protocol. The server stores the input information in data storage and transfers it to a sentiment analysis model using natural language processing technology.

[0176] Emotion analysis models process input information to determine the user's emotional state. High-precision algorithms and machine learning models are used for this analysis. The resulting emotional state is then used as important data to further evaluate the user's suitability.

[0177] The server uses a generative AI model to generate career suggestions that are tailored to the user's emotions. This process involves creating messages that are sensitive to the user's feelings, designed to reduce stress. The generated career suggestions are aligned with the user's skills and interests.

[0178] The generated list of occupations is presented to the user via the terminal, and the user's response is monitored. The server uses this feedback to dynamically optimize the dialogue and evaluation process.

[0179] For example, if a user inputs "I'm interested in programming but I'm not confident," the sentiment analysis model will detect anxiety, and the generative AI model will suggest programming jobs and learning resources suitable for beginners.

[0180] Example prompt: "If a user inputs that they are interested in programming but lack confidence, explain how to generate appropriate career suggestions while providing reassurance."

[0181] Thus, the present invention provides a system that offers vocational aptitude assessment that takes into account the user's emotional state, thereby improving the user experience and increasing the accuracy of matching with companies.

[0182] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0183] Step 1:

[0184] Users access the vocational aptitude assessment system using their devices and enter their profile information, skills, and interests. This input is done through forms, and the collected data is sent to the server using a secure communication protocol. Specific examples of input include age, work experience, and areas of interest (e.g., data science, graphic design).

[0185] Step 2:

[0186] The server stores the received user input information in data storage. At this stage, the data entered is uniquely managed for each user. The stored data is used as foundational data for subsequent analysis processes.

[0187] Step 3:

[0188] The server uses natural language processing technology to pass stored user input information to an emotion analysis model. Here, the text data is analyzed, and the user's emotional state is determined. This analysis uses machine learning algorithms, for example, to extract emotional states based on emotional keywords such as "anxiety" and "excitement" contained in the input text. The output is the analyzed emotional state data.

[0189] Step 4:

[0190] The server generates job suggestions using a generative AI model based on the emotional state obtained through emotion analysis, as well as the user's skills and interests. This process creates job suggestions optimized for the user according to their emotional state. For example, if the user is identified as "anxious," job suggestions that provide a sense of security will be proposed. A list of suggested jobs is generated as output.

[0191] Step 5:

[0192] The server sends the generated list of occupations to the terminal and presents it to the user. The terminal displays the list of occupations to the user in an easy-to-understand interface. The user can refer to the presented list of occupations and consider them in light of their own interests and aptitudes.

[0193] Step 6:

[0194] The device records how the user reacts to the presented list of occupations and sends this feedback to the server. Based on this feedback data, the server dynamically optimizes the parameters of the generative AI model and the sentiment analysis model to improve the accuracy of future suggestions.

[0195] Step 7:

[0196] With the user's consent, the server makes the user's profile information public to relevant companies and prepares to receive recruitment information from companies in real time. This information is notified to the device, allowing the user to quickly understand the expected job opportunities.

[0197] (Application Example 2)

[0198] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0199] Traditional career aptitude systems have the problem of providing a uniform and inadequately optimized user experience because they do not take into account the user's emotional state. Furthermore, when users experience emotional anxiety regarding career choices, there is a lack of means to alleviate that anxiety and support them in making informed choices with greater confidence.

[0200] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0201] In this invention, the server includes means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for analyzing the user's emotional state and adjusting the interaction according to that state. This makes it possible to provide optimal job suggestions that take the user's emotions into consideration and a richer user experience.

[0202] "User input information" refers to basic profile data, skills, interests, and other information that users provide to the system.

[0203] A "database" is an information management system used to temporarily or permanently store user input information.

[0204] "Natural language processing technology" refers to the technology that enables computers to understand, process, and generate human language.

[0205] "Means for evaluating user suitability" refers to methods and systems for determining a suitable occupation for a person based on the information they input.

[0206] "Means of suggesting occupations" refers to a function that suggests appropriate occupations to users based on evaluation results.

[0207] "Means for analyzing emotional states and adjusting interactions accordingly" refers to technologies that analyze a user's emotions in real time and dynamically change the user experience based on the results.

[0208] "External information sources" refer to internet and other information providers from which the system collects information such as recruitment information and market trends.

[0209] In the system implementing this invention, a server, a terminal, and a user work together in cooperation. The server is hosted on the cloud and is responsible for managing the information transmitted from the user's terminal. Users access the system using a smartphone or smart glasses and input the necessary information. This information includes basic profile data, skills, and interests.

[0210] The server is equipped with natural language processing technology and an emotion analysis engine. The natural language processing technology analyzes user input information and evaluates career suitability. The emotion analysis engine has the ability to analyze the user's emotional state in real time. This allows the system to recognize whether the user is anxious or at ease and adjust career suggestions based on the results.

[0211] Specifically, the server uses natural language processing technology to analyze user input data as soon as it receives it. Based on the analysis results, it suggests suitable occupations for the user. Meanwhile, an emotion analysis engine detects the user's emotional state, and if, for example, the user is feeling stressed, it presents suggestions for relaxation or encouraging messages.

[0212] Through their devices, users can view job information provided by the server, along with related success stories and recruitment status. Because they can obtain information about their chosen profession, they can make more specific and informed career choices. Furthermore, the server optimizes subsequent interactions based on how the user receives this information.

[0213] For example, if a user expresses excitement about a new profession, the emotion engine leverages this excitement, and the server presents positive success stories related to that profession. This process is performed in real time by an automated, dynamic system.

[0214] [Example of prompts for a generative AI model]

[0215] "Please provide the most relevant positive success stories, taking into account the emotional state of users when selecting an AA occupation."

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] Users use their devices to send basic profile data, skills, and interest information to the system. The server receives this information and stores it in a database. The entered data is registered in the database for post-processing analysis.

[0219] Step 2:

[0220] The server uses natural language processing technology to analyze user input information stored in the database. This analysis incorporates the input information as structured data into a model to diagnose the user's aptitude. As a result, the most suitable occupational field for the user is identified.

[0221] Step 3:

[0222] The server uses an emotion analysis engine to analyze additional real-time data (such as voice and facial expressions) obtained from the user's device and evaluate the user's emotional state. Based on the input emotion data, it determines, for example, whether the user is feeling safe or anxious. Based on the analysis results, the interaction is adjusted appropriately according to the user's emotions.

[0223] Step 4:

[0224] The server suggests suitable occupations to the user based on the results of natural language processing and sentiment analysis. The suggestions are tailored to the user's emotional state and include relaxing occupational suggestions and positive success stories. The server dynamically generates these suggestions using a generative AI model.

[0225] Step 5:

[0226] The terminal displays job suggestions and related recruitment information received from the server to the user. The user can review this and delve further into the details and success stories of jobs that match their interests. The user's responses and choices are fed back into the next suggestions, optimizing the system's interaction.

[0227] Step 6:

[0228] Users can choose to share information about their preferred occupations with companies. Based on this choice, the server makes the user's profile data public to companies. This allows users to start receiving recruitment offers in real time.

[0229] Each step is designed to improve the user experience, including examples of prompts for the generative AI model.

[0230] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0231] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0232] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0236] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0237] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0238] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0239] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0240] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0241] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0242] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0243] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0244] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0245] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0246] This invention is an AI-powered interactive career aptitude system aimed at supporting users in making appropriate career choices. The system performs an aptitude assessment based on user input regarding their experience, skills, and interests. It then analyzes this information through natural language processing and presents suitable career options to the user.

[0247] First, users access the system using their device and register personal information, work experience, and areas of interest. This data is sent to the server in real time and stored in a database. Users then begin interacting with the AI ​​in voice or text format, and the AI ​​collects their input and guides the conversation to extract the necessary information.

[0248] The server uses natural language processing technology to analyze user input and perform an aptitude assessment. The analysis results undergo further review and data matching to generate a list of the most suitable occupations for the user. The presented list includes job types that match the user's interests and related success stories.

[0249] As a concrete example, if a recent graduate user inputs information into this system and selects environmental science as their area of ​​particular interest, the system will identify an appropriate occupational category based on that information. For instance, it might suggest a job as a climate change analyst, and simultaneously provide success stories of related career paths and advice on acquiring skills for further career advancement.

[0250] Furthermore, users can check the current recruitment status for jobs they are interested in. The server collaborates with external sources to retrieve the latest recruitment information and provides it to the user. In addition, with the user's permission, the user's profile information is made public to companies, and they await recruitment offers.

[0251] Thus, the present invention provides an effective means to effectively connect users and companies and reduce mismatches in career choices.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] Users access the system using their devices and register for an account. They enter basic information, work experience, and areas of interest, and the device sends this information to the server.

[0255] Step 2:

[0256] The server stores the received user information in a database. During this process, it performs basic checks to verify the completeness and accuracy of the information.

[0257] Step 3:

[0258] The user initiates an interactive assessment with the AI ​​using their device. The AI ​​utilizes natural language processing technology to generate questions based on the user's profile.

[0259] Step 4:

[0260] The user answers questions from the AI, providing detailed information about their interests and skills. The device sends these answers to the server in real time.

[0261] Step 5:

[0262] The server analyzes the user's responses and uses a machine learning algorithm to perform an aptitude assessment. The assessment results are temporarily stored in a database.

[0263] Step 6:

[0264] The server generates a list of suitable occupations for the user based on the aptitude assessment results. This list, along with past success stories and information on the skills required for each occupation, is sent to the terminal.

[0265] Step 7:

[0266] Users view a list of jobs presented via their device and check the details. If necessary, they are provided with options to check the job availability for those jobs.

[0267] Step 8:

[0268] The server retrieves relevant job postings from external sources and displays the results on the terminal. The user then uses this information to make a career choice decision.

[0269] Step 9:

[0270] If the user consents, their device will be configured to share their profile information with companies. The server manages this, allowing companies to send recruitment information.

[0271] Step 10:

[0272] The server receives the recruitment information and notifies the user. The user checks the offer details through their device and decides on their next course of action.

[0273] (Example 1)

[0274] Next, we will describe Example 1. 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."

[0275] In today's labor market, a mismatch between individual aptitudes and market demand is common, making it difficult to choose the right job. This can lead to poor career decisions, resulting in decreased job satisfaction and stagnation in career development. This problem is particularly serious for new job seekers with limited experience and skills, highlighting the need for new technological approaches to address these challenges.

[0276] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0277] In this invention, the server includes means for receiving information from a user's terminal and storing the information in a storage device, means for analyzing the input information using natural language processing technology and evaluating the suitability of the user, and means for presenting a profession suitable for the user based on the evaluation result using a generative AI model. This enables detailed analysis of the user's skills and interests and supports optimal career selection.

[0278] A "user" is an individual or corporation that uses the system, inputs information, and is the subject that receives a diagnosis and proposal of career suitability based on the input.

[0279] A "terminal" is an electronic device used by a user to input information or receive results, and mainly refers to computing devices such as computers and smartphones.

[0280] "Information" is data such as the user's personal profile, work experience, and fields of interest input by the user, and is the material used by the system for analysis.

[0281] A "storage device" refers to a database or storage medium for permanently storing the received information, and is a device that enables safe storage and rapid access to information.

[0282] "Natural language processing technology" is a computational technology for analyzing text data from a user and understanding the meaning of language, and includes machine learning and text mining.

[0283] A "generative AI model" is a computational model for generating new data and proposals using artificial intelligence technology, and plays a role in evaluating the suitability of a career based on the user's input information.

[0284] "Evaluating suitability" is a process of analyzing the user's abilities and interests and determining the degree of suitability for a specific career based on this.

[0285] "Means" refers to the technical elements or methods incorporated into the system to achieve a specific function.

[0286] "Occupation" refers to the specific business or position recommended to the user as a result of the occupational suitability assessment.

[0287] "External information source" is a source for obtaining information from databases or servers existing outside the system and is used to obtain job offers.

[0288] The present invention is an interactive occupational suitability system that provides support for a user to select an appropriate occupation. The system utilizes a generative AI model and natural language processing technology to propose the optimal occupation to the user. The embodiments thereof will be specifically described below.

[0289] The user accesses the system using a terminal. This terminal is a computing device such as a computer or a smartphone. The user logs in or registers and enters their personal information, work experience, and fields of interest. These data are transmitted to the server via the terminal. The HTTPS protocol for secure communication through the Internet is used for information transmission.

[0290] The server stores the received data in a database as a storage device. This database can use a general relational database system, such as MySQL or PostgreSQL. Then, the server uses natural language processing technology to analyze the user's input information and evaluate the user's suitability. Specific NLP libraries such as spaCy or Google Cloud Natural Language API are used.

[0291] The server utilizes the generative AI model based on the analysis results to generate a list of occupations suitable for the user. This model matches past occupational data with the user's profile and proposes occupations based on the user's interests and skills. The proposed occupations include job contents and success stories related to the user's interests.

[0292] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the proposed occupation. This utilizes external job posting APIs, such as those provided by job posting platforms. The proposed occupation and the latest job postings are then presented to the user via their device.

[0293] As a concrete example, suppose a recent graduate accesses this system and enters their area of ​​interest, "environmental science." In this case, the system suggests professions such as climate change analyst or environmental consultant, and also provides advice on related success stories and necessary skills.

[0294] An example of a prompt message could be, "I'm a recent graduate and I'm interested in environmental science. What kind of job would suit me?" In this way, the system effectively supports the user in their career selection.

[0295] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0296] Step 1:

[0297] Users access the system using a terminal and enter their personal information, work experience, and areas of interest. The data is submitted by pressing a submit button through the user interface. Basic format checks are performed to ensure the information is in the correct format for transmission to the server. The output is user data in the correct format.

[0298] Step 2:

[0299] The server receives user data sent from the terminal and stores it in a storage device (database). During this process, the data is inserted into the database using SQL statements and stored securely. The input is user data, and the output is a confirmation that the data has been successfully saved to the database.

[0300] Step 3:

[0301] The server retrieves the saved user information and starts the analysis by making full use of natural language processing technology. Specifically, it tokenizes the text data retrieved from the database, extracts keywords, and classifies the content. Here, the input information is the raw data of the user, and a user profile is generated as the output.

[0302] Step 4:

[0303] The server uses a generative AI model to evaluate the career suitability based on the user profile obtained through analysis. The generative AI model has learned past data patterns and has the ability to propose the most suitable career categories for the user's interests and skills. Profile data is used as the input, and a list of careers suitable for the user is generated as the output.

[0304] Step 5:

[0305] The server accesses an external information source and retrieves the latest job recruitment information corresponding to the generated list of careers. It executes queries against various external job databases via an API and filters the relevant job information. The list of careers is used as the input, and the latest job information is collected as the output.

[0306] Step 6:

[0307] The server returns the generated list of careers and the latest job information to the terminal for display to the user. The user can view the detailed information of the recommended careers and the job situation through the terminal screen. The data from the server is used as the input, and the output is the display of information on the user interface.

[0308] <000097l>Step 7:

[0309] Based on the suggested job information, the user decides whether to make their profile public to companies. If they choose to make it public, the server updates the user's settings, enabling them to receive recruitment offers from companies. The input is the user's selection, and the output is an update to the profile's public status.

[0310] (Application Example 1)

[0311] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0312] In modern society, with the increasing diversity and complexity of career choices, it is difficult for individual users to find a suitable job. Furthermore, challenges include a lack of appropriate career paths, insufficient information on skill acquisition, and poor matching between career options and actual workplaces. There is also a need for increased efficiency in face-to-face counseling at physical locations.

[0313] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0314] This invention includes a server that provides means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's aptitude, means for suggesting suitable occupations based on the evaluation results and providing relevant career paths and skill acquisition information, means for providing a function that allows visitors to receive vocational aptitude tests using terminals installed in stores, and means for obtaining the recruitment status of suitable occupations from external information sources. As a result, users can discover the occupation that is most suitable for them and obtain specific career plans and skill improvement measures for that occupation. Furthermore, effective career selection support is realized through dialogue with advisors at physical stores.

[0315] A "user" refers to an individual who uses the system to undergo a career aptitude assessment.

[0316] "Input information" refers to information provided by the user, including data on their work experience, interests, skills, etc.

[0317] A "database" is an information management system that stores user input information and allows it to be referenced and updated as needed.

[0318] "Natural language processing technology" is a technology that enables computers to understand and interpret human language, and is used to analyze user input and evaluate aptitude.

[0319] "Occupational aptitude assessment" is an analytical process that identifies the most suitable occupation based on a user's skills and interests.

[0320] A "career path" is a systematically planned route outlining the stages of progression in a particular profession.

[0321] "Skill acquisition information" refers to information that provides users with specific guidelines and advice for acquiring the skills necessary for a particular occupation.

[0322] A "store-installed terminal" is an electronic device installed in a physical store that users can use to take a career aptitude test.

[0323] "External information sources" refer to information providers or platforms outside the system that are linked to provide current job openings.

[0324] To realize this invention, the server first receives user input information and stores it in a database in an appropriate format. The server then uses natural language processing technology to analyze the user's input and evaluates their vocational aptitude based on that analysis. For this purpose, natural language processing APIs such as the Google Cloud Natural Language API may be used.

[0325] Terminals installed in physical stores provide users with a means to take a career aptitude test. Users access the terminal and input information via voice or text. The terminal transmits this data to a server in real time and displays a list of the most suitable occupations for the user. The list also includes relevant career path and skills acquisition information.

[0326] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the listed occupations and provides them to users through their terminals. This allows users to obtain real-time job information for occupations they are interested in.

[0327] As a concrete example, consider a user who majored in environmental science at university. The user enters "I am interested in a career related to the environment" into the terminal. The program, as a result of its analysis, suggests the career of "climate change analyst" and provides information on related career paths and future skill acquisition.

[0328] As an example of a prompt, a user might input, "I want to work in the field of data science after graduating from university. What kind of job would suit me?" In response to this input, appropriate job suggestions and related information would be provided.

[0329] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0330] Step 1:

[0331] The user accesses their device and launches a career aptitude assessment application. The user inputs information about their work experience, interests, and skills in text or voice format. The input data is transmitted from the device to the server in real time. The input data format is standardized and converted into a format easily processed by the server.

[0332] Step 2:

[0333] The server stores the received input information in a database. This process verifies the accuracy and completeness of the input information and checks for any missing information. After verification, the information is stored in the database according to the data model.

[0334] Step 3:

[0335] The server analyzes the stored data using natural language processing technology. Specifically, it uses the Google Cloud Natural Language API to extract keywords related to the user's interests and skills and identify potential related occupations. Through this analysis, an assessment of the user's suitability for different occupations is performed.

[0336] Step 4:

[0337] The server generates a list of suitable occupations for the user based on the analysis results. The generated list includes career paths and skill acquisition information related to each occupation. The list is constructed by retrieving information from a database.

[0338] Step 5:

[0339] The generated list of occupations is provided to the user via the device. The information is displayed in the format specified by the user (text or audio). The user can browse this list and view detailed information about occupations that interest them.

[0340] Step 6:

[0341] The server interacts with external information sources to obtain the latest job postings. It queries external information sources to retrieve the latest job information and temporarily stores it in the database.

[0342] Step 7:

[0343] The device displays the latest job postings to the user. Based on the information presented, the user can check the application status of jobs they are interested in and decide on further actions.

[0344] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0345] This invention combines an AI-powered interactive career aptitude system with an emotion engine. Users access the system using a terminal and provide information about their career aptitude. This information includes basic profile data as well as skills and interests.

[0346] The system is hosted on a server and analyzes user input using an emotion engine. The emotion engine analyzes the user's input data and recognizes the user's emotional state. Based on this, it adjusts the dialogue appropriately in response to user feedback and corrects the aptitude evaluation results.

[0347] For example, if a user is feeling anxious about future career choices, the emotion engine detects this anxiety, and the server responds by providing reassuring career suggestions and more detailed success stories. This interaction is designed to allow users to use the system in a more relaxed manner.

[0348] Furthermore, the server evaluates the user's aptitude and, taking into account their emotional state, generates a list of suitable occupations. This list, along with relevant job postings, is presented to the user's device. Additionally, an emotion engine monitors how the user reacts to the aptitude assessment and job suggestions, dynamically optimizing the evaluation process and user experience through feedback.

[0349] Finally, with the user's consent, the system makes their profile public to companies and allows them to receive recruitment information in real time. This enables users to quickly access suitable occupations through the system. The integration of these functions significantly improves the user experience in career selection and optimizes matching with companies.

[0350] The following describes the processing flow.

[0351] Step 1:

[0352] The user logs into the system using their device. After logging in, a screen appears where the user can enter profile information, work experience, and areas of interest, and the user enters the required information.

[0353] Step 2:

[0354] The terminal sends the input information to the server, which then stores that information in a database. Simultaneously, the stored information is sent to the emotion engine to begin analysis.

[0355] Step 3:

[0356] The emotion engine analyzes user input data and uses natural language processing to recognize the user's emotional state. This emotional state data is then used in the evaluation process.

[0357] Step 4:

[0358] The server uses the analysis results from the emotion engine to execute a process to evaluate the user's suitability and generate an suitability score. Considering emotional data allows for a more accurate evaluation.

[0359] Step 5:

[0360] The server generates a list of suitable occupations for the user based on the aptitude assessment results. It adjusts the suggestion method and content according to the user's emotional state, providing reassuring occupational suggestions.

[0361] Step 6:

[0362] Users can view a list of jobs presented on their device and see related job postings and success stories. They can also request further information based on their interests.

[0363] Step 7:

[0364] The emotion engine monitors in real time how users react to career suggestions and information displays, and provides feedback via the device to help improve the user experience.

[0365] Step 8:

[0366] If a user is interested in a particular occupation, they should configure their device to allow receiving recruitment offers from companies related to that occupation.

[0367] Step 9:

[0368] The server verifies the settings and, based on the user's consent, publishes profile information to companies. It receives recruitment information from companies and immediately notifies the user via their device.

[0369] Step 10:

[0370] Users can check recruitment information via their devices and plan their next career steps. This allows users to continue receiving support for optimal career choices through the system.

[0371] (Example 2)

[0372] Next, we will describe Example 2. 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".

[0373] Modern vocational aptitude assessment systems require not only evaluations based on the user's skills and experience, but also more sophisticated career suggestions that take into account the user's emotional state. However, conventional systems have the problem of not being able to accurately grasp the user's emotions and dynamically adjust the content of the dialogue and career suggestions accordingly. Therefore, there is a need for a means to provide users with the most suitable career choices.

[0374] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0375] In this invention, the server includes means for receiving user input information and storing it in data storage; means for determining the user's emotional state using an emotion analysis model with natural language processing technology; means for analyzing the input information and emotional state and evaluating the user's suitability; and means for generating job suggestions that correspond to the user's emotions using a generative AI model and presenting suitable jobs to the user based on the evaluation results. This makes it possible to optimize job suggestions and evaluation processes that take the user's emotions into consideration.

[0376] "User input information" refers to basic profile data, skills, and interests provided by users accessing the system.

[0377] "Natural language processing technology" is a technology that enables computers to understand, analyze, and respond to human language, and is also used for analyzing emotional states.

[0378] An "emotion analysis model" is an algorithm or machine learning-based analysis method that recognizes and classifies emotional states from user input information.

[0379] A "generative AI model" is a model that utilizes artificial intelligence to generate appropriate career suggestions based on the user's emotional state.

[0380] "Data storage" refers to a system component used to store user input information and analysis results.

[0381] "Evaluation results" are the outcomes derived by the aptitude evaluation system based on the user's input information and emotional state, and form the basis of career suggestions.

[0382] "Career suggestion" is a process that presents users with career options deemed most suitable based on their aptitude assessment results.

[0383] "Scout information" refers to data about employment opportunities and recruitment information that companies send to users.

[0384] This invention is an interactive vocational aptitude assessment system that combines natural language processing technology and an emotion analysis model to recognize the user's emotional state and provide optimal vocational suggestions. Specific embodiments are described below.

[0385] Users access the system using a device and input their profile information, skills, and interests. The device collects this information and transmits it to the server via a secure communication protocol. The server stores the input information in data storage and transfers it to a sentiment analysis model using natural language processing technology.

[0386] Emotion analysis models process input information to determine the user's emotional state. High-precision algorithms and machine learning models are used for this analysis. The resulting emotional state is then used as important data to further evaluate the user's suitability.

[0387] The server uses a generative AI model to generate career suggestions that are tailored to the user's emotions. This process involves creating messages that are sensitive to the user's feelings, designed to reduce stress. The generated career suggestions are aligned with the user's skills and interests.

[0388] The generated list of occupations is presented to the user via the terminal, and the user's response is monitored. The server uses this feedback to dynamically optimize the dialogue and evaluation process.

[0389] For example, if a user inputs "I'm interested in programming but I'm not confident," the sentiment analysis model will detect anxiety, and the generative AI model will suggest programming jobs and learning resources suitable for beginners.

[0390] Example prompt: "If a user inputs that they are interested in programming but lack confidence, explain how to generate appropriate career suggestions while providing reassurance."

[0391] Thus, the present invention provides a system that offers vocational aptitude assessment that takes into account the user's emotional state, thereby improving the user experience and increasing the accuracy of matching with companies.

[0392] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0393] Step 1:

[0394] Users access the vocational aptitude assessment system using their devices and enter their profile information, skills, and interests. This input is done through forms, and the collected data is sent to the server using a secure communication protocol. Specific examples of input include age, work experience, and areas of interest (e.g., data science, graphic design).

[0395] Step 2:

[0396] The server stores the received user input information in data storage. At this stage, the data entered is uniquely managed for each user. The stored data is used as foundational data for subsequent analysis processes.

[0397] Step 3:

[0398] The server uses natural language processing technology to pass stored user input information to an emotion analysis model. Here, the text data is analyzed, and the user's emotional state is determined. This analysis uses machine learning algorithms, for example, to extract emotional states based on emotional keywords such as "anxiety" and "excitement" contained in the input text. The output is the analyzed emotional state data.

[0399] Step 4:

[0400] The server generates job suggestions using a generative AI model based on the emotional state obtained through emotion analysis, as well as the user's skills and interests. This process creates job suggestions optimized for the user according to their emotional state. For example, if the user is identified as "anxious," job suggestions that provide a sense of security will be proposed. A list of suggested jobs is generated as output.

[0401] Step 5:

[0402] The server sends the generated list of occupations to the terminal and presents it to the user. The terminal displays the list of occupations to the user in an easy-to-understand interface. The user can refer to the presented list of occupations and consider them in light of their own interests and aptitudes.

[0403] Step 6:

[0404] The device records how the user reacts to the presented list of occupations and sends this feedback to the server. Based on this feedback data, the server dynamically optimizes the parameters of the generative AI model and the sentiment analysis model to improve the accuracy of future suggestions.

[0405] Step 7:

[0406] With the user's consent, the server makes the user's profile information public to relevant companies and prepares to receive recruitment information from companies in real time. This information is notified to the device, allowing the user to quickly understand the expected job opportunities.

[0407] (Application Example 2)

[0408] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0409] Traditional career aptitude systems have the problem of providing a uniform and inadequately optimized user experience because they do not take into account the user's emotional state. Furthermore, when users experience emotional anxiety regarding career choices, there is a lack of means to alleviate that anxiety and support them in making informed choices with greater confidence.

[0410] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0411] In this invention, the server includes means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for analyzing the user's emotional state and adjusting the interaction according to that state. This makes it possible to provide optimal job suggestions that take the user's emotions into consideration and a richer user experience.

[0412] "User input information" refers to basic profile data, skills, interests, and other information that users provide to the system.

[0413] A "database" is an information management system used to temporarily or permanently store user input information.

[0414] "Natural language processing technology" refers to the technology that enables computers to understand, process, and generate human language.

[0415] "Means for evaluating user suitability" refers to methods and systems for determining a suitable occupation for a person based on the information they input.

[0416] "Means of suggesting occupations" refers to a function that suggests appropriate occupations to users based on evaluation results.

[0417] "Means for analyzing emotional states and adjusting interactions accordingly" refers to technologies that analyze a user's emotions in real time and dynamically change the user experience based on the results.

[0418] "External information sources" refer to internet and other information providers from which the system collects information such as recruitment information and market trends.

[0419] In the system implementing this invention, a server, a terminal, and a user work together in cooperation. The server is hosted on the cloud and is responsible for managing the information transmitted from the user's terminal. Users access the system using a smartphone or smart glasses and input the necessary information. This information includes basic profile data, skills, and interests.

[0420] The server is equipped with natural language processing technology and an emotion analysis engine. The natural language processing technology analyzes user input information and evaluates career suitability. The emotion analysis engine has the ability to analyze the user's emotional state in real time. This allows the system to recognize whether the user is anxious or at ease and adjust career suggestions based on the results.

[0421] Specifically, the server uses natural language processing technology to analyze user input data as soon as it receives it. Based on the analysis results, it suggests suitable occupations for the user. Meanwhile, an emotion analysis engine detects the user's emotional state, and if, for example, the user is feeling stressed, it presents suggestions for relaxation or encouraging messages.

[0422] Through their devices, users can view job information provided by the server, along with related success stories and recruitment status. Because they can obtain information about their chosen profession, they can make more specific and informed career choices. Furthermore, the server optimizes subsequent interactions based on how the user receives this information.

[0423] For example, if a user expresses excitement about a new profession, the emotion engine leverages this excitement, and the server presents positive success stories related to that profession. This process is performed in real time by an automated, dynamic system.

[0424] [Example of prompts for a generative AI model]

[0425] "Please provide the most relevant positive success stories, taking into account the emotional state of users when selecting an AA occupation."

[0426] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0427] Step 1:

[0428] Users use their devices to send basic profile data, skills, and interest information to the system. The server receives this information and stores it in a database. The entered data is registered in the database for post-processing analysis.

[0429] Step 2:

[0430] The server uses natural language processing technology to analyze user input information stored in the database. This analysis incorporates the input information as structured data into a model to diagnose the user's aptitude. As a result, the most suitable occupational field for the user is identified.

[0431] Step 3:

[0432] The server uses an emotion analysis engine to analyze additional real-time data (such as voice and facial expressions) obtained from the user's device and evaluate the user's emotional state. Based on the input emotion data, it determines, for example, whether the user is feeling safe or anxious. Based on the analysis results, the interaction is adjusted appropriately according to the user's emotions.

[0433] Step 4:

[0434] The server suggests suitable occupations to the user based on the results of natural language processing and sentiment analysis. The suggestions are tailored to the user's emotional state and include relaxing occupational suggestions and positive success stories. The server dynamically generates these suggestions using a generative AI model.

[0435] Step 5:

[0436] The terminal displays job suggestions and related recruitment information received from the server to the user. The user can review this and delve further into the details and success stories of jobs that match their interests. The user's responses and choices are fed back into the next suggestions, optimizing the system's interaction.

[0437] Step 6:

[0438] Users can choose to share information about their preferred occupations with companies. Based on this choice, the server makes the user's profile data public to companies. This allows users to start receiving recruitment offers in real time.

[0439] Each step is designed to improve the user experience, including examples of prompts for the generative AI model.

[0440] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0441] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0442] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0443] [Third Embodiment]

[0444] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0445] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0446] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0447] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0448] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0449] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0450] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0451] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0452] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0453] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0454] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0455] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0456] This invention is an AI-powered interactive career aptitude system aimed at supporting users in making appropriate career choices. The system performs an aptitude assessment based on user input regarding their experience, skills, and interests. It then analyzes this information through natural language processing and presents suitable career options to the user.

[0457] First, users access the system using their device and register personal information, work experience, and areas of interest. This data is sent to the server in real time and stored in a database. Users then begin interacting with the AI ​​in voice or text format, and the AI ​​collects their input and guides the conversation to extract the necessary information.

[0458] The server uses natural language processing technology to analyze user input and perform an aptitude assessment. The analysis results undergo further review and data matching to generate a list of the most suitable occupations for the user. The presented list includes job types that match the user's interests and related success stories.

[0459] As a concrete example, if a recent graduate user inputs information into this system and selects environmental science as their area of ​​particular interest, the system will identify an appropriate occupational category based on that information. For instance, it might suggest a job as a climate change analyst, and simultaneously provide success stories of related career paths and advice on acquiring skills for further career advancement.

[0460] Furthermore, users can check the current recruitment status for jobs they are interested in. The server collaborates with external sources to retrieve the latest recruitment information and provides it to the user. In addition, with the user's permission, the user's profile information is made public to companies, and they await recruitment offers.

[0461] Thus, the present invention provides an effective means to effectively connect users and companies and reduce mismatches in career choices.

[0462] The following describes the processing flow.

[0463] Step 1:

[0464] Users access the system using their devices and register for an account. They enter basic information, work experience, and areas of interest, and the device sends this information to the server.

[0465] Step 2:

[0466] The server stores the received user information in a database. During this process, it performs basic checks to verify the completeness and accuracy of the information.

[0467] Step 3:

[0468] The user initiates an interactive assessment with the AI ​​using their device. The AI ​​utilizes natural language processing technology to generate questions based on the user's profile.

[0469] Step 4:

[0470] The user answers questions from the AI, providing detailed information about their interests and skills. The device sends these answers to the server in real time.

[0471] Step 5:

[0472] The server analyzes the user's responses and uses a machine learning algorithm to perform an aptitude assessment. The assessment results are temporarily stored in a database.

[0473] Step 6:

[0474] The server generates a list of suitable occupations for the user based on the aptitude assessment results. This list, along with past success stories and information on the skills required for each occupation, is sent to the terminal.

[0475] Step 7:

[0476] Users view a list of jobs presented via their device and check the details. If necessary, they are provided with options to check the job availability for those jobs.

[0477] Step 8:

[0478] The server retrieves relevant job postings from external sources and displays the results on the terminal. The user then uses this information to make a career choice decision.

[0479] Step 9:

[0480] If the user consents, their device will be configured to share their profile information with companies. The server manages this, allowing companies to send recruitment information.

[0481] Step 10:

[0482] The server receives the recruitment information and notifies the user. The user checks the offer details through their device and decides on their next course of action.

[0483] (Example 1)

[0484] Next, we will describe Example 1. 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."

[0485] In today's labor market, a mismatch between individual aptitudes and market demand is common, making it difficult to choose the right job. This can lead to poor career decisions, resulting in decreased job satisfaction and stagnation in career development. This problem is particularly serious for new job seekers with limited experience and skills, highlighting the need for new technological approaches to address these challenges.

[0486] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0487] In this invention, the server includes means for receiving information from the user's terminal and storing the information in a storage device, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for presenting suitable occupations to the user based on the evaluation results using a generative AI model. This makes it possible to analyze the user's skills and interests in detail and support them in making the optimal career choice.

[0488] A "user" is an individual or legal entity that utilizes the system, inputs information, and receives vocational aptitude assessments and suggestions based on that input.

[0489] A "terminal" is an electronic device used by a user to input information or receive results, and primarily refers to computing devices such as computers and smartphones.

[0490] "Information" refers to data such as a user's personal profile, work experience, and areas of interest, which the system uses for analysis.

[0491] A "storage device" refers to a database or storage medium for permanently storing received information, and is a device that enables secure storage and rapid access to information.

[0492] "Natural language processing technology" refers to computational techniques for analyzing text data from users and understanding the meaning of language, and includes machine learning and text mining.

[0493] A "generative AI model" is a computational model that uses artificial intelligence technology to generate new data and suggestions, and plays a role in evaluating occupational suitability based on user input information.

[0494] "Assessing suitability" is the process of analyzing a user's abilities and interests and determining their suitability for a particular occupation based on that analysis.

[0495] "Means" refers to the technical elements or methods incorporated into a system to achieve a specific function.

[0496] "Occupation" refers to the specific tasks or positions recommended to the user as a result of the occupational aptitude assessment.

[0497] An "external information source" is a source for obtaining information from databases or servers located outside the system, and is used to retrieve job postings.

[0498] This invention is an interactive career aptitude system that provides support to users in selecting appropriate occupations. The system utilizes generative AI models and natural language processing technology to suggest optimal occupations to the user. The following describes its specific embodiments.

[0499] Users access the system using a device, such as a computer or smartphone. Users log in or register and enter their personal information, work experience, and areas of interest. This data is transmitted to the server via the device. The HTTPS protocol is used for secure communication over the internet.

[0500] The server stores the received data in a database, which serves as a storage device. This database can be a common relational database system, such as MySQL or PostgreSQL. Subsequently, the server uses natural language processing (NLP) techniques to analyze the user's input and evaluate the user's suitability. Specific NLP libraries used include spaCy and the Google Cloud Natural Language API.

[0501] The server uses an AI model based on the analysis results to generate a list of suitable occupations for the user. This model matches past occupational data with the user's profile and suggests occupations based on the user's interests and skills. The suggested occupations include job descriptions and success stories related to the user's interests.

[0502] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the proposed occupation. This utilizes external job posting APIs, such as those provided by job posting platforms. The proposed occupation and the latest job postings are then presented to the user via their device.

[0503] As a concrete example, suppose a recent graduate accesses this system and enters their area of ​​interest, "environmental science." In this case, the system suggests professions such as climate change analyst or environmental consultant, and also provides advice on related success stories and necessary skills.

[0504] An example of a prompt message could be, "I'm a recent graduate and I'm interested in environmental science. What kind of job would suit me?" In this way, the system effectively supports the user in their career selection.

[0505] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0506] Step 1:

[0507] Users access the system using a terminal and enter their personal information, work experience, and areas of interest. The data is submitted by pressing a submit button through the user interface. Basic format checks are performed to ensure the information is in the correct format for transmission to the server. The output is user data in the correct format.

[0508] Step 2:

[0509] The server receives user data sent from the terminal and stores it in a storage device (database). During this process, the data is inserted into the database using SQL statements and stored securely. The input is user data, and the output is a confirmation that the data has been successfully saved to the database.

[0510] Step 3:

[0511] The server retrieves stored user information and begins analysis using natural language processing techniques. Specifically, it tokenizes text data obtained from the database, extracts keywords, and classifies the content. Here, the input information is the user's raw data, and a user profile is generated as output.

[0512] Step 4:

[0513] The server uses a generative AI model to evaluate occupational suitability based on the user profile obtained through analysis. The generative AI model has learned from past data patterns and has the ability to suggest the most suitable occupational category for the user's interests and skills. Profile data is used as input, and a list of suitable occupations for the user is generated as output.

[0514] Step 5:

[0515] The server accesses external information sources and retrieves the latest job postings corresponding to the generated occupation list. It queries various external job databases via API and filters the relevant job postings. The input is an occupation list, and the output is a collection of the latest job postings.

[0516] Step 6:

[0517] The server sends the generated job list and the latest job postings back to the terminal and displays them to the user. The user can view detailed information and job availability for recommended jobs through the terminal screen. The input is data from the server, and the output is the information displayed on the user interface.

[0518] Step 7:

[0519] Based on the suggested job information, the user decides whether to make their profile public to companies. If they choose to make it public, the server updates the user's settings, enabling them to receive recruitment offers from companies. The input is the user's selection, and the output is an update to the profile's public status.

[0520] (Application Example 1)

[0521] Next, we will explain Application Example 1. In the following explanation, 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."

[0522] In modern society, with the increasing diversity and complexity of career choices, it is difficult for individual users to find a suitable job. Furthermore, challenges include a lack of appropriate career paths, insufficient information on skill acquisition, and poor matching between career options and actual workplaces. There is also a need for increased efficiency in face-to-face counseling at physical locations.

[0523] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0524] This invention includes a server that provides means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's aptitude, means for suggesting suitable occupations based on the evaluation results and providing relevant career paths and skill acquisition information, means for providing a function that allows visitors to receive vocational aptitude tests using terminals installed in stores, and means for obtaining the recruitment status of suitable occupations from external information sources. As a result, users can discover the occupation that is most suitable for them and obtain specific career plans and skill improvement measures for that occupation. Furthermore, effective career selection support is realized through dialogue with advisors at physical stores.

[0525] A "user" refers to an individual who uses the system to undergo a career aptitude assessment.

[0526] "Input information" refers to information provided by the user, including data on their work experience, interests, skills, etc.

[0527] A "database" is an information management system that stores user input information and allows it to be referenced and updated as needed.

[0528] "Natural language processing technology" is a technology that enables computers to understand and interpret human language, and is used to analyze user input and evaluate aptitude.

[0529] "Occupational aptitude assessment" is an analytical process that identifies the most suitable occupation based on a user's skills and interests.

[0530] A "career path" is a systematically planned route outlining the stages of progression in a particular profession.

[0531] "Skill acquisition information" refers to information that provides users with specific guidelines and advice for acquiring the skills necessary for a particular occupation.

[0532] A "store-installed terminal" is an electronic device installed in a physical store that users can use to take a career aptitude test.

[0533] "External information sources" refer to information providers or platforms outside the system that are linked to provide current job openings.

[0534] To realize this invention, the server first receives user input information and stores it in a database in an appropriate format. The server then uses natural language processing technology to analyze the user's input and evaluates their vocational aptitude based on that analysis. For this purpose, natural language processing APIs such as the Google Cloud Natural Language API may be used.

[0535] Terminals installed in physical stores provide users with a means to take a career aptitude test. Users access the terminal and input information via voice or text. The terminal transmits this data to a server in real time and displays a list of the most suitable occupations for the user. The list also includes relevant career path and skills acquisition information.

[0536] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the listed occupations and provides them to users through their terminals. This allows users to obtain real-time job information for occupations they are interested in.

[0537] As a concrete example, consider a user who majored in environmental science at university. The user enters "I am interested in a career related to the environment" into the terminal. The program, as a result of its analysis, suggests the career of "climate change analyst" and provides information on related career paths and future skill acquisition.

[0538] As an example of a prompt, a user might input, "I want to work in the field of data science after graduating from university. What kind of job would suit me?" In response to this input, appropriate job suggestions and related information would be provided.

[0539] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0540] Step 1:

[0541] The user accesses their device and launches a career aptitude assessment application. The user inputs information about their work experience, interests, and skills in text or voice format. The input data is transmitted from the device to the server in real time. The input data format is standardized and converted into a format easily processed by the server.

[0542] Step 2:

[0543] The server stores the received input information in a database. This process verifies the accuracy and completeness of the input information and checks for any missing information. After verification, the information is stored in the database according to the data model.

[0544] Step 3:

[0545] The server analyzes the stored data using natural language processing technology. Specifically, it uses the Google Cloud Natural Language API to extract keywords related to the user's interests and skills and identify potential related occupations. Through this analysis, an assessment of the user's suitability for different occupations is performed.

[0546] Step 4:

[0547] The server generates a list of suitable occupations for the user based on the analysis results. The generated list includes career paths and skill acquisition information related to each occupation. The list is constructed by retrieving information from a database.

[0548] Step 5:

[0549] The generated list of occupations is provided to the user via the device. The information is displayed in the format specified by the user (text or audio). The user can browse this list and view detailed information about occupations that interest them.

[0550] Step 6:

[0551] The server interacts with external information sources to obtain the latest job postings. It queries external information sources to retrieve the latest job information and temporarily stores it in the database.

[0552] Step 7:

[0553] The device displays the latest job postings to the user. Based on the information presented, the user can check the application status of jobs they are interested in and decide on further actions.

[0554] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0555] This invention combines an AI-powered interactive career aptitude system with an emotion engine. Users access the system using a terminal and provide information about their career aptitude. This information includes basic profile data as well as skills and interests.

[0556] The system is hosted on a server and analyzes user input using an emotion engine. The emotion engine analyzes the user's input data and recognizes the user's emotional state. Based on this, it adjusts the dialogue appropriately in response to user feedback and corrects the aptitude evaluation results.

[0557] For example, if a user is feeling anxious about future career choices, the emotion engine detects this anxiety, and the server responds by providing reassuring career suggestions and more detailed success stories. This interaction is designed to allow users to use the system in a more relaxed manner.

[0558] Furthermore, the server evaluates the user's aptitude and, taking into account their emotional state, generates a list of suitable occupations. This list, along with relevant job postings, is presented to the user's device. Additionally, an emotion engine monitors how the user reacts to the aptitude assessment and job suggestions, dynamically optimizing the evaluation process and user experience through feedback.

[0559] Finally, with the user's consent, the system makes their profile public to companies and allows them to receive recruitment information in real time. This enables users to quickly access suitable occupations through the system. The integration of these functions significantly improves the user experience in career selection and optimizes matching with companies.

[0560] The following describes the processing flow.

[0561] Step 1:

[0562] The user logs into the system using their device. After logging in, a screen appears where the user can enter profile information, work experience, and areas of interest, and the user enters the required information.

[0563] Step 2:

[0564] The terminal sends the input information to the server, which then stores that information in a database. Simultaneously, the stored information is sent to the emotion engine to begin analysis.

[0565] Step 3:

[0566] The emotion engine analyzes user input data and uses natural language processing to recognize the user's emotional state. This emotional state data is then used in the evaluation process.

[0567] Step 4:

[0568] The server uses the analysis results from the emotion engine to execute a process to evaluate the user's suitability and generate an suitability score. Considering emotional data allows for a more accurate evaluation.

[0569] Step 5:

[0570] The server generates a list of suitable occupations for the user based on the aptitude assessment results. It adjusts the suggestion method and content according to the user's emotional state, providing reassuring occupational suggestions.

[0571] Step 6:

[0572] Users can view a list of jobs presented on their device and see related job postings and success stories. They can also request further information based on their interests.

[0573] Step 7:

[0574] The emotion engine monitors in real time how users react to career suggestions and information displays, and provides feedback via the device to help improve the user experience.

[0575] Step 8:

[0576] If a user is interested in a particular occupation, they should configure their device to allow receiving recruitment offers from companies related to that occupation.

[0577] Step 9:

[0578] The server verifies the settings and, based on the user's consent, publishes profile information to companies. It receives recruitment information from companies and immediately notifies the user via their device.

[0579] Step 10:

[0580] Users can check recruitment information via their devices and plan their next career steps. This allows users to continue receiving support for optimal career choices through the system.

[0581] (Example 2)

[0582] Next, we will describe Example 2. 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."

[0583] Modern vocational aptitude assessment systems require not only evaluations based on the user's skills and experience, but also more sophisticated career suggestions that take into account the user's emotional state. However, conventional systems have the problem of not being able to accurately grasp the user's emotions and dynamically adjust the content of the dialogue and career suggestions accordingly. Therefore, there is a need for a means to provide users with the most suitable career choices.

[0584] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0585] In this invention, the server includes means for receiving user input information and storing it in data storage; means for determining the user's emotional state using an emotion analysis model with natural language processing technology; means for analyzing the input information and emotional state and evaluating the user's suitability; and means for generating job suggestions that correspond to the user's emotions using a generative AI model and presenting suitable jobs to the user based on the evaluation results. This makes it possible to optimize job suggestions and evaluation processes that take the user's emotions into consideration.

[0586] "User input information" refers to basic profile data, skills, and interests provided by users accessing the system.

[0587] "Natural language processing technology" is a technology that enables computers to understand, analyze, and respond to human language, and is also used for analyzing emotional states.

[0588] An "emotion analysis model" is an algorithm or machine learning-based analysis method that recognizes and classifies emotional states from user input information.

[0589] A "generative AI model" is a model that utilizes artificial intelligence to generate appropriate career suggestions based on the user's emotional state.

[0590] "Data storage" refers to a system component used to store user input information and analysis results.

[0591] "Evaluation results" are the outcomes derived by the aptitude evaluation system based on the user's input information and emotional state, and form the basis of career suggestions.

[0592] "Career suggestion" is a process that presents users with career options deemed most suitable based on their aptitude assessment results.

[0593] "Scout information" refers to data about employment opportunities and recruitment information that companies send to users.

[0594] This invention is an interactive vocational aptitude assessment system that combines natural language processing technology and an emotion analysis model to recognize the user's emotional state and provide optimal vocational suggestions. Specific embodiments are described below.

[0595] Users access the system using a device and input their profile information, skills, and interests. The device collects this information and transmits it to the server via a secure communication protocol. The server stores the input information in data storage and transfers it to a sentiment analysis model using natural language processing technology.

[0596] Emotion analysis models process input information to determine the user's emotional state. High-precision algorithms and machine learning models are used for this analysis. The resulting emotional state is then used as important data to further evaluate the user's suitability.

[0597] The server uses a generative AI model to generate career suggestions that are tailored to the user's emotions. This process involves creating messages that are sensitive to the user's feelings, designed to reduce stress. The generated career suggestions are aligned with the user's skills and interests.

[0598] The generated list of occupations is presented to the user via the terminal, and the user's response is monitored. The server uses this feedback to dynamically optimize the dialogue and evaluation process.

[0599] For example, if a user inputs "I'm interested in programming but I'm not confident," the sentiment analysis model will detect anxiety, and the generative AI model will suggest programming jobs and learning resources suitable for beginners.

[0600] Example prompt: "If a user inputs that they are interested in programming but lack confidence, explain how to generate appropriate career suggestions while providing reassurance."

[0601] Thus, the present invention provides a system that offers vocational aptitude assessment that takes into account the user's emotional state, thereby improving the user experience and increasing the accuracy of matching with companies.

[0602] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0603] Step 1:

[0604] Users access the vocational aptitude assessment system using their devices and enter their profile information, skills, and interests. This input is done through forms, and the collected data is sent to the server using a secure communication protocol. Specific examples of input include age, work experience, and areas of interest (e.g., data science, graphic design).

[0605] Step 2:

[0606] The server stores the received user input information in data storage. At this stage, the data entered is uniquely managed for each user. The stored data is used as foundational data for subsequent analysis processes.

[0607] Step 3:

[0608] The server uses natural language processing technology to pass stored user input information to an emotion analysis model. Here, the text data is analyzed, and the user's emotional state is determined. This analysis uses machine learning algorithms, for example, to extract emotional states based on emotional keywords such as "anxiety" and "excitement" contained in the input text. The output is the analyzed emotional state data.

[0609] Step 4:

[0610] The server generates job suggestions using a generative AI model based on the emotional state obtained through emotion analysis, as well as the user's skills and interests. This process creates job suggestions optimized for the user according to their emotional state. For example, if the user is identified as "anxious," job suggestions that provide a sense of security will be proposed. A list of suggested jobs is generated as output.

[0611] Step 5:

[0612] The server sends the generated list of occupations to the terminal and presents it to the user. The terminal displays the list of occupations to the user in an easy-to-understand interface. The user can refer to the presented list of occupations and consider them in light of their own interests and aptitudes.

[0613] Step 6:

[0614] The device records how the user reacts to the presented list of occupations and sends this feedback to the server. Based on this feedback data, the server dynamically optimizes the parameters of the generative AI model and the sentiment analysis model to improve the accuracy of future suggestions.

[0615] Step 7:

[0616] With the user's consent, the server makes the user's profile information public to relevant companies and prepares to receive recruitment information from companies in real time. This information is notified to the device, allowing the user to quickly understand the expected job opportunities.

[0617] (Application Example 2)

[0618] Next, we will explain application example 2. In the following explanation, 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."

[0619] Traditional career aptitude systems have the problem of providing a uniform and inadequately optimized user experience because they do not take into account the user's emotional state. Furthermore, when users experience emotional anxiety regarding career choices, there is a lack of means to alleviate that anxiety and support them in making informed choices with greater confidence.

[0620] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0621] In this invention, the server includes means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for analyzing the user's emotional state and adjusting the interaction according to that state. This makes it possible to provide optimal job suggestions that take the user's emotions into consideration and a richer user experience.

[0622] "User input information" refers to basic profile data, skills, interests, and other information that users provide to the system.

[0623] A "database" is an information management system used to temporarily or permanently store user input information.

[0624] "Natural language processing technology" refers to the technology that enables computers to understand, process, and generate human language.

[0625] "Means for evaluating user suitability" refers to methods and systems for determining a suitable occupation for a person based on the information they input.

[0626] "Means of suggesting occupations" refers to a function that suggests appropriate occupations to users based on evaluation results.

[0627] "Means for analyzing emotional states and adjusting interactions accordingly" refers to technologies that analyze a user's emotions in real time and dynamically change the user experience based on the results.

[0628] "External information sources" refer to internet and other information providers from which the system collects information such as recruitment information and market trends.

[0629] In the system implementing this invention, a server, a terminal, and a user work together in cooperation. The server is hosted on the cloud and is responsible for managing the information transmitted from the user's terminal. Users access the system using a smartphone or smart glasses and input the necessary information. This information includes basic profile data, skills, and interests.

[0630] The server is equipped with natural language processing technology and an emotion analysis engine. The natural language processing technology analyzes user input information and evaluates career suitability. The emotion analysis engine has the ability to analyze the user's emotional state in real time. This allows the system to recognize whether the user is anxious or at ease and adjust career suggestions based on the results.

[0631] Specifically, the server uses natural language processing technology to analyze user input data as soon as it receives it. Based on the analysis results, it suggests suitable occupations for the user. Meanwhile, an emotion analysis engine detects the user's emotional state, and if, for example, the user is feeling stressed, it presents suggestions for relaxation or encouraging messages.

[0632] Through their devices, users can view job information provided by the server, along with related success stories and recruitment status. Because they can obtain information about their chosen profession, they can make more specific and informed career choices. Furthermore, the server optimizes subsequent interactions based on how the user receives this information.

[0633] For example, if a user expresses excitement about a new profession, the emotion engine leverages this excitement, and the server presents positive success stories related to that profession. This process is performed in real time by an automated, dynamic system.

[0634] [Example of prompts for a generative AI model]

[0635] "Please provide the most relevant positive success stories, taking into account the emotional state of users when selecting an AA occupation."

[0636] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0637] Step 1:

[0638] Users use their devices to send basic profile data, skills, and interest information to the system. The server receives this information and stores it in a database. The entered data is registered in the database for post-processing analysis.

[0639] Step 2:

[0640] The server uses natural language processing technology to analyze user input information stored in the database. This analysis incorporates the input information as structured data into a model to diagnose the user's aptitude. As a result, the most suitable occupational field for the user is identified.

[0641] Step 3:

[0642] The server uses an emotion analysis engine to analyze additional real-time data (such as voice and facial expressions) obtained from the user's device and evaluate the user's emotional state. Based on the input emotion data, it determines, for example, whether the user is feeling safe or anxious. Based on the analysis results, the interaction is adjusted appropriately according to the user's emotions.

[0643] Step 4:

[0644] The server suggests suitable occupations to the user based on the results of natural language processing and sentiment analysis. The suggestions are tailored to the user's emotional state and include relaxing occupational suggestions and positive success stories. The server dynamically generates these suggestions using a generative AI model.

[0645] Step 5:

[0646] The terminal displays job suggestions and related recruitment information received from the server to the user. The user can review this and delve further into the details and success stories of jobs that match their interests. The user's responses and choices are fed back into the next suggestions, optimizing the system's interaction.

[0647] Step 6:

[0648] Users can choose to share information about their preferred occupations with companies. Based on this choice, the server makes the user's profile data public to companies. This allows users to start receiving recruitment offers in real time.

[0649] Each step is designed to improve the user experience, including examples of prompts for the generative AI model.

[0650] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0651] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0652] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0653] [Fourth Embodiment]

[0654] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0655] As shown in Figure 7, the 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.

[0656] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0657] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0658] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0659] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0660] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0661] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0662] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0663] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0664] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0665] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0666] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0667] This invention is an AI-powered interactive career aptitude system aimed at supporting users in making appropriate career choices. The system performs an aptitude assessment based on user input regarding their experience, skills, and interests. It then analyzes this information through natural language processing and presents suitable career options to the user.

[0668] First, users access the system using their device and register personal information, work experience, and areas of interest. This data is sent to the server in real time and stored in a database. Users then begin interacting with the AI ​​in voice or text format, and the AI ​​collects their input and guides the conversation to extract the necessary information.

[0669] The server uses natural language processing technology to analyze user input and perform an aptitude assessment. The analysis results undergo further review and data matching to generate a list of the most suitable occupations for the user. The presented list includes job types that match the user's interests and related success stories.

[0670] As a concrete example, if a recent graduate user inputs information into this system and selects environmental science as their area of ​​particular interest, the system will identify an appropriate occupational category based on that information. For instance, it might suggest a job as a climate change analyst, and simultaneously provide success stories of related career paths and advice on acquiring skills for further career advancement.

[0671] Furthermore, users can check the current recruitment status for jobs they are interested in. The server collaborates with external sources to retrieve the latest recruitment information and provides it to the user. In addition, with the user's permission, the user's profile information is made public to companies, and they await recruitment offers.

[0672] Thus, the present invention provides an effective means to effectively connect users and companies and reduce mismatches in career choices.

[0673] The following describes the processing flow.

[0674] Step 1:

[0675] Users access the system using their devices and register for an account. They enter basic information, work experience, and areas of interest, and the device sends this information to the server.

[0676] Step 2:

[0677] The server stores the received user information in a database. During this process, it performs basic checks to verify the completeness and accuracy of the information.

[0678] Step 3:

[0679] The user initiates an interactive assessment with the AI ​​using their device. The AI ​​utilizes natural language processing technology to generate questions based on the user's profile.

[0680] Step 4:

[0681] The user answers questions from the AI, providing detailed information about their interests and skills. The device sends these answers to the server in real time.

[0682] Step 5:

[0683] The server analyzes the user's responses and uses a machine learning algorithm to perform an aptitude assessment. The assessment results are temporarily stored in a database.

[0684] Step 6:

[0685] The server generates a list of suitable occupations for the user based on the aptitude assessment results. This list, along with past success stories and information on the skills required for each occupation, is sent to the terminal.

[0686] Step 7:

[0687] Users view a list of jobs presented via their device and check the details. If necessary, they are provided with options to check the job availability for those jobs.

[0688] Step 8:

[0689] The server retrieves relevant job postings from external sources and displays the results on the terminal. The user then uses this information to make a career choice decision.

[0690] Step 9:

[0691] If the user consents, their device will be configured to share their profile information with companies. The server manages this, allowing companies to send recruitment information.

[0692] Step 10:

[0693] The server receives the recruitment information and notifies the user. The user checks the offer details through their device and decides on their next course of action.

[0694] (Example 1)

[0695] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0696] In today's labor market, a mismatch between individual aptitudes and market demand is common, making it difficult to choose the right job. This can lead to poor career decisions, resulting in decreased job satisfaction and stagnation in career development. This problem is particularly serious for new job seekers with limited experience and skills, highlighting the need for new technological approaches to address these challenges.

[0697] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0698] In this invention, the server includes means for receiving information from the user's terminal and storing the information in a storage device, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for presenting suitable occupations to the user based on the evaluation results using a generative AI model. This makes it possible to analyze the user's skills and interests in detail and support them in making the optimal career choice.

[0699] A "user" is an individual or legal entity that utilizes the system, inputs information, and receives vocational aptitude assessments and suggestions based on that input.

[0700] A "terminal" is an electronic device used by a user to input information or receive results, and primarily refers to computing devices such as computers and smartphones.

[0701] "Information" refers to data such as a user's personal profile, work experience, and areas of interest, which the system uses for analysis.

[0702] A "storage device" refers to a database or storage medium for permanently storing received information, and is a device that enables secure storage and rapid access to information.

[0703] "Natural language processing technology" refers to computational techniques for analyzing text data from users and understanding the meaning of language, and includes machine learning and text mining.

[0704] A "generative AI model" is a computational model that uses artificial intelligence technology to generate new data and suggestions, and plays a role in evaluating occupational suitability based on user input information.

[0705] "Assessing suitability" is the process of analyzing a user's abilities and interests and determining their suitability for a particular occupation based on that analysis.

[0706] "Means" refers to the technical elements or methods incorporated into a system to achieve a specific function.

[0707] "Occupation" refers to the specific tasks or positions recommended to the user as a result of the occupational aptitude assessment.

[0708] An "external information source" is a source for obtaining information from databases or servers located outside the system, and is used to retrieve job postings.

[0709] This invention is an interactive career aptitude system that provides support to users in selecting appropriate occupations. The system utilizes generative AI models and natural language processing technology to suggest optimal occupations to the user. The following describes its specific embodiments.

[0710] Users access the system using a device, such as a computer or smartphone. Users log in or register and enter their personal information, work experience, and areas of interest. This data is transmitted to the server via the device. The HTTPS protocol is used for secure communication over the internet.

[0711] The server stores the received data in a database, which serves as a storage device. This database can be a common relational database system, such as MySQL or PostgreSQL. Subsequently, the server uses natural language processing (NLP) techniques to analyze the user's input and evaluate the user's suitability. Specific NLP libraries used include spaCy and the Google Cloud Natural Language API.

[0712] The server uses an AI model based on the analysis results to generate a list of suitable occupations for the user. This model matches past occupational data with the user's profile and suggests occupations based on the user's interests and skills. The suggested occupations include job descriptions and success stories related to the user's interests.

[0713] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the proposed occupation. This utilizes external job posting APIs, such as those provided by job posting platforms. The proposed occupation and the latest job postings are then presented to the user via their device.

[0714] As a concrete example, suppose a recent graduate accesses this system and enters their area of ​​interest, "environmental science." In this case, the system suggests professions such as climate change analyst or environmental consultant, and also provides advice on related success stories and necessary skills.

[0715] An example of a prompt message could be, "I'm a recent graduate and I'm interested in environmental science. What kind of job would suit me?" In this way, the system effectively supports the user in their career selection.

[0716] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0717] Step 1:

[0718] Users access the system using a terminal and enter their personal information, work experience, and areas of interest. The data is submitted by pressing a submit button through the user interface. Basic format checks are performed to ensure the information is in the correct format for transmission to the server. The output is user data in the correct format.

[0719] Step 2:

[0720] The server receives user data sent from the terminal and stores it in a storage device (database). During this process, the data is inserted into the database using SQL statements and stored securely. The input is user data, and the output is a confirmation that the data has been successfully saved to the database.

[0721] Step 3:

[0722] The server retrieves stored user information and begins analysis using natural language processing techniques. Specifically, it tokenizes text data obtained from the database, extracts keywords, and classifies the content. Here, the input information is the user's raw data, and a user profile is generated as output.

[0723] Step 4:

[0724] The server uses a generative AI model to evaluate occupational suitability based on the user profile obtained through analysis. The generative AI model has learned from past data patterns and has the ability to suggest the most suitable occupational category for the user's interests and skills. Profile data is used as input, and a list of suitable occupations for the user is generated as output.

[0725] Step 5:

[0726] The server accesses external information sources and retrieves the latest job postings corresponding to the generated occupation list. It queries various external job databases via API and filters the relevant job postings. The input is an occupation list, and the output is a collection of the latest job postings.

[0727] Step 6:

[0728] The server sends the generated job list and the latest job postings back to the terminal and displays them to the user. The user can view detailed information and job availability for recommended jobs through the terminal screen. The input is data from the server, and the output is the information displayed on the user interface.

[0729] Step 7:

[0730] Based on the suggested job information, the user decides whether to make their profile public to companies. If they choose to make it public, the server updates the user's settings, enabling them to receive recruitment offers from companies. The input is the user's selection, and the output is an update to the profile's public status.

[0731] (Application Example 1)

[0732] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] In modern society, with the increasing diversity and complexity of career choices, it is difficult for individual users to find a suitable job. Furthermore, challenges include a lack of appropriate career paths, insufficient information on skill acquisition, and poor matching between career options and actual workplaces. There is also a need for increased efficiency in face-to-face counseling at physical locations.

[0734] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0735] This invention includes a server that provides means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's aptitude, means for suggesting suitable occupations based on the evaluation results and providing relevant career paths and skill acquisition information, means for providing a function that allows visitors to receive vocational aptitude tests using terminals installed in stores, and means for obtaining the recruitment status of suitable occupations from external information sources. As a result, users can discover the occupation that is most suitable for them and obtain specific career plans and skill improvement measures for that occupation. Furthermore, effective career selection support is realized through dialogue with advisors at physical stores.

[0736] A "user" refers to an individual who uses the system to undergo a career aptitude assessment.

[0737] "Input information" refers to information provided by the user, including data on their work experience, interests, skills, etc.

[0738] A "database" is an information management system that stores user input information and allows it to be referenced and updated as needed.

[0739] "Natural language processing technology" is a technology that enables computers to understand and interpret human language, and is used to analyze user input and evaluate aptitude.

[0740] "Occupational aptitude assessment" is an analytical process that identifies the most suitable occupation based on a user's skills and interests.

[0741] A "career path" is a systematically planned route outlining the stages of progression in a particular profession.

[0742] "Skill acquisition information" refers to information that provides users with specific guidelines and advice for acquiring the skills necessary for a particular occupation.

[0743] A "store-installed terminal" is an electronic device installed in a physical store that users can use to take a career aptitude test.

[0744] "External information sources" refer to information providers or platforms outside the system that are linked to provide current job openings.

[0745] To realize this invention, the server first receives user input information and stores it in a database in an appropriate format. The server then uses natural language processing technology to analyze the user's input and evaluates their vocational aptitude based on that analysis. For this purpose, natural language processing APIs such as the Google Cloud Natural Language API may be used.

[0746] Terminals installed in physical stores provide users with a means to take a career aptitude test. Users access the terminal and input information via voice or text. The terminal transmits this data to a server in real time and displays a list of the most suitable occupations for the user. The list also includes relevant career path and skills acquisition information.

[0747] Furthermore, the server collaborates with external information sources to retrieve the latest job postings for the listed occupations and provides them to users through their terminals. This allows users to obtain real-time job information for occupations they are interested in.

[0748] As a concrete example, consider a user who majored in environmental science at university. The user enters "I am interested in a career related to the environment" into the terminal. The program, as a result of its analysis, suggests the career of "climate change analyst" and provides information on related career paths and future skill acquisition.

[0749] As an example of a prompt, a user might input, "I want to work in the field of data science after graduating from university. What kind of job would suit me?" In response to this input, appropriate job suggestions and related information would be provided.

[0750] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0751] Step 1:

[0752] The user accesses their device and launches a career aptitude assessment application. The user inputs information about their work experience, interests, and skills in text or voice format. The input data is transmitted from the device to the server in real time. The input data format is standardized and converted into a format easily processed by the server.

[0753] Step 2:

[0754] The server stores the received input information in a database. This process verifies the accuracy and completeness of the input information and checks for any missing information. After verification, the information is stored in the database according to the data model.

[0755] Step 3:

[0756] The server analyzes the stored data using natural language processing technology. Specifically, it uses the Google Cloud Natural Language API to extract keywords related to the user's interests and skills and identify potential related occupations. Through this analysis, an assessment of the user's suitability for different occupations is performed.

[0757] Step 4:

[0758] The server generates a list of suitable occupations for the user based on the analysis results. The generated list includes career paths and skill acquisition information related to each occupation. The list is constructed by retrieving information from a database.

[0759] Step 5:

[0760] The generated list of occupations is provided to the user via the device. The information is displayed in the format specified by the user (text or audio). The user can browse this list and view detailed information about occupations that interest them.

[0761] Step 6:

[0762] The server interacts with external information sources to obtain the latest job postings. It queries external information sources to retrieve the latest job information and temporarily stores it in the database.

[0763] Step 7:

[0764] The device displays the latest job postings to the user. Based on the information presented, the user can check the application status of jobs they are interested in and decide on further actions.

[0765] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0766] This invention combines an AI-powered interactive career aptitude system with an emotion engine. Users access the system using a terminal and provide information about their career aptitude. This information includes basic profile data as well as skills and interests.

[0767] The system is hosted on a server and analyzes user input using an emotion engine. The emotion engine analyzes the user's input data and recognizes the user's emotional state. Based on this, it adjusts the dialogue appropriately in response to user feedback and corrects the aptitude evaluation results.

[0768] For example, if a user is feeling anxious about future career choices, the emotion engine detects this anxiety, and the server responds by providing reassuring career suggestions and more detailed success stories. This interaction is designed to allow users to use the system in a more relaxed manner.

[0769] Furthermore, the server evaluates the user's aptitude and, taking into account their emotional state, generates a list of suitable occupations. This list, along with relevant job postings, is presented to the user's device. Additionally, an emotion engine monitors how the user reacts to the aptitude assessment and job suggestions, dynamically optimizing the evaluation process and user experience through feedback.

[0770] Finally, with the user's consent, the system makes their profile public to companies and allows them to receive recruitment information in real time. This enables users to quickly access suitable occupations through the system. The integration of these functions significantly improves the user experience in career selection and optimizes matching with companies.

[0771] The following describes the processing flow.

[0772] Step 1:

[0773] The user logs into the system using their device. After logging in, a screen appears where the user can enter profile information, work experience, and areas of interest, and the user enters the required information.

[0774] Step 2:

[0775] The terminal sends the input information to the server, which then stores that information in a database. Simultaneously, the stored information is sent to the emotion engine to begin analysis.

[0776] Step 3:

[0777] The emotion engine analyzes user input data and uses natural language processing to recognize the user's emotional state. This emotional state data is then used in the evaluation process.

[0778] Step 4:

[0779] The server uses the analysis results from the emotion engine to execute a process to evaluate the user's suitability and generate an suitability score. Considering emotional data allows for a more accurate evaluation.

[0780] Step 5:

[0781] The server generates a list of suitable occupations for the user based on the aptitude assessment results. It adjusts the suggestion method and content according to the user's emotional state, providing reassuring occupational suggestions.

[0782] Step 6:

[0783] Users can view a list of jobs presented on their device and see related job postings and success stories. They can also request further information based on their interests.

[0784] Step 7:

[0785] The emotion engine monitors in real time how users react to career suggestions and information displays, and provides feedback via the device to help improve the user experience.

[0786] Step 8:

[0787] If a user is interested in a particular occupation, they should configure their device to allow receiving recruitment offers from companies related to that occupation.

[0788] Step 9:

[0789] The server verifies the settings and, based on the user's consent, publishes profile information to companies. It receives recruitment information from companies and immediately notifies the user via their device.

[0790] Step 10:

[0791] Users can check recruitment information via their devices and plan their next career steps. This allows users to continue receiving support for optimal career choices through the system.

[0792] (Example 2)

[0793] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0794] Modern vocational aptitude assessment systems require not only evaluations based on the user's skills and experience, but also more sophisticated career suggestions that take into account the user's emotional state. However, conventional systems have the problem of not being able to accurately grasp the user's emotions and dynamically adjust the content of the dialogue and career suggestions accordingly. Therefore, there is a need for a means to provide users with the most suitable career choices.

[0795] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0796] In this invention, the server includes means for receiving user input information and storing it in data storage; means for determining the user's emotional state using an emotion analysis model with natural language processing technology; means for analyzing the input information and emotional state and evaluating the user's suitability; and means for generating job suggestions that correspond to the user's emotions using a generative AI model and presenting suitable jobs to the user based on the evaluation results. This makes it possible to optimize job suggestions and evaluation processes that take the user's emotions into consideration.

[0797] "User input information" refers to basic profile data, skills, and interests provided by users accessing the system.

[0798] "Natural language processing technology" is a technology that enables computers to understand, analyze, and respond to human language, and is also used for analyzing emotional states.

[0799] An "emotion analysis model" is an algorithm or machine learning-based analysis method that recognizes and classifies emotional states from user input information.

[0800] A "generative AI model" is a model that utilizes artificial intelligence to generate appropriate career suggestions based on the user's emotional state.

[0801] "Data storage" refers to a system component used to store user input information and analysis results.

[0802] "Evaluation results" are the outcomes derived by the aptitude evaluation system based on the user's input information and emotional state, and form the basis of career suggestions.

[0803] "Career suggestion" is a process that presents users with career options deemed most suitable based on their aptitude assessment results.

[0804] "Scout information" refers to data about employment opportunities and recruitment information that companies send to users.

[0805] This invention is an interactive vocational aptitude assessment system that combines natural language processing technology and an emotion analysis model to recognize the user's emotional state and provide optimal vocational suggestions. Specific embodiments are described below.

[0806] Users access the system using a device and input their profile information, skills, and interests. The device collects this information and transmits it to the server via a secure communication protocol. The server stores the input information in data storage and transfers it to a sentiment analysis model using natural language processing technology.

[0807] Emotion analysis models process input information to determine the user's emotional state. High-precision algorithms and machine learning models are used for this analysis. The resulting emotional state is then used as important data to further evaluate the user's suitability.

[0808] The server uses a generative AI model to generate career suggestions that are tailored to the user's emotions. This process involves creating messages that are sensitive to the user's feelings, designed to reduce stress. The generated career suggestions are aligned with the user's skills and interests.

[0809] The generated list of occupations is presented to the user via the terminal, and the user's response is monitored. The server uses this feedback to dynamically optimize the dialogue and evaluation process.

[0810] For example, if a user inputs "I'm interested in programming but I'm not confident," the sentiment analysis model will detect anxiety, and the generative AI model will suggest programming jobs and learning resources suitable for beginners.

[0811] Example prompt: "If a user inputs that they are interested in programming but lack confidence, explain how to generate appropriate career suggestions while providing reassurance."

[0812] Thus, the present invention provides a system that offers vocational aptitude assessment that takes into account the user's emotional state, thereby improving the user experience and increasing the accuracy of matching with companies.

[0813] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0814] Step 1:

[0815] Users access the vocational aptitude assessment system using their devices and enter their profile information, skills, and interests. This input is done through forms, and the collected data is sent to the server using a secure communication protocol. Specific examples of input include age, work experience, and areas of interest (e.g., data science, graphic design).

[0816] Step 2:

[0817] The server stores the received user input information in data storage. At this stage, the data entered is uniquely managed for each user. The stored data is used as foundational data for subsequent analysis processes.

[0818] Step 3:

[0819] The server uses natural language processing technology to pass stored user input information to an emotion analysis model. Here, the text data is analyzed, and the user's emotional state is determined. This analysis uses machine learning algorithms, for example, to extract emotional states based on emotional keywords such as "anxiety" and "excitement" contained in the input text. The output is the analyzed emotional state data.

[0820] Step 4:

[0821] The server generates job suggestions using a generative AI model based on the emotional state obtained through emotion analysis, as well as the user's skills and interests. This process creates job suggestions optimized for the user according to their emotional state. For example, if the user is identified as "anxious," job suggestions that provide a sense of security will be proposed. A list of suggested jobs is generated as output.

[0822] Step 5:

[0823] The server sends the generated list of occupations to the terminal and presents it to the user. The terminal displays the list of occupations to the user in an easy-to-understand interface. The user can refer to the presented list of occupations and consider them in light of their own interests and aptitudes.

[0824] Step 6:

[0825] The device records how the user reacts to the presented list of occupations and sends this feedback to the server. Based on this feedback data, the server dynamically optimizes the parameters of the generative AI model and the sentiment analysis model to improve the accuracy of future suggestions.

[0826] Step 7:

[0827] With the user's consent, the server makes the user's profile information public to relevant companies and prepares to receive recruitment information from companies in real time. This information is notified to the device, allowing the user to quickly understand the expected job opportunities.

[0828] (Application Example 2)

[0829] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0830] Traditional career aptitude systems have the problem of providing a uniform and inadequately optimized user experience because they do not take into account the user's emotional state. Furthermore, when users experience emotional anxiety regarding career choices, there is a lack of means to alleviate that anxiety and support them in making informed choices with greater confidence.

[0831] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0832] In this invention, the server includes means for receiving user input information and storing it in a database, means for analyzing the input information using natural language processing technology and evaluating the user's suitability, and means for analyzing the user's emotional state and adjusting the interaction according to that state. This makes it possible to provide optimal job suggestions that take the user's emotions into consideration and a richer user experience.

[0833] "User input information" refers to basic profile data, skills, interests, and other information that users provide to the system.

[0834] A "database" is an information management system used to temporarily or permanently store user input information.

[0835] "Natural language processing technology" refers to the technology that enables computers to understand, process, and generate human language.

[0836] "Means for evaluating user suitability" refers to methods and systems for determining a suitable occupation for a person based on the information they input.

[0837] "Means of suggesting occupations" refers to a function that suggests appropriate occupations to users based on evaluation results.

[0838] "Means for analyzing emotional states and adjusting interactions accordingly" refers to technologies that analyze a user's emotions in real time and dynamically change the user experience based on the results.

[0839] "External information sources" refer to internet and other information providers from which the system collects information such as recruitment information and market trends.

[0840] In the system implementing this invention, a server, a terminal, and a user work together in cooperation. The server is hosted on the cloud and is responsible for managing the information transmitted from the user's terminal. Users access the system using a smartphone or smart glasses and input the necessary information. This information includes basic profile data, skills, and interests.

[0841] The server is equipped with natural language processing technology and an emotion analysis engine. The natural language processing technology analyzes user input information and evaluates career suitability. The emotion analysis engine has the ability to analyze the user's emotional state in real time. This allows the system to recognize whether the user is anxious or at ease and adjust career suggestions based on the results.

[0842] Specifically, the server uses natural language processing technology to analyze user input data as soon as it receives it. Based on the analysis results, it suggests suitable occupations for the user. Meanwhile, an emotion analysis engine detects the user's emotional state, and if, for example, the user is feeling stressed, it presents suggestions for relaxation or encouraging messages.

[0843] Through their devices, users can view job information provided by the server, along with related success stories and recruitment status. Because they can obtain information about their chosen profession, they can make more specific and informed career choices. Furthermore, the server optimizes subsequent interactions based on how the user receives this information.

[0844] For example, if a user expresses excitement about a new profession, the emotion engine leverages this excitement, and the server presents positive success stories related to that profession. This process is performed in real time by an automated, dynamic system.

[0845] [Example of prompts for a generative AI model]

[0846] "Please provide the most relevant positive success stories, taking into account the emotional state of users when selecting an AA occupation."

[0847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0848] Step 1:

[0849] Users use their devices to send basic profile data, skills, and interest information to the system. The server receives this information and stores it in a database. The entered data is registered in the database for post-processing analysis.

[0850] Step 2:

[0851] The server uses natural language processing technology to analyze user input information stored in the database. This analysis incorporates the input information as structured data into a model to diagnose the user's aptitude. As a result, the most suitable occupational field for the user is identified.

[0852] Step 3:

[0853] The server uses an emotion analysis engine to analyze additional real-time data (such as voice and facial expressions) obtained from the user's device and evaluate the user's emotional state. Based on the input emotion data, it determines, for example, whether the user is feeling safe or anxious. Based on the analysis results, the interaction is adjusted appropriately according to the user's emotions.

[0854] Step 4:

[0855] The server suggests suitable occupations to the user based on the results of natural language processing and sentiment analysis. The suggestions are tailored to the user's emotional state and include relaxing occupational suggestions and positive success stories. The server dynamically generates these suggestions using a generative AI model.

[0856] Step 5:

[0857] The terminal displays job suggestions and related recruitment information received from the server to the user. The user can review this and delve further into the details and success stories of jobs that match their interests. The user's responses and choices are fed back into the next suggestions, optimizing the system's interaction.

[0858] Step 6:

[0859] Users can choose to share information about their preferred occupations with companies. Based on this choice, the server makes the user's profile data public to companies. This allows users to start receiving recruitment offers in real time.

[0860] Each step is designed to improve the user experience, including examples of prompts for the generative AI model.

[0861] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0862] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0863] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0864] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0865] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0866] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0867] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0868] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0869] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0870] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0871] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0872] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0873] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0874] 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.

[0875] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0876] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0877] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0878] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0879] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0880] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0881] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0882] The following is further disclosed regarding the embodiments described above.

[0883] (Claim 1)

[0884] A means for receiving user input information and storing said information in a database,

[0885] A means for analyzing the input information using natural language processing technology and evaluating the user's suitability,

[0886] Based on the aforementioned evaluation results, a means for suggesting suitable occupations to the user,

[0887] A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, further comprising means for providing the user with information on successful cases for the aforementioned occupations.

[0891] (Claim 3)

[0892] The system according to claim 1, further comprising means for disclosing the user's information to a company and receiving recruitment information based on the user's approval.

[0893] "Example 1"

[0894] (Claim 1)

[0895] A means for receiving information from a user's terminal and storing the said information in a storage device,

[0896] A means for analyzing the input information using natural language processing technology and evaluating the user's suitability,

[0897] A means for presenting suitable occupations to the user based on the evaluation results using a generative AI model,

[0898] A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources,

[0899] With the user's permission, a means for disclosing the user's information and receiving the information,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, further comprising means for providing the user with case information regarding the aforementioned presented occupation.

[0903] (Claim 3)

[0904] The system according to claim 1, further comprising means for including dynamically generated interactive suggestions based on user input.

[0905] "Application Example 1"

[0906] (Claim 1)

[0907] A means for receiving user input information and storing said information in a database,

[0908] A means for analyzing the input information using natural language processing technology and evaluating the user's suitability,

[0909] Based on the aforementioned evaluation results, a means for suggesting suitable occupations to the user,

[0910] A means of providing information on career paths and skill acquisition related to the aforementioned occupations,

[0911] A means that allows visitors to take a career aptitude test using a terminal installed in the store,

[0912] A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, further comprising means for providing the user with information on successful cases for the aforementioned occupations.

[0916] (Claim 3)

[0917] The system according to claim 1, further comprising means for disclosing the user's information to an organization and receiving scouting information based on the user's approval.

[0918] "Example 2 of combining an emotion engine"

[0919] (Claim 1)

[0920] A means for receiving user input information and storing said information in data storage,

[0921] A means of determining a user's emotional state using an emotion analysis model with natural language processing technology,

[0922] A means for analyzing the aforementioned input information and emotional state to evaluate the user's suitability,

[0923] A means for generating job suggestions that respond to the user's emotions using a generative AI model, and for presenting suitable jobs to the user based on the evaluation results,

[0924] A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources,

[0925] A means of monitoring user responses and dynamically optimizing the dialogue content and evaluation process through feedback,

[0926] A system that includes this.

[0927] (Claim 2)

[0928] The system according to claim 1, further comprising means for providing the user with reassuring success story information about the presented occupation, based on the user's emotional state.

[0929] (Claim 3)

[0930] The system according to claim 1, further comprising means for disclosing the user's information to an organization based on the user's consent and receiving scout information in real time.

[0931] "Application example 2 when combining with an emotional engine"

[0932] (Claim 1)

[0933] A means for receiving user input information and storing said information in a database,

[0934] A means for analyzing the input information using natural language processing technology and evaluating the user's suitability,

[0935] Based on the aforementioned evaluation results, a means for suggesting suitable occupations to the user,

[0936] A means for analyzing the user's emotional state and adjusting the interaction according to the said emotional state,

[0937] A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources,

[0938] A system that includes this.

[0939] (Claim 2)

[0940] The system according to claim 1, further comprising means for providing the user with information on successful cases for the aforementioned occupations.

[0941] (Claim 3)

[0942] The system according to claim 1, further comprising means for disclosing the user's information to a company and receiving recruitment information based on the user's approval. [Explanation of Symbols]

[0943] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving user input information and storing said information in a database, A means for analyzing the input information using natural language processing technology and evaluating the user's suitability, Based on the aforementioned evaluation results, a means for suggesting suitable occupations to the user, A means of obtaining the recruitment status of the aforementioned suitable occupation from external sources, A system that includes this.

2. The system according to claim 1, further comprising means for providing the user with information on successful cases for the aforementioned occupations.

3. The system according to claim 1, further comprising means for disclosing the user's information to a company and receiving recruitment information based on the user's approval.

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