system

Abstract

Provide a system. A means for collecting information input by a user; means for transmitting the collected user information to a server; A means for analyzing the user information received by the server using a generative AI model; A means for transmitting the analysis results of the generative AI model from the server to the terminal; means for displaying the transmitted analysis results to the user by the terminal; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditionally, when children and young people decide on their future career paths, they often rely on limited information from their parents and teachers, making it difficult to receive a wide range of career options or specific advice tailored to their individual characteristics. There is also the psychological barrier of not being able to speak honestly with parents or teachers. This can lead to students choosing a career path they may regret in the future. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides a system that collects user information, analyzes it using a generative AI model, and suggests optimal career paths and occupations. The system of the present invention includes the following means.

[0006] a means for collecting user-entered information;

[0007] means for transmitting the collected user information to a server;

[0008] A means for analyzing the user information received by the server using a generative AI model;

[0009] A means for transmitting the analysis results of the generative AI model from the server to the terminal;

[0010] means for displaying the transmitted analysis results to the user by the terminal;

[0011] It is a system including:

[0012] Furthermore, the generative AI model uses user information to diagnose personality and suggest future careers. The analysis results are displayed as concrete images and video links, allowing users to understand their future career paths more concretely and visually. In this way, by suggesting optimal career paths and occupations from a wide range of information, this system provides an environment where users can easily consult with the system, helping them make career choices they will not regret.

[0013] "User information" refers to information such as personal characteristics, hobbies, likes and dislikes, future aspirations, desired place to live, family environment, friendships, etc. that a user inputs into the system.

[0014] "Collection means" refers to the means for inputting and recording user information through an interface.

[0015] The "transmission means" is a means for transmitting collected user information to the server.

[0016] A "server" is a computer system that receives user information and analyzes it using a generative AI model.

[0017] A "generative AI model" is an artificial intelligence algorithm that automatically performs personality assessments and suggests careers based on user information.

[0018] "Analysis means" refers to a means for analyzing user information using a generative AI model and generating results.

[0019] "Analysis results" refers to information obtained as a result of analysis by the generative AI model, and includes personality assessments and suggestions for suitable careers.

[0020] The "display means" is a means for visually conveying the analysis results to the user on the terminal.

[0021] "Image and video links" are media formats used to concretely and visually present analysis results. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0023] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0024] First, the terms used in the following description will be explained.

[0025] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0026] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0027] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0028] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0029] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0033] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0034] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0035] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0036] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0037] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0040] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0041] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0042] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0043] This invention relates to a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. Below, we will explain each component of the system and how they work together.

[0044] Collection and transmission of user information

[0045] Device:

[0046] The terminal provides an interface that users can access, and users input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, friendships, etc. This information is collected as user information and sent to the server.

[0047] For example, suppose User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends." This information is saved on the device and immediately sent to the server.

[0048] Data reception and analysis

[0049] server:

[0050] The server receives the user information sent from the device and analyzes it using a generative AI model. The generative AI model performs a personality diagnosis based on the user's characteristics and suggests suitable occupations and future career paths for the user.

[0051] For example, the server receives information about user A, analyzes that "communication skills" are a strength, and suggests suitable jobs such as "teacher" or "consultant."

[0052] Sending analysis results

[0053] server:

[0054] The server sends the analysis results of the generative AI model to the user's device, which include an overview of the user's strengths, suitable occupations, and personality assessment.

[0055] Displaying analysis results

[0056] Device:

[0057] The device receives the analysis results from the server and displays them to the user, including specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0058] For example, user A receives advice through his device such as, "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please see this link: https: / / example.com / video."

[0059] Specific examples

[0060] As a concrete example, suppose User B enters the following information:

[0061] Hobbies: Listening to music

[0062] Favorite subject: Music

[0063] Least Favorite Subject: Physical Education

[0064] What I want to do in the future: Become a music producer

[0065] Where I want to live: Urban area

[0066] Family environment: Only child

[0067] Current friendships: I have a few close friends

[0068] The server receives this information, and the generative AI model analyzes it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, it suggests "music producer" or "music teacher." The analysis results are sent to User B's device along with images and video links, and User B receives advice such as, "Your strength is creativity. A music producer or music teacher would be suitable occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0069] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0070] The processing flow will be explained below.

[0071] Step 1: User enters information

[0072] Users access the device interface and enter information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, friendships, etc. This is user information.

[0073] Step 2: Collect user information

[0074] The terminal temporarily stores the information entered by the user, which is used for subsequent processing.

[0075] Step 3: Submit user information

[0076] The device sends the collected user information to the server, for example, using an HTTP POST request.

[0077] Step 4: Receiving data on the server

[0078] The server receives the user information sent from the device and stores the received data for analysis.

[0079] Step 5: Analysis by generative AI model

[0080] The server inputs the received user information into the generative AI model, which then uses this information to diagnose the user's personality and suggest careers.

[0081] Step 6: Generate analysis results

[0082] The server compiles the analysis results obtained from the generative AI model, including the user's strengths, recommended occupations, and occupation details.

[0083] Step 7: Submitting the analysis results

[0084] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0085] Step 8: Viewing the analysis results

[0086] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0087] Step 9: User Feedback

[0088] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0089] Example 1

[0090] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0091] In today's world, there is a strong demand for systems that suggest optimal careers and paths for individual users. However, conventional systems have struggled to provide comprehensive and accurate results in the collection, analysis, and proposal of user information. For example, problems exist such as insufficient analysis of individually input information or generalized proposals. A system that can solve these problems and support users in making appropriate and satisfactory career choices is needed.

[0092] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0093] In this invention, the server includes means for providing an interface accessible to the user and inputting information, means for transmitting collected user information to the server, means for the server to store the received user information in a database, means for the server to analyze the user information using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, and means for the terminal to display the transmitted analysis results to the user. This makes it possible to accurately analyze user information and make suggestions in a specific and visually easy-to-understand format.

[0094] A "user-accessible interface" is any form or screen that a user can use to enter information.

[0095] "Means for inputting information" refers to a function that allows users to collect information such as their hobbies and special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their family environment, and friendships.

[0096] "Means for sending to the server" refers to the communication protocol and network functions for sending collected user information to the server.

[0097] "Means for storing in a database" refers to a database or storage system for temporarily or permanently storing the user information received by the server.

[0098] A "generative AI model" is an artificial intelligence model that analyzes user information and uses that information to make personality diagnoses and career suggestions.

[0099] The "means of analysis" is a processing function that uses a generative AI model to analyze user information and derive results.

[0100] "Means for transmitting to the terminal" refers to the communication protocols and network functions for transmitting the analysis results obtained by the generative AI model to the user's terminal.

[0101] "Means for displaying to the user" refers to a screen or interface for presenting the analysis results received by the terminal to the user.

[0102] "Personality diagnosis" refers to analyzing a user's characteristics and personality based on information entered by the user and providing the results.

[0103] "Means to suggest future careers" is a function that suggests suitable careers and career paths for users based on analysis by a generative AI model.

[0104] "Means for displaying specific images and video links" refers to a function that displays the results of the analysis in a format that includes related images and video links in order to communicate the results to the user in an easy-to-understand manner.

[0105] The present invention is a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. This system uses a user-accessible interface, a server, a generative AI model, a database, a communication protocol, and a display terminal.

[0106] First, the device provides the user with an interface for inputting information. The user inputs information on the device screen, such as their hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and their friendships. This interface can be realized as a web application or a mobile application.

[0107] The entered information is then collected by the terminal and sent to a server in real time using a communication protocol such as HTTP or HTTPS. The server stores the received user information in a database, which can be a relational database such as MySQL (registered trademark) or PostgreSQL.

[0108] The server performs analysis using a generative AI model based on the saved user information. This generative AI model may utilize existing generative AI technology such as OpenAI's GPT-3. Analysis begins by inputting a prompt statement to the model. The following is an example of a prompt statement:

[0109] Based on your user information, we will suggest the best career path for you. Enter the following user information:

[0110] Hobbies: Listening to music

[0111] Favorite subject: Music

[0112] Least Favorite Subject: Physical Education

[0113] What I want to do in the future: Become a music producer

[0114] Where I want to live: Urban area

[0115] Family environment: Only child

[0116] Current friendships: I have a few close friends

[0117] Based on the user's information, the generative AI model analyzes the user's characteristics and strengths and suggests suitable occupations and future paths. The analysis results include an overview of the user's strengths, suitable occupations, and personality assessment.

[0118] The server sends the analysis results obtained by the generative AI model to the user's device. For example, the result might be, "Your strength is creativity. A suitable career would be a music producer or music teacher. For more information, please see this link: https: / / example.com / music_video."

[0119] Finally, the device displays the analysis results received from the server to the user. At this time, the analysis results are displayed including concrete images and video links, so the user can obtain information in a visually easy-to-understand format.

[0120] For example, if User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the generative AI model will analyze this information, determine that "communication skills are a strength," and suggest jobs like "teacher" or "consultant." The server sends this result to the device, which then displays it to the user as "Your strength is communication skills. Suitable occupations are teacher or consultant. For more information, please see this link: https: / / example.com / video."

[0121] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] The terminal provides the user with an interface for inputting information, such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0125] Input: Personal information entered by the user on the device (e.g., "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math").

[0126] Output: A dataset of the input user information.

[0127] Specific behavior:

[0128] User A enters "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math" into the input form displayed on the device screen. When the user presses the "Send" button, the information is temporarily saved on the device.

[0129] Step 2:

[0130] The device sends the collected user information to the server using a communication protocol such as HTTP / HTTPS.

[0131] Input: User information stored on the device.

[0132] Output: The user information sent to the server.

[0133] Specific behavior:

[0134] After the information entered by User A is temporarily saved on the device, the device immediately sends the information to the server, which receives the data using the HTTPS protocol.

[0135] Step 3:

[0136] The server stores the received user information in a database, where the data is processed and stored as needed.

[0137] Input: User information received by the server.

[0138] Output: User information stored in the database.

[0139] Specific behavior:

[0140] The server receives User A's information (hobbies, favorite subjects, least favorite subjects, etc.) and stores it in the database as "User A: Hobbies are reading, favorite subject is Japanese, least favorite subject is math." This makes it available for use in later steps.

[0141] Step 4:

[0142] The server uses the generative AI model to analyze the stored user information, which includes creating prompt sentences and inputting them into the AI ​​model.

[0143] Input: User information stored in the database.

[0144] Output: Analysis results from the generative AI model.

[0145] Specific behavior:

[0146] The server generates the following prompt and inputs it into the generative AI model: "Based on the information about user A, please suggest the most suitable occupation or career path. The following user information is entered: hobby is reading, favorite subject is Japanese, least favorite subject is math, and wants to live abroad in the future." Based on this, the generative AI model obtains the result that "communication skills are a strength," and suggests "teacher" or "consultant."

[0147] Step 5:

[0148] The server transmits the generated analysis results to the user's terminal.

[0149] Input: Analysis results from the generative AI model.

[0150] Output: Analysis results sent to the device.

[0151] Specific behavior:

[0152] The analysis results provided by the generative AI model (communication skills are a strength, and suitable occupations are teaching or consulting) are compiled on a server and sent to the device using the HTTPS protocol.

[0153] Step 6:

[0154] The device displays the analysis results received from the server to the user, including specific images and video links.

[0155] Input: Analysis results received from the server.

[0156] Output: Analysis results displayed to the user.

[0157] Specific behavior:

[0158] The analysis result will be displayed on User A's device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please refer to this link: https: / / example.com / video." User A can click the link to visually check the detailed information.

[0159] Through these steps, user information is collected, analyzed using a generative AI model, and a system is created that suggests optimal occupations and career paths.

[0160] (Application example 1)

[0161] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0162] Conventional career and career suggestion systems have the problem that detailed face-to-face counseling is difficult because the process of collecting and analyzing user information is carried out only online. If the consultation environment in a physical store is insufficient, it may be difficult for users to fully understand the content of the suggestions, making it difficult to make an appropriate decision. Another issue is that the provision of additional information is limited, making it difficult for users to concretely imagine the career or career path that is best suited to them.

[0163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0164] In this invention, the server includes means for collecting information entered by the user, means for transmitting the collected user information to the server, means for analyzing using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, means for the terminal to display the analysis results transmitted to the user, means for the terminal to display the analysis results transmitted on a guidance device in the physical store, means for using a robot in the physical store to input user information and display the analysis results, and means for providing additional information in a dedicated consultation booth or at a terminal. This enables detailed face-to-face counseling and allows users to specifically understand the occupations and career paths that are best suited to them.

[0165] "Information gathering means" refers to a means of providing an interface that users can access and input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0166] The "means for transmitting to the server" is a communication means for transmitting the collected user information to the server.

[0167] The "analysis means" is a means for analyzing the user information received by the server using a generative AI model.

[0168] The "means for transmitting analysis results by the generative AI model" is a means for transmitting analysis results by the generative AI model from the server to the terminal.

[0169] The "analysis result display means" is a means for visually displaying the analysis results transmitted by the terminal to the user.

[0170] The "guide device display means" is a means for displaying the analysis results sent by the terminal on a guide device in a physical store.

[0171] The "user information input means and analysis result display means" refers to a means for inputting user information using a robot in a physical store and displaying the analysis results.

[0172] "Means for providing additional information" refers to means for providing detailed information at dedicated consultation booths or terminals.

[0173] This invention provides a system that collects information entered by users, analyzes it, and suggests optimal occupations and career paths. The system uses robots and terminals for users to enter information in physical stores, and transmits the collected data to a server. The system then analyzes the results using a generative AI model and displays them on information displays and terminals in the physical stores, providing detailed information to users face-to-face.

[0174] Hardware and software used

[0175] Hardware: In-store guide robot, user tablet, server

[0176] Software: Server with API endpoint, Python script, generative AI model

[0177] Data collection

[0178] Users use a robot or tablet device in a physical store to input information about themselves, such as hobbies, favorite subjects, least favorite subjects, future goals, where they want to live, their home environment, and friendships. This allows the system to collect specific information about the user's characteristics and wishes.

[0179] Data transmission and analysis

[0180] The collected user information is sent to the server in real time. Here, the data is sent to the server as a POST request using Python's requests library. The server inputs the received data into a generative AI model to analyze the optimal occupation and career path.

[0181] Displaying analysis results

[0182] When the server returns the analysis results from the generated AI model, the results are returned to the client (robot or tablet device) in JSON format. The analysis results include suitable occupations, the user's strengths, and a summary of their personality. The device visually displays these results to the user. In addition, in-store guide devices and robots present detailed information and related content (images, video links, etc.) to help users understand the situation more concretely.

[0183] Specific examples

[0184] For example, if a user enters the following information:

[0185] Hobbies: Photography

[0186] Favorite subject: Art

[0187] Least Favorite Subject: Physics

[0188] What I want to do in the future: Become a professional photographer

[0189] Where I want to live: Local area

[0190] Family: Large family

[0191] Friendships: A few very close friends

[0192] When this information is input into a generative AI model, it analyzes it and concludes that "creativity is a strength, and a career such as professional photography or commercial photography would be suitable." The analysis result is displayed as "Your strength is creativity. A suitable career would be professional photography or commercial photography. For more information, please see this link: https: / / example.com / photo_career."

[0193] As described above, this invention uses a generative AI model to analyze user information and propose occupations and career paths in a concrete and visually easy-to-understand format, making it easier for users to make appropriate decisions. In addition, by providing a consultation environment in a physical store, detailed face-to-face counseling is possible.

[0194] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0195] Step 1:

[0196] Users input their information using a robot or tablet device in a physical store. The input information includes hobbies, favorite subjects, least favorite subjects, future goals, desired place to live, family environment, friendships, etc. This information is saved on the device. Input data includes "hobbies: photography," "favorite subject: art," "least favorite subject: physics," etc., and the collected data is sent to a server in real time.

[0197] Step 2:

[0198] The collected user information is sent from the device to the server. The server receives it in POST format using the Python requests library. The input data is the information the user entered earlier. The server then inputs the received data into a generative AI model ready for analysis.

[0199] Step 3:

[0200] The server has the generative AI model analyze the input data. The generative AI model analyzes the data based on the prompt. This analysis identifies the user's strengths and suitable occupations. For example, it may determine that "creativity is a strength, so professional photography or advertising photography would be suitable." The results of this data calculation are output in JSON format.

[0201] Step 4:

[0202] The server sends the analysis results of the generative AI model in JSON format to the device. The data sent includes career suggestions based on the analysis results and information about the user's strengths. Specifically, it includes information such as, "Your strength is creativity. A suitable career would be professional photography or advertising photography."

[0203] Step 5:

[0204] The device receives the analysis results from the server and displays them to the user. The analysis results are displayed as the user's strengths, suitable careers, and even specific images and video links. For example, the link might include "More information here: https: / / example.com / photo_career."

[0205] Step 6:

[0206] The in-store guidance device visually displays the analysis results to the user, allowing the user to obtain more specific and detailed information. This display is linked to the user's device to provide detailed images and videos.

[0207] Step 7:

[0208] Dedicated consultation booths and terminals provide additional information to users, who can receive detailed counseling and learn more about specific career plans and future goals based on the analysis results.

[0209] Through these steps, the system supports users in choosing the right occupation or career path, and provides an environment where users can receive face-to-face counseling in a physical store.

[0210] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0211] This invention combines a system that collects user information, analyzes it using a generative AI model, and suggests optimal career paths and occupations with an emotion engine that recognizes the user's emotions. This system makes it possible to suggest personalized career paths and occupations that take the user's emotional aspects into consideration. Below, we will explain each component of the system and how they work together.

[0212] Collection and transmission of user information and emotional data

[0213] Device:

[0214] The device provides an interface that users can access, and allows them to input information such as their hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, and their friendships. The device also has a built-in emotion engine that collects emotional data from the user's facial expressions and voice. The information collected in this way is sent to the server as user information.

[0215] For example, User A might enter, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," and the emotion engine would then recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0216] Data reception and analysis

[0217] server:

[0218] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotion engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotion engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state.

[0219] For example, the server receives information about user A and analyzes that "communication skills are his strengths, and a career as a teacher or consultant would be suitable," and also reads from his emotional data that user A is in a relaxed state. Taking this information into consideration, the server generates appropriate advice.

[0220] Sending analysis results

[0221] server:

[0222] The server sends the analysis results of the generative AI model and emotion engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0223] Displaying analysis results

[0224] Device:

[0225] The device receives the analysis results from the server and displays them to the user. The analysis results include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0226] For example, user A might see the following message on their device: "Your strength is communication skills. A suitable career would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0227] Specific examples

[0228] As a concrete example, suppose User B enters the following information:

[0229] Hobbies: Listening to music

[0230] Favorite subject: Music

[0231] Least Favorite Subject: Physical Education

[0232] What I want to do in the future: Become a music producer

[0233] Where I want to live: Urban area

[0234] Family environment: Only child

[0235] Current friendships: I have a few close friends

[0236] The emotion engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0237] In this way, the system of the present invention uses a generative AI model and emotion engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[0238] The processing flow will be explained below.

[0239] Step 1: User enters information

[0240] Users access the device's interface and input information such as hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, friendships, etc. The device's built-in emotion engine also recognizes the user's emotions in real time from their facial expressions and voice and collects them as data.

[0241] Step 2: Collect user information and sentiment data

[0242] The device temporarily stores the information entered by the user and the emotional data collected by the emotion engine, which is then used in subsequent processing.

[0243] Step 3: Sending user information and emotion data

[0244] The device sends the collected user information and emotion data to the server, for example, using an HTTP POST request.

[0245] Step 4: Receiving data on the server

[0246] The server receives the user information and emotion data sent from the device, and stores the received data for analysis.

[0247] Step 5: Analysis by generative AI models and emotion engines

[0248] The server inputs the received user information into a generative AI model to perform personality assessment and career suggestions, and also uses an emotion engine to analyze the user's emotional data and perform additional personalized analysis based on the user's emotional state.

[0249] Step 6: Generate analysis results

[0250] The server combines the analysis results from the generative AI model with the emotion data from the emotion engine to generate final advice for the user, including the user's strengths, recommended occupations, a personality summary, and advice based on the user's emotions.

[0251] Step 7: Submitting the analysis results

[0252] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0253] Step 8: Viewing the analysis results

[0254] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0255] Step 9: User Feedback

[0256] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0257] Example 2

[0258] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0259] Conventional career and occupation suggestion systems only considered the user's personality and aptitude, ignoring emotional aspects, which resulted in suggestions that were inappropriate for some users. Furthermore, the suggested results were difficult to visually understand, resulting in low user understanding and satisfaction. Furthermore, there were limited methods for improving the accuracy of the information entered by users and their motivation.

[0260] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0261] In this invention, the server includes means for collecting information and emotional data input by the user, means for transmitting the collected user information and emotional data to the server, means for analyzing the user information and emotional data received by the server using a generative AI model and an emotional analysis engine, means for transmitting the analysis results by the generative AI model and the emotional analysis engine from the server to the terminal, and means for the terminal to visually display the analysis results sent to the user. This enables personalized career and occupation suggestions that take the user's emotional aspects into consideration, and by displaying the suggestion results in a visually easy-to-understand manner, it is possible to improve the user's understanding and satisfaction.

[0262] "User" refers to an individual who uses the system or who inputs information and receives analysis results.

[0263] "Information" includes data entered by the user, such as hobbies, special skills, favorite subjects, least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0264] "Emotion data" is information about the emotional state collected from the user's facial expressions and voice.

[0265] "Server" refers to a central computer system that receives user information and emotion data, analyzes it using a generative AI model and emotion analysis engine, and transmits the results to the device.

[0266] "Terminal" refers to a device for users to input information and a device for displaying analysis results, and specifically includes smartphones, PCs, tablets, etc.

[0267] "Means for collection" refers to the functions and devices that allow a terminal to input or acquire user information and emotion data.

[0268] "Means for transmitting" refers to the means for transmitting user information and emotion data collected by the terminal to the server, as well as the functions and technologies for transmitting the analysis results generated by the server to the terminal.

[0269] "Means of analysis" refers to the functions and algorithms that analyze the user information and emotional data received by the server using a generative AI model and an emotion analysis engine.

[0270] A "generative AI model" refers to an artificial intelligence model that performs personality diagnosis and career suggestions based on user information.

[0271] An "emotion analysis engine" refers to a system that analyzes emotional data from a user's facial expressions and voice and identifies the user's emotional state.

[0272] "Display means" refers to the functions and technologies that allow the terminal to visually present the analysis results to the user.

[0273] "Visually displaying" means providing the analysis results to the user in a form that is intuitively easy to understand, and includes forms such as text information, images, and video links.

[0274] This invention is a system that collects user information and emotional data, analyzes it using a generative AI model and an emotional analysis engine, and then suggests optimal career paths and occupations. This system makes it possible to suggest personalized career paths and occupations that also take into account the user's emotional aspects. This section describes in detail each component of the system and how they work together.

[0275] Collection and transmission of user information and emotional data

[0276] Terminal

[0277] The device provides an interface accessible to users, through which they input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and their friendships. The device also incorporates an emotion engine that collects emotional data from the user's facial expressions and voice. This collected information is then sent to the server as user information. For example, if User A inputs, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the emotion engine will recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0278] Data reception and analysis

[0279] server

[0280] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotional analysis engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotional analysis engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state. As a concrete example, the server receives information about User A and analyzes that "communication skills are his strengths and that teaching or consulting would be suitable occupations," while also reading from the emotional data that User A is in a relaxed state. Taking this information into consideration, appropriate advice is generated.

[0281] Sending analysis results

[0282] server

[0283] The server sends the analysis results from the generative AI model and the emotion analysis engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0284] Displaying analysis results

[0285] Terminal

[0286] The device displays the analysis results received from the server to the user. The analysis results also include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format. For example, user A might see the following message on his device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0287] Specific examples

[0288] As a concrete example, suppose User B enters the following information:

[0289] Hobbies: Listening to music

[0290] Favorite subject: Music

[0291] Least Favorite Subject: Physical Education

[0292] What I want to do in the future: Become a music producer

[0293] Where I want to live: Urban area

[0294] Family environment: Only child

[0295] Current friendships: I have a few close friends

[0296] The emotion analysis engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion analysis engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable for you." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0297] In this way, the system of the present invention uses a generative AI model and an emotion analysis engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[0298] Prompt Sentence Examples

[0299] "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I would like to live abroad in the future, I would like to live in an urban area, I get along well with my siblings at home, and I currently have many friends. Based on this, please suggest a suitable occupation or career path."

[0300] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0301] Step 1:

[0302] The device collects information entered by the user. The input information includes the user's hobbies and special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and friendships. After the user has completed their input, the device temporarily stores it. For example, if the user inputs "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the information will be temporarily stored.

[0303] Step 2:

[0304] The device uses an emotion engine to collect user emotional data. It uses a camera and microphone as input to collect the user's facial expressions and voice. For example, the camera detects whether the user is smiling, and the microphone analyzes the tone and speed of the voice. Based on this, emotional data such as whether the user is relaxed or excited is collected.

[0305] Step 3:

[0306] The device transmits the collected user information and emotional data to the server. The input includes user information and emotional data, and the integrated data is transmitted to the server as output. For example, data such as "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends" and "I feel relaxed" are transmitted.

[0307] Step 4:

[0308] The server receives user information and emotion data sent from the device. It takes user information and emotion data as input and prepares them for analysis as output. Specifically, it stores the received data in a database and passes it to the analysis engine.

[0309] Step 5:

[0310] The server analyzes user information using a generative AI model. The input includes user information (hobbies, favorite subjects, least favorite subjects, etc.), and the output generates a personality assessment result for the user and suggestions for suitable careers. For example, if the result is "good communication skills," "teacher" or "consultant" will be suggested.

[0311] Step 6:

[0312] The server analyzes the emotional data using an emotion analysis engine. The input includes the collected emotional data, and the output generates advice based on the user's emotional state. For example, if the user is "relaxed," advice to maintain that state is provided.

[0313] Step 7:

[0314] The server combines the analysis results of the generative AI model and the emotion analysis engine to generate the final analysis result. The input includes the personality assessment results, suitable career suggestions, and emotion-based advice, and the output is a report that integrates these. For example, the report may say, "Your strength is communication skills. Suitable careers are teaching or consulting. A relaxed state will be beneficial for these suggestions."

[0315] Step 8:

[0316] The server sends the generated analysis results to the user's device. The final analysis results are included as input, and the results are sent to the device as output. For example, the result sent to the device might be, "Your strength is communication skills. Suitable occupations are teaching or consulting. A relaxed state will be beneficial for this suggestion."

[0317] Step 9:

[0318] The device displays the analysis results received from the server to the user. The input contains the final analysis results, and the output displays them visually. Specifically, text information, images, video links, etc. are displayed. For example, it might say, "Your strength is communication skills. Suitable occupations are teaching or consulting. For more information, please refer to this link: https: / / example.com / video."

[0319] (Application example 2)

[0320] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] Conventional systems only provide analysis results based on user input, making it difficult to provide personalized recommendations that match the user's emotions and preferences. Furthermore, these systems are limited in their ability to improve the user experience, and online shopping sites, in particular, lack the means to efficiently recommend the most suitable products for each user. As a result, users' purchasing motivation cannot be fully stimulated, resulting in a decrease in satisfaction and lost purchasing opportunities.

[0322] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user information and emotion data, means for analyzing the collected user information and emotion data, and means for generating personalized proposals based on the analysis results. This enables personalized product proposals that take into account the user's preferences and emotions.

[0323] "User information" refers to data entered by the user, such as hobbies, special skills, preferred types, desired product categories, colors, styles, etc.

[0324] "Emotion data" refers to data relating to the user's emotional state, such as excitement or relaxation, obtained from the user's facial expressions and voice.

[0325] The term "server" refers to a computer system that receives and analyzes user information and emotion data, and includes a processing device, a storage device, a communication device, and the like for performing specific analytical processing.

[0326] "Terminal" refers to a device that provides an interface for a user to access and a device that displays the analysis results sent from the server.

[0327] A "generative AI model" refers to an artificial intelligence model that analyzes collected user information to diagnose personality and suggest future careers and products.

[0328] An "emotion engine" refers to a system that recognizes emotions from a user's facial expressions and voice data and generates data corresponding to that emotional state.

[0329] "Personalized suggestions" means suggesting the most suitable products or occupations based on the user's individual preferences and emotional state.

[0330] "Image and video links" refers to media links and visual information that provide information in a form that is visually easy for users to understand.

[0331] The present invention is a system that collects user information and emotional data, analyzes them using a generative AI model, and makes optimal product or career recommendations. This system also takes into account the user's emotional state, allowing for more personalized recommendations.

[0332] Program and system configuration

[0333] The system mainly consists of a user's device and a server. The device is a device such as a smartphone, smart glasses, or head-mounted display, and uses a camera and microphone to collect the user's facial expression and voice data. Based on this data, the user's information and emotional data are collected. The device also provides an interface for inputting information such as the user's hobbies and skills, preferred type, desired product category, color, and style.

[0334] 1. Collecting user information and sentiment data:

[0335] Users collect facial expression data through the camera on their smartphone or smart glasses, and collect voice data using a microphone.

[0336] Using this data, an emotion engine (e.g., EmotionRecognizer) analyzes the user's emotional state.

[0337] 2. Data transmission:

[0338] The collected user information and emotion data are transmitted from the terminal to a server.

[0339] 3. Data analysis on the server:

[0340] Based on the received data, the server analyzes the user's preferences and emotional state using a generative AI model (e.g., RecommendationEngine).

[0341] Based on the analysis results, the server suggests the most suitable product or occupation to the user.

[0342] 4. Displaying the proposed results:

[0343] The analysis results sent from the server are displayed on the terminal.

[0344] The proposed results include concrete images and video links, and are displayed in a way that is easy for users to understand visually.

[0345] For example, if User C enters the following information:

[0346] Hobbies: Fashion

[0347] Favorite color: Blue

[0348] Category of product you want:Outerwear

[0349] Facial expression data: excited

[0350] Based on this user information and emotional data, the generative AI model and emotion engine perform analysis and make optimal product recommendations. User C is recommended a "blue trench coat," offering a stylish design that suits their current excited mood. Detailed information and a purchase link are also provided, displaying a message such as "Click here for more details" (e.g., https: / / example.com / outerwear).

[0351] Example prompt sentence:

[0352] User information: Hobbies are fashion, favorite color is blue, desired product category is outerwear

[0353] Facial expression data: excited

[0354] Based on the analysis results, we will propose the most suitable product.

[0355] This system will be able to appropriately consider the user's preferences and emotions and make optimal product and occupation suggestions, which is expected to improve user satisfaction and stimulate purchasing motivation.

[0356] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0357] Step 1:

[0358] Users input information such as hobbies, special skills, preferred types, desired product categories, colors, and styles. Furthermore, facial expression data is collected using the camera on a smartphone or smart glasses, and voice data is collected using a microphone. The input information and emotional data are temporarily stored on the device.

[0359] Input: Hobbies, special skills, preferred type, desired product category, color, style, facial expression data, voice data

[0360] Output: Temporarily saved user information and emotion data

[0361] Step 2:

[0362] The device sends the user information and emotion data collected and saved in step 1 to the server. The transmitted data is encrypted and handled securely.

[0363] Input: Temporarily saved user information and emotional data

[0364] Output: User information and emotion data sent to the server

[0365] Step 3:

[0366] The server analyzes the received user information and emotional data. First, it uses an emotion engine to analyze facial expression and voice data to recognize the user's emotional state. Then, it uses a generative AI model to perform analysis based on the user's preferences and emotional state.

[0367] Input: User information and emotion data sent to the server

[0368] Output: Analyzed user preference and emotional state data

[0369] Step 4:

[0370] The server then generates optimal product or job suggestions based on the analyzed data, including specific images and video links.

[0371] Input: Parsed user preference and emotional state data

[0372] Output: Generated product or job proposal data (including specific images and video links)

[0373] Step 5:

[0374] The server generates and sends the proposed data to the device, which is personalized to the user in real time.

[0375] Input: Generated product or occupation proposal data

[0376] Output: Proposal data sent to the device

[0377] Step 6:

[0378] The device receives the proposed data sent from the server and displays it to the user, who can visually confirm the images and video links and obtain more detailed information.

[0379] Input: Proposal data sent to the device

[0380] Output: The proposal data displayed to the user (including images and video links)

[0381] As a concrete example, when User C inputs information such as his hobbies, special skills, and preferences and collects emotional data, the server analyzes the data using a generative AI model and an emotion engine to generate a blue trench coat recommendation. This recommendation includes a link to more details, which User C can visually check on his device.

[0382] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0383] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0384] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0385] [Second embodiment]

[0386] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0387] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0388] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0389] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0390] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0391] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0392] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0393] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0394] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0395] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0396] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0397] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0398] This invention relates to a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. Below, we will explain each component of the system and how they work together.

[0399] Collection and transmission of user information

[0400] Device:

[0401] The terminal provides an interface that users can access, and users input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, friendships, etc. This information is collected as user information and sent to the server.

[0402] For example, suppose User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends." This information is saved on the device and immediately sent to the server.

[0403] Data reception and analysis

[0404] server:

[0405] The server receives the user information sent from the device and analyzes it using a generative AI model. The generative AI model performs a personality diagnosis based on the user's characteristics and suggests suitable occupations and future career paths for the user.

[0406] For example, the server receives information about user A, analyzes that "communication skills" are a strength, and suggests suitable jobs such as "teacher" or "consultant."

[0407] Sending analysis results

[0408] server:

[0409] The server sends the analysis results of the generative AI model to the user's device, which include an overview of the user's strengths, suitable occupations, and personality assessment.

[0410] Displaying analysis results

[0411] Device:

[0412] The device receives the analysis results from the server and displays them to the user, including specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0413] For example, user A receives advice through his device such as, "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please see this link: https: / / example.com / video."

[0414] Specific examples

[0415] As a concrete example, suppose User B enters the following information:

[0416] Hobbies: Listening to music

[0417] Favorite subject: Music

[0418] Least Favorite Subject: Physical Education

[0419] What I want to do in the future: Become a music producer

[0420] Where I want to live: Urban area

[0421] Family environment: Only child

[0422] Current friendships: I have a few close friends

[0423] The server receives this information, and the generative AI model analyzes it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, it suggests "music producer" or "music teacher." The analysis results are sent to User B's device along with images and video links, and User B receives advice such as, "Your strength is creativity. A music producer or music teacher would be suitable occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0424] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0425] The processing flow will be explained below.

[0426] Step 1: User enters information

[0427] Users access the device interface and enter information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, friendships, etc. This is user information.

[0428] Step 2: Collect user information

[0429] The terminal temporarily stores the information entered by the user, which is used for subsequent processing.

[0430] Step 3: Submit user information

[0431] The device sends the collected user information to the server, for example, using an HTTP POST request.

[0432] Step 4: Receiving data on the server

[0433] The server receives the user information sent from the device and stores the received data for analysis.

[0434] Step 5: Analysis by generative AI model

[0435] The server inputs the received user information into the generative AI model, which then uses this information to diagnose the user's personality and suggest careers.

[0436] Step 6: Generate analysis results

[0437] The server compiles the analysis results obtained from the generative AI model, including the user's strengths, recommended occupations, and occupation details.

[0438] Step 7: Submitting the analysis results

[0439] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0440] Step 8: Viewing the analysis results

[0441] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0442] Step 9: User Feedback

[0443] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0444] Example 1

[0445] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0446] In today's world, there is a strong demand for systems that suggest optimal careers and paths for individual users. However, conventional systems have struggled to provide comprehensive and accurate results in the collection, analysis, and proposal of user information. For example, problems exist such as insufficient analysis of individually input information or generalized proposals. A system that can solve these problems and support users in making appropriate and satisfactory career choices is needed.

[0447] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0448] In this invention, the server includes means for providing an interface accessible to the user and inputting information, means for transmitting collected user information to the server, means for the server to store the received user information in a database, means for the server to analyze the user information using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, and means for the terminal to display the transmitted analysis results to the user. This makes it possible to accurately analyze user information and make suggestions in a specific and visually easy-to-understand format.

[0449] A "user-accessible interface" is any form or screen that a user can use to enter information.

[0450] "Means for inputting information" refers to a function that allows users to collect information such as their hobbies and special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their family environment, and friendships.

[0451] "Means for sending to the server" refers to the communication protocol and network functions for sending collected user information to the server.

[0452] "Means for storing in a database" refers to a database or storage system for temporarily or permanently storing the user information received by the server.

[0453] A "generative AI model" is an artificial intelligence model that analyzes user information and uses that information to make personality diagnoses and career suggestions.

[0454] The "means of analysis" is a processing function that uses a generative AI model to analyze user information and derive results.

[0455] "Means for transmitting to the terminal" refers to the communication protocols and network functions for transmitting the analysis results obtained by the generative AI model to the user's terminal.

[0456] "Means for displaying to the user" refers to a screen or interface for presenting the analysis results received by the terminal to the user.

[0457] "Personality diagnosis" refers to analyzing a user's characteristics and personality based on information entered by the user and providing the results.

[0458] "Means to suggest future careers" is a function that suggests suitable careers and career paths for users based on analysis by a generative AI model.

[0459] "Means for displaying specific images and video links" refers to a function that displays the results of the analysis in a format that includes related images and video links in order to communicate the results to the user in an easy-to-understand manner.

[0460] The present invention is a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. This system uses a user-accessible interface, a server, a generative AI model, a database, a communication protocol, and a display terminal.

[0461] First, the device provides the user with an interface for inputting information. The user inputs information on the device screen, such as their hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and their friendships. This interface can be realized as a web application or a mobile application.

[0462] The entered information is then collected by the device and sent to the server in real time using a communication protocol such as HTTP or HTTPS. The server then stores the received user information in a database, which can be a relational database such as MySQL or PostgreSQL.

[0463] The server performs analysis using a generative AI model based on the saved user information. This generative AI model may use existing generative AI technology such as OpenAI's GPT-3. Analysis begins by inputting a prompt statement to the model. The following is an example of a prompt statement:

[0464] Based on your user information, we will suggest the best career path for you. Enter the following user information:

[0465] Hobbies: Listening to music

[0466] Favorite subject: Music

[0467] Least Favorite Subject: Physical Education

[0468] What I want to do in the future: Become a music producer

[0469] Where I want to live: Urban area

[0470] Family environment: Only child

[0471] Current friendships: I have a few close friends

[0472] Based on the user's information, the generative AI model analyzes the user's characteristics and strengths and suggests suitable occupations and future paths. The analysis results include an overview of the user's strengths, suitable occupations, and personality assessment.

[0473] The server sends the analysis results obtained by the generative AI model to the user's device. For example, the result might be, "Your strength is creativity. A suitable career would be a music producer or music teacher. For more information, please see this link: https: / / example.com / music_video."

[0474] Finally, the device displays the analysis results received from the server to the user. At this time, the analysis results are displayed including concrete images and video links, so the user can obtain information in a visually easy-to-understand format.

[0475] For example, if User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the generative AI model will analyze this information, determine that "communication skills are a strength," and suggest jobs like "teacher" or "consultant." The server sends this result to the device, which then displays it to the user as "Your strength is communication skills. Suitable occupations are teacher or consultant. For more information, please see this link: https: / / example.com / video."

[0476] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0477] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0478] Step 1:

[0479] The terminal provides the user with an interface for inputting information, such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0480] Input: Personal information entered by the user on the device (e.g., "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math").

[0481] Output: A dataset of the input user information.

[0482] Specific behavior:

[0483] User A enters "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math" into the input form displayed on the device screen. When the user presses the "Send" button, the information is temporarily saved on the device.

[0484] Step 2:

[0485] The device sends the collected user information to the server using a communication protocol such as HTTP / HTTPS.

[0486] Input: User information stored on the device.

[0487] Output: The user information sent to the server.

[0488] Specific behavior:

[0489] After the information entered by User A is temporarily saved on the device, the device immediately sends the information to the server, which receives the data using the HTTPS protocol.

[0490] Step 3:

[0491] The server stores the received user information in a database, where the data is processed and stored as needed.

[0492] Input: User information received by the server.

[0493] Output: User information stored in the database.

[0494] Specific behavior:

[0495] The server receives User A's information (hobbies, favorite subjects, least favorite subjects, etc.) and stores it in the database as "User A: Hobbies are reading, favorite subject is Japanese, least favorite subject is math." This makes it available for use in later steps.

[0496] Step 4:

[0497] The server uses the generative AI model to analyze the stored user information, which includes creating prompt sentences and inputting them into the AI ​​model.

[0498] Input: User information stored in the database.

[0499] Output: Analysis results from the generative AI model.

[0500] Specific behavior:

[0501] The server generates the following prompt and inputs it into the generative AI model: "Based on the information about user A, please suggest the most suitable occupation or career path. The following user information is entered: hobby is reading, favorite subject is Japanese, least favorite subject is math, and wants to live abroad in the future." Based on this, the generative AI model obtains the result that "communication skills are a strength," and suggests "teacher" or "consultant."

[0502] Step 5:

[0503] The server transmits the generated analysis results to the user's terminal.

[0504] Input: Analysis results from the generative AI model.

[0505] Output: Analysis results sent to the device.

[0506] Specific behavior:

[0507] The analysis results provided by the generative AI model (communication skills are a strength, and suitable occupations are teaching or consulting) are compiled on a server and sent to the device using the HTTPS protocol.

[0508] Step 6:

[0509] The device displays the analysis results received from the server to the user, including specific images and video links.

[0510] Input: Analysis results received from the server.

[0511] Output: Analysis results displayed to the user.

[0512] Specific behavior:

[0513] The analysis result will be displayed on User A's device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please refer to this link: https: / / example.com / video." User A can click the link to visually check the detailed information.

[0514] Through these steps, user information is collected, analyzed using a generative AI model, and a system is created that suggests optimal occupations and career paths.

[0515] (Application example 1)

[0516] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0517] Conventional career and career suggestion systems have the problem that detailed face-to-face counseling is difficult because the process of collecting and analyzing user information is carried out only online. If the consultation environment in a physical store is insufficient, it may be difficult for users to fully understand the content of the suggestions, making it difficult to make an appropriate decision. Another issue is that the provision of additional information is limited, making it difficult for users to concretely imagine the career or career path that is best suited to them.

[0518] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0519] In this invention, the server includes means for collecting information entered by the user, means for transmitting the collected user information to the server, means for analyzing using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, means for the terminal to display the analysis results transmitted to the user, means for the terminal to display the analysis results transmitted on a guidance device in the physical store, means for using a robot in the physical store to input user information and display the analysis results, and means for providing additional information in a dedicated consultation booth or at a terminal. This enables detailed face-to-face counseling and allows users to specifically understand the occupations and career paths that are best suited to them.

[0520] "Information gathering means" refers to a means of providing an interface that users can access and input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0521] The "means for transmitting to the server" is a communication means for transmitting the collected user information to the server.

[0522] The "analysis means" is a means for analyzing the user information received by the server using a generative AI model.

[0523] The "means for transmitting analysis results by the generative AI model" is a means for transmitting analysis results by the generative AI model from the server to the terminal.

[0524] The "analysis result display means" is a means for visually displaying the analysis results transmitted by the terminal to the user.

[0525] The "guide device display means" is a means for displaying the analysis results sent by the terminal on a guide device in a physical store.

[0526] The "user information input means and analysis result display means" refers to a means for inputting user information using a robot in a physical store and displaying the analysis results.

[0527] "Means for providing additional information" refers to means for providing detailed information at dedicated consultation booths or terminals.

[0528] This invention provides a system that collects information entered by users, analyzes it, and suggests optimal occupations and career paths. The system uses robots and terminals for users to enter information in physical stores, and transmits the collected data to a server. The system then analyzes the results using a generative AI model and displays them on information displays and terminals in the physical stores, providing detailed information to users face-to-face.

[0529] Hardware and software used

[0530] Hardware: In-store guide robot, user tablet, server

[0531] Software: Server with API endpoint, Python script, generative AI model

[0532] Data collection

[0533] Users use a robot or tablet device in a physical store to input information about themselves, such as hobbies, favorite subjects, least favorite subjects, future goals, where they want to live, their home environment, and friendships. This allows the system to collect specific information about the user's characteristics and wishes.

[0534] Data transmission and analysis

[0535] The collected user information is sent to the server in real time. Here, the data is sent to the server as a POST request using Python's requests library. The server inputs the received data into a generative AI model to analyze the optimal occupation and career path.

[0536] Displaying analysis results

[0537] When the server returns the analysis results from the generated AI model, the results are returned to the client (robot or tablet device) in JSON format. The analysis results include suitable occupations, the user's strengths, and a summary of their personality. The device visually displays these results to the user. In addition, in-store guide devices and robots present detailed information and related content (images, video links, etc.) to help users understand the situation more concretely.

[0538] Specific examples

[0539] For example, if a user enters the following information:

[0540] Hobbies: Photography

[0541] Favorite subject: Art

[0542] Least Favorite Subject: Physics

[0543] What I want to do in the future: Become a professional photographer

[0544] Where I want to live: Local area

[0545] Family: Large family

[0546] Friendships: A few very close friends

[0547] When this information is input into a generative AI model, it analyzes it and concludes that "creativity is a strength, and a career such as professional photography or commercial photography would be suitable." The analysis result is displayed as "Your strength is creativity. A suitable career would be professional photography or commercial photography. For more information, please see this link: https: / / example.com / photo_career."

[0548] As described above, this invention uses a generative AI model to analyze user information and propose occupations and career paths in a concrete and visually easy-to-understand format, making it easier for users to make appropriate decisions. In addition, by providing a consultation environment in a physical store, detailed face-to-face counseling is possible.

[0549] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0550] Step 1:

[0551] Users input their information using a robot or tablet device in a physical store. The input information includes hobbies, favorite subjects, least favorite subjects, future goals, desired place to live, family environment, friendships, etc. This information is saved on the device. Input data includes "hobbies: photography," "favorite subject: art," "least favorite subject: physics," etc., and the collected data is sent to a server in real time.

[0552] Step 2:

[0553] The collected user information is sent from the device to the server. The server receives it in POST format using the Python requests library. The input data is the information the user entered earlier. The server then inputs the received data into a generative AI model ready for analysis.

[0554] Step 3:

[0555] The server has the generative AI model analyze the input data. The generative AI model analyzes the data based on the prompt. This analysis identifies the user's strengths and suitable occupations. For example, it may determine that "creativity is a strength, so professional photography or advertising photography would be suitable." The results of this data calculation are output in JSON format.

[0556] Step 4:

[0557] The server sends the analysis results of the generative AI model in JSON format to the device. The data sent includes career suggestions based on the analysis results and information about the user's strengths. Specifically, it includes information such as, "Your strength is creativity. A suitable career would be professional photography or advertising photography."

[0558] Step 5:

[0559] The device receives the analysis results from the server and displays them to the user. The analysis results are displayed as the user's strengths, suitable careers, and even specific images and video links. For example, the link might include "More information here: https: / / example.com / photo_career."

[0560] Step 6:

[0561] The in-store guidance device visually displays the analysis results to the user, allowing the user to obtain more specific and detailed information. This display is linked to the user's device to provide detailed images and videos.

[0562] Step 7:

[0563] Dedicated consultation booths and terminals provide additional information to users, who can receive detailed counseling and learn more about specific career plans and future goals based on the analysis results.

[0564] Through these steps, the system supports users in choosing the right occupation or career path, and provides an environment where users can receive face-to-face counseling in a physical store.

[0565] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0566] This invention combines a system that collects user information, analyzes it using a generative AI model, and suggests optimal career paths and occupations with an emotion engine that recognizes the user's emotions. This system makes it possible to suggest personalized career paths and occupations that take the user's emotional aspects into consideration. Below, we will explain each component of the system and how they work together.

[0567] Collection and transmission of user information and emotional data

[0568] Device:

[0569] The device provides an interface that users can access, and allows them to input information such as their hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, and their friendships. The device also has a built-in emotion engine that collects emotional data from the user's facial expressions and voice. The information collected in this way is sent to the server as user information.

[0570] For example, User A might enter, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," and the emotion engine would then recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0571] Data reception and analysis

[0572] server:

[0573] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotion engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotion engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state.

[0574] For example, the server receives information about user A and analyzes that "communication skills are his strengths, and a career as a teacher or consultant would be suitable," and also reads from his emotional data that user A is in a relaxed state. Taking this information into consideration, the server generates appropriate advice.

[0575] Sending analysis results

[0576] server:

[0577] The server sends the analysis results of the generative AI model and emotion engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0578] Displaying analysis results

[0579] Device:

[0580] The device receives the analysis results from the server and displays them to the user. The analysis results include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0581] For example, user A might see the following message on their device: "Your strength is communication skills. A suitable career would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0582] Specific examples

[0583] As a concrete example, suppose User B enters the following information:

[0584] Hobbies: Listening to music

[0585] Favorite subject: Music

[0586] Least Favorite Subject: Physical Education

[0587] What I want to do in the future: Become a music producer

[0588] Where I want to live: Urban area

[0589] Family environment: Only child

[0590] Current friendships: I have a few close friends

[0591] The emotion engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0592] In this way, the system of the present invention uses a generative AI model and emotion engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[0593] The processing flow will be explained below.

[0594] Step 1: User enters information

[0595] Users access the device's interface and input information such as hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, friendships, etc. The device's built-in emotion engine also recognizes the user's emotions in real time from their facial expressions and voice and collects them as data.

[0596] Step 2: Collect user information and sentiment data

[0597] The device temporarily stores the information entered by the user and the emotional data collected by the emotion engine, which is then used in subsequent processing.

[0598] Step 3: Sending user information and emotion data

[0599] The device sends the collected user information and emotion data to the server, for example, using an HTTP POST request.

[0600] Step 4: Receiving data on the server

[0601] The server receives the user information and emotion data sent from the device, and stores the received data for analysis.

[0602] Step 5: Analysis by generative AI models and emotion engines

[0603] The server inputs the received user information into a generative AI model to perform personality assessment and career suggestions, and also uses an emotion engine to analyze the user's emotional data and perform additional personalized analysis based on the user's emotional state.

[0604] Step 6: Generate analysis results

[0605] The server combines the analysis results from the generative AI model with the emotion data from the emotion engine to generate final advice for the user, including the user's strengths, recommended occupations, a personality summary, and advice based on the user's emotions.

[0606] Step 7: Submitting the analysis results

[0607] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0608] Step 8: Viewing the analysis results

[0609] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0610] Step 9: User Feedback

[0611] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0612] Example 2

[0613] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0614] Conventional career and occupation suggestion systems only considered the user's personality and aptitude, ignoring emotional aspects, which resulted in suggestions that were inappropriate for some users. Furthermore, the suggested results were difficult to visually understand, resulting in low user understanding and satisfaction. Furthermore, there were limited methods for improving the accuracy of the information entered by users and their motivation.

[0615] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0616] In this invention, the server includes means for collecting information and emotional data input by the user, means for transmitting the collected user information and emotional data to the server, means for analyzing the user information and emotional data received by the server using a generative AI model and an emotional analysis engine, means for transmitting the analysis results by the generative AI model and the emotional analysis engine from the server to the terminal, and means for the terminal to visually display the analysis results sent to the user. This enables personalized career and occupation suggestions that take the user's emotional aspects into consideration, and by displaying the suggestion results in a visually easy-to-understand manner, it is possible to improve the user's understanding and satisfaction.

[0617] "User" refers to an individual who uses the system or who inputs information and receives analysis results.

[0618] "Information" includes data entered by the user, such as hobbies, special skills, favorite subjects, least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0619] "Emotion data" is information about the emotional state collected from the user's facial expressions and voice.

[0620] "Server" refers to a central computer system that receives user information and emotion data, analyzes it using a generative AI model and emotion analysis engine, and transmits the results to the device.

[0621] "Terminal" refers to a device for users to input information and a device for displaying analysis results, and specifically includes smartphones, PCs, tablets, etc.

[0622] "Means for collection" refers to the functions and devices that allow a terminal to input or acquire user information and emotion data.

[0623] "Means for transmitting" refers to the means for transmitting user information and emotion data collected by the terminal to the server, as well as the functions and technologies for transmitting the analysis results generated by the server to the terminal.

[0624] "Means of analysis" refers to the functions and algorithms that analyze the user information and emotional data received by the server using a generative AI model and an emotion analysis engine.

[0625] A "generative AI model" refers to an artificial intelligence model that performs personality diagnosis and career suggestions based on user information.

[0626] An "emotion analysis engine" refers to a system that analyzes emotional data from a user's facial expressions and voice and identifies the user's emotional state.

[0627] "Display means" refers to the functions and technologies that allow the terminal to visually present the analysis results to the user.

[0628] "Visually displaying" means providing the analysis results to the user in a form that is intuitively easy to understand, and includes forms such as text information, images, and video links.

[0629] This invention is a system that collects user information and emotional data, analyzes it using a generative AI model and an emotional analysis engine, and then suggests optimal career paths and occupations. This system makes it possible to suggest personalized career paths and occupations that also take into account the user's emotional aspects. This section describes in detail each component of the system and how they work together.

[0630] Collection and transmission of user information and emotional data

[0631] Terminal

[0632] The device provides an interface accessible to users, through which they input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and their friendships. The device also incorporates an emotion engine that collects emotional data from the user's facial expressions and voice. This collected information is then sent to the server as user information. For example, if User A inputs, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the emotion engine will recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0633] Data reception and analysis

[0634] server

[0635] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotional analysis engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotional analysis engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state. As a concrete example, the server receives information about User A and analyzes that "communication skills are his strengths and that teaching or consulting would be suitable occupations," while also reading from the emotional data that User A is in a relaxed state. Taking this information into consideration, appropriate advice is generated.

[0636] Sending analysis results

[0637] server

[0638] The server sends the analysis results from the generative AI model and the emotion analysis engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0639] Displaying analysis results

[0640] Terminal

[0641] The device displays the analysis results received from the server to the user. The analysis results also include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format. For example, user A might see the following message on his device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0642] Specific examples

[0643] As a concrete example, suppose User B enters the following information:

[0644] Hobbies: Listening to music

[0645] Favorite subject: Music

[0646] Least Favorite Subject: Physical Education

[0647] What I want to do in the future: Become a music producer

[0648] Where I want to live: Urban area

[0649] Family environment: Only child

[0650] Current friendships: I have a few close friends

[0651] The emotion analysis engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion analysis engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable for you." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0652] In this way, the system of the present invention uses a generative AI model and an emotion analysis engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[0653] Prompt Sentence Examples

[0654] "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I would like to live abroad in the future, I would like to live in an urban area, I get along well with my siblings at home, and I currently have many friends. Based on this, please suggest a suitable occupation or career path."

[0655] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0656] Step 1:

[0657] The device collects information entered by the user. The input information includes the user's hobbies and special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and friendships. After the user has completed their input, the device temporarily stores it. For example, if the user inputs "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the information will be temporarily stored.

[0658] Step 2:

[0659] The device uses an emotion engine to collect user emotional data. It uses a camera and microphone as input to collect the user's facial expressions and voice. For example, the camera detects whether the user is smiling, and the microphone analyzes the tone and speed of the voice. Based on this, emotional data such as whether the user is relaxed or excited is collected.

[0660] Step 3:

[0661] The device transmits the collected user information and emotional data to the server. The input includes user information and emotional data, and the integrated data is transmitted to the server as output. For example, data such as "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends" and "I feel relaxed" are transmitted.

[0662] Step 4:

[0663] The server receives user information and emotion data sent from the device. It takes user information and emotion data as input and prepares them for analysis as output. Specifically, it stores the received data in a database and passes it to the analysis engine.

[0664] Step 5:

[0665] The server analyzes user information using a generative AI model. The input includes user information (hobbies, favorite subjects, least favorite subjects, etc.), and the output generates a personality assessment result for the user and suggestions for suitable careers. For example, if the result is "good communication skills," "teacher" or "consultant" will be suggested.

[0666] Step 6:

[0667] The server analyzes the emotional data using an emotion analysis engine. The input includes the collected emotional data, and the output generates advice based on the user's emotional state. For example, if the user is "relaxed," advice to maintain that state is provided.

[0668] Step 7:

[0669] The server combines the analysis results of the generative AI model and the emotion analysis engine to generate the final analysis result. The input includes the personality assessment results, suitable career suggestions, and emotion-based advice, and the output is a report that integrates these. For example, the report may say, "Your strength is communication skills. Suitable careers are teaching or consulting. A relaxed state will be beneficial for these suggestions."

[0670] Step 8:

[0671] The server sends the generated analysis results to the user's device. The final analysis results are included as input, and the results are sent to the device as output. For example, the result sent to the device might be, "Your strength is communication skills. Suitable occupations are teaching or consulting. A relaxed state will be beneficial for this suggestion."

[0672] Step 9:

[0673] The device displays the analysis results received from the server to the user. The input contains the final analysis results, and the output displays them visually. Specifically, text information, images, video links, etc. are displayed. For example, it might say, "Your strength is communication skills. Suitable occupations are teaching or consulting. For more information, please refer to this link: https: / / example.com / video."

[0674] (Application example 2)

[0675] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0676] Conventional systems only provide analysis results based on user input, making it difficult to provide personalized recommendations that match the user's emotions and preferences. Furthermore, these systems are limited in their ability to improve the user experience, and online shopping sites, in particular, lack the means to efficiently recommend the most suitable products for each user. As a result, users' purchasing motivation cannot be fully stimulated, resulting in a decrease in satisfaction and lost purchasing opportunities.

[0677] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user information and emotion data, means for analyzing the collected user information and emotion data, and means for generating personalized proposals based on the analysis results. This enables personalized product proposals that take into account the user's preferences and emotions.

[0678] "User information" refers to data entered by the user, such as hobbies, special skills, preferred types, desired product categories, colors, styles, etc.

[0679] "Emotion data" refers to data relating to the user's emotional state, such as excitement or relaxation, obtained from the user's facial expressions and voice.

[0680] The term "server" refers to a computer system that receives and analyzes user information and emotion data, and includes a processing device, a storage device, a communication device, and the like for performing specific analytical processing.

[0681] "Terminal" refers to a device that provides an interface for a user to access and a device that displays the analysis results sent from the server.

[0682] A "generative AI model" refers to an artificial intelligence model that analyzes collected user information to diagnose personality and suggest future careers and products.

[0683] An "emotion engine" refers to a system that recognizes emotions from a user's facial expressions and voice data and generates data corresponding to that emotional state.

[0684] "Personalized suggestions" means suggesting the most suitable products or occupations based on the user's individual preferences and emotional state.

[0685] "Image and video links" refers to media links and visual information that provide information in a form that is visually easy for users to understand.

[0686] The present invention is a system that collects user information and emotional data, analyzes them using a generative AI model, and makes optimal product or career recommendations. This system also takes into account the user's emotional state, allowing for more personalized recommendations.

[0687] Program and system configuration

[0688] The system mainly consists of a user's device and a server. The device is a device such as a smartphone, smart glasses, or head-mounted display, and uses a camera and microphone to collect the user's facial expression and voice data. Based on this data, the user's information and emotional data are collected. The device also provides an interface for inputting information such as the user's hobbies and skills, preferred type, desired product category, color, and style.

[0689] 1. Collecting user information and sentiment data:

[0690] Users collect facial expression data through the camera on their smartphone or smart glasses, and collect voice data using a microphone.

[0691] Using this data, an emotion engine (e.g., EmotionRecognizer) analyzes the user's emotional state.

[0692] 2. Data transmission:

[0693] The collected user information and emotion data are transmitted from the terminal to a server.

[0694] 3. Data analysis on the server:

[0695] Based on the received data, the server analyzes the user's preferences and emotional state using a generative AI model (e.g., RecommendationEngine).

[0696] Based on the analysis results, the server suggests the most suitable product or occupation to the user.

[0697] 4. Displaying the proposed results:

[0698] The analysis results sent from the server are displayed on the terminal.

[0699] The proposed results include concrete images and video links, and are displayed in a way that is easy for users to understand visually.

[0700] For example, if User C enters the following information:

[0701] Hobbies: Fashion

[0702] Favorite color: Blue

[0703] Category of product you want:Outerwear

[0704] Facial expression data: excited

[0705] Based on this user information and emotional data, the generative AI model and emotion engine perform analysis and make optimal product recommendations. User C is recommended a "blue trench coat," offering a stylish design that suits their current excited mood. Detailed information and a purchase link are also provided, displaying a message such as "Click here for more details" (e.g., https: / / example.com / outerwear).

[0706] Example prompt sentence:

[0707] User information: Hobbies are fashion, favorite color is blue, desired product category is outerwear

[0708] Facial expression data: excited

[0709] Based on the analysis results, we will propose the most suitable product.

[0710] This system will be able to appropriately consider the user's preferences and emotions and make optimal product and occupation suggestions, which is expected to improve user satisfaction and stimulate purchasing motivation.

[0711] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0712] Step 1:

[0713] Users input information such as hobbies, special skills, preferred types, desired product categories, colors, and styles. Furthermore, facial expression data is collected using the camera on a smartphone or smart glasses, and voice data is collected using a microphone. The input information and emotional data are temporarily stored on the device.

[0714] Input: Hobbies, special skills, preferred type, desired product category, color, style, facial expression data, voice data

[0715] Output: Temporarily saved user information and emotion data

[0716] Step 2:

[0717] The device sends the user information and emotion data collected and saved in step 1 to the server. The transmitted data is encrypted and handled securely.

[0718] Input: Temporarily saved user information and emotional data

[0719] Output: User information and emotion data sent to the server

[0720] Step 3:

[0721] The server analyzes the received user information and emotional data. First, it uses an emotion engine to analyze facial expression and voice data to recognize the user's emotional state. Then, it uses a generative AI model to perform analysis based on the user's preferences and emotional state.

[0722] Input: User information and emotion data sent to the server

[0723] Output: Analyzed user preference and emotional state data

[0724] Step 4:

[0725] The server then generates optimal product or job suggestions based on the analyzed data, including specific images and video links.

[0726] Input: Parsed user preference and emotional state data

[0727] Output: Generated product or job proposal data (including specific images and video links)

[0728] Step 5:

[0729] The server generates and sends the proposed data to the device, which is personalized to the user in real time.

[0730] Input: Generated product or occupation proposal data

[0731] Output: Proposal data sent to the device

[0732] Step 6:

[0733] The device receives the proposed data sent from the server and displays it to the user, who can visually confirm the images and video links and obtain more detailed information.

[0734] Input: Proposal data sent to the device

[0735] Output: The proposal data displayed to the user (including images and video links)

[0736] As a concrete example, when User C inputs information such as his hobbies, special skills, and preferences and collects emotional data, the server analyzes the data using a generative AI model and an emotion engine to generate a blue trench coat recommendation. This recommendation includes a link to more details, which User C can visually check on his device.

[0737] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0738] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0739] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0740] [Third embodiment]

[0741] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0742] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0743] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0744] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0745] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0746] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0747] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0748] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0749] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0750] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0751] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0752] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0753] This invention relates to a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. Below, we will explain each component of the system and how they work together.

[0754] Collection and transmission of user information

[0755] Device:

[0756] The terminal provides an interface that users can access, and users input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, friendships, etc. This information is collected as user information and sent to the server.

[0757] For example, suppose User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends." This information is saved on the device and immediately sent to the server.

[0758] Data reception and analysis

[0759] server:

[0760] The server receives the user information sent from the device and analyzes it using a generative AI model. The generative AI model performs a personality diagnosis based on the user's characteristics and suggests suitable occupations and future career paths for the user.

[0761] For example, the server receives information about user A, analyzes that "communication skills" are a strength, and suggests suitable jobs such as "teacher" or "consultant."

[0762] Sending analysis results

[0763] server:

[0764] The server sends the analysis results of the generative AI model to the user's device, which include an overview of the user's strengths, suitable occupations, and personality assessment.

[0765] Displaying analysis results

[0766] Device:

[0767] The device receives the analysis results from the server and displays them to the user, including specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0768] For example, user A receives advice through his device such as, "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please see this link: https: / / example.com / video."

[0769] Specific examples

[0770] As a concrete example, suppose User B enters the following information:

[0771] Hobbies: Listening to music

[0772] Favorite subject: Music

[0773] Least Favorite Subject: Physical Education

[0774] What I want to do in the future: Become a music producer

[0775] Where I want to live: Urban area

[0776] Family environment: Only child

[0777] Current friendships: I have a few close friends

[0778] The server receives this information, and the generative AI model analyzes it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, it suggests "music producer" or "music teacher." The analysis results are sent to User B's device along with images and video links, and User B receives advice such as, "Your strength is creativity. A music producer or music teacher would be suitable occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0779] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0780] The processing flow will be explained below.

[0781] Step 1: User enters information

[0782] Users access the device interface and enter information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, friendships, etc. This is user information.

[0783] Step 2: Collect user information

[0784] The terminal temporarily stores the information entered by the user, which is used for subsequent processing.

[0785] Step 3: Submit user information

[0786] The device sends the collected user information to the server, for example, using an HTTP POST request.

[0787] Step 4: Receiving data on the server

[0788] The server receives the user information sent from the device and stores the received data for analysis.

[0789] Step 5: Analysis by generative AI model

[0790] The server inputs the received user information into the generative AI model, which then uses this information to diagnose the user's personality and suggest careers.

[0791] Step 6: Generate analysis results

[0792] The server compiles the analysis results obtained from the generative AI model, including the user's strengths, recommended occupations, and occupation details.

[0793] Step 7: Submitting the analysis results

[0794] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0795] Step 8: Viewing the analysis results

[0796] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0797] Step 9: User Feedback

[0798] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0799] Example 1

[0800] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0801] In today's world, there is a strong demand for systems that suggest optimal careers and paths for individual users. However, conventional systems have struggled to provide comprehensive and accurate results in the collection, analysis, and proposal of user information. For example, problems exist such as insufficient analysis of individually input information or generalized proposals. A system that can solve these problems and support users in making appropriate and satisfactory career choices is needed.

[0802] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0803] In this invention, the server includes means for providing an interface accessible to the user and inputting information, means for transmitting collected user information to the server, means for the server to store the received user information in a database, means for the server to analyze the user information using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, and means for the terminal to display the transmitted analysis results to the user. This makes it possible to accurately analyze user information and make suggestions in a specific and visually easy-to-understand format.

[0804] A "user-accessible interface" is any form or screen that a user can use to enter information.

[0805] "Means for inputting information" refers to a function that allows users to collect information such as their hobbies and special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their family environment, and friendships.

[0806] "Means for sending to the server" refers to the communication protocol and network functions for sending collected user information to the server.

[0807] "Means for storing in a database" refers to a database or storage system for temporarily or permanently storing the user information received by the server.

[0808] A "generative AI model" is an artificial intelligence model that analyzes user information and uses that information to make personality diagnoses and career suggestions.

[0809] The "means of analysis" is a processing function that uses a generative AI model to analyze user information and derive results.

[0810] "Means for transmitting to the terminal" refers to the communication protocols and network functions for transmitting the analysis results obtained by the generative AI model to the user's terminal.

[0811] "Means for displaying to the user" refers to a screen or interface for presenting the analysis results received by the terminal to the user.

[0812] "Personality diagnosis" refers to analyzing a user's characteristics and personality based on information entered by the user and providing the results.

[0813] "Means to suggest future careers" is a function that suggests suitable careers and career paths for users based on analysis by a generative AI model.

[0814] "Means for displaying specific images and video links" refers to a function that displays the results of the analysis in a format that includes related images and video links in order to communicate the results to the user in an easy-to-understand manner.

[0815] The present invention is a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. This system uses a user-accessible interface, a server, a generative AI model, a database, a communication protocol, and a display terminal.

[0816] First, the device provides the user with an interface for inputting information. The user inputs information on the device screen, such as their hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and their friendships. This interface can be realized as a web application or a mobile application.

[0817] The entered information is then collected by the device and sent to the server in real time using a communication protocol such as HTTP or HTTPS. The server then stores the received user information in a database, which can be a relational database such as MySQL or PostgreSQL.

[0818] The server performs analysis using a generative AI model based on the saved user information. This generative AI model may use existing generative AI technology such as OpenAI's GPT-3. Analysis begins by inputting a prompt statement to the model. The following is an example of a prompt statement:

[0819] Based on your user information, we will suggest the best career path for you. Enter the following user information:

[0820] Hobbies: Listening to music

[0821] Favorite subject: Music

[0822] Least Favorite Subject: Physical Education

[0823] What I want to do in the future: Become a music producer

[0824] Where I want to live: Urban area

[0825] Family environment: Only child

[0826] Current friendships: I have a few close friends

[0827] Based on the user's information, the generative AI model analyzes the user's characteristics and strengths and suggests suitable occupations and future paths. The analysis results include an overview of the user's strengths, suitable occupations, and personality assessment.

[0828] The server sends the analysis results obtained by the generative AI model to the user's device. For example, the result might be, "Your strength is creativity. A suitable career would be a music producer or music teacher. For more information, please see this link: https: / / example.com / music_video."

[0829] Finally, the device displays the analysis results received from the server to the user. At this time, the analysis results are displayed including concrete images and video links, so the user can obtain information in a visually easy-to-understand format.

[0830] For example, if User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the generative AI model will analyze this information, determine that "communication skills are a strength," and suggest jobs like "teacher" or "consultant." The server sends this result to the device, which then displays it to the user as "Your strength is communication skills. Suitable occupations are teacher or consultant. For more information, please see this link: https: / / example.com / video."

[0831] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[0832] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0833] Step 1:

[0834] The terminal provides the user with an interface for inputting information, such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0835] Input: Personal information entered by the user on the device (e.g., "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math").

[0836] Output: A dataset of the input user information.

[0837] Specific behavior:

[0838] User A enters "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math" into the input form displayed on the device screen. When the user presses the "Send" button, the information is temporarily saved on the device.

[0839] Step 2:

[0840] The device sends the collected user information to the server using a communication protocol such as HTTP / HTTPS.

[0841] Input: User information stored on the device.

[0842] Output: The user information sent to the server.

[0843] Specific behavior:

[0844] After the information entered by User A is temporarily saved on the device, the device immediately sends the information to the server, which receives the data using the HTTPS protocol.

[0845] Step 3:

[0846] The server stores the received user information in a database, where the data is processed and stored as needed.

[0847] Input: User information received by the server.

[0848] Output: User information stored in the database.

[0849] Specific behavior:

[0850] The server receives User A's information (hobbies, favorite subjects, least favorite subjects, etc.) and stores it in the database as "User A: Hobbies are reading, favorite subject is Japanese, least favorite subject is math." This makes it available for use in later steps.

[0851] Step 4:

[0852] The server uses the generative AI model to analyze the stored user information, which includes creating prompt sentences and inputting them into the AI ​​model.

[0853] Input: User information stored in the database.

[0854] Output: Analysis results from the generative AI model.

[0855] Specific behavior:

[0856] The server generates the following prompt and inputs it into the generative AI model: "Based on the information about user A, please suggest the most suitable occupation or career path. The following user information is entered: hobby is reading, favorite subject is Japanese, least favorite subject is math, and wants to live abroad in the future." Based on this, the generative AI model obtains the result that "communication skills are a strength," and suggests "teacher" or "consultant."

[0857] Step 5:

[0858] The server transmits the generated analysis results to the user's terminal.

[0859] Input: Analysis results from the generative AI model.

[0860] Output: Analysis results sent to the device.

[0861] Specific behavior:

[0862] The analysis results provided by the generative AI model (communication skills are a strength, and suitable occupations are teaching or consulting) are compiled on a server and sent to the device using the HTTPS protocol.

[0863] Step 6:

[0864] The device displays the analysis results received from the server to the user, including specific images and video links.

[0865] Input: Analysis results received from the server.

[0866] Output: Analysis results displayed to the user.

[0867] Specific behavior:

[0868] The analysis result will be displayed on User A's device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please refer to this link: https: / / example.com / video." User A can click the link to visually check the detailed information.

[0869] Through these steps, user information is collected, analyzed using a generative AI model, and a system is created that suggests optimal occupations and career paths.

[0870] (Application example 1)

[0871] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0872] Conventional career and career suggestion systems have the problem that detailed face-to-face counseling is difficult because the process of collecting and analyzing user information is carried out only online. If the consultation environment in a physical store is insufficient, it may be difficult for users to fully understand the content of the suggestions, making it difficult to make an appropriate decision. Another issue is that the provision of additional information is limited, making it difficult for users to concretely imagine the career or career path that is best suited to them.

[0873] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0874] In this invention, the server includes means for collecting information entered by the user, means for transmitting the collected user information to the server, means for analyzing using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, means for the terminal to display the analysis results transmitted to the user, means for the terminal to display the analysis results transmitted on a guidance device in the physical store, means for using a robot in the physical store to input user information and display the analysis results, and means for providing additional information in a dedicated consultation booth or at a terminal. This enables detailed face-to-face counseling and allows users to specifically understand the occupations and career paths that are best suited to them.

[0875] "Information gathering means" refers to a means of providing an interface that users can access and input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0876] The "means for transmitting to the server" is a communication means for transmitting the collected user information to the server.

[0877] The "analysis means" is a means for analyzing the user information received by the server using a generative AI model.

[0878] The "means for transmitting analysis results by the generative AI model" is a means for transmitting analysis results by the generative AI model from the server to the terminal.

[0879] The "analysis result display means" is a means for visually displaying the analysis results transmitted by the terminal to the user.

[0880] The "guide device display means" is a means for displaying the analysis results sent by the terminal on a guide device in a physical store.

[0881] The "user information input means and analysis result display means" refers to a means for inputting user information using a robot in a physical store and displaying the analysis results.

[0882] "Means for providing additional information" refers to means for providing detailed information at dedicated consultation booths or terminals.

[0883] This invention provides a system that collects information entered by users, analyzes it, and suggests optimal occupations and career paths. The system uses robots and terminals for users to enter information in physical stores, and transmits the collected data to a server. The system then analyzes the results using a generative AI model and displays them on information displays and terminals in the physical stores, providing detailed information to users face-to-face.

[0884] Hardware and software used

[0885] Hardware: In-store guide robot, user tablet, server

[0886] Software: Server with API endpoint, Python script, generative AI model

[0887] Data collection

[0888] Users use a robot or tablet device in a physical store to input information about themselves, such as hobbies, favorite subjects, least favorite subjects, future goals, where they want to live, their home environment, and friendships. This allows the system to collect specific information about the user's characteristics and wishes.

[0889] Data transmission and analysis

[0890] The collected user information is sent to the server in real time. Here, the data is sent to the server as a POST request using Python's requests library. The server inputs the received data into a generative AI model to analyze the optimal occupation and career path.

[0891] Displaying analysis results

[0892] When the server returns the analysis results from the generated AI model, the results are returned to the client (robot or tablet device) in JSON format. The analysis results include suitable occupations, the user's strengths, and a summary of their personality. The device visually displays these results to the user. In addition, in-store guide devices and robots present detailed information and related content (images, video links, etc.) to help users understand the situation more concretely.

[0893] Specific examples

[0894] For example, if a user enters the following information:

[0895] Hobbies: Photography

[0896] Favorite subject: Art

[0897] Least Favorite Subject: Physics

[0898] What I want to do in the future: Become a professional photographer

[0899] Where I want to live: Local area

[0900] Family: Large family

[0901] Friendships: A few very close friends

[0902] When this information is input into a generative AI model, it analyzes it and concludes that "creativity is a strength, and a career such as professional photography or commercial photography would be suitable." The analysis result is displayed as "Your strength is creativity. A suitable career would be professional photography or commercial photography. For more information, please see this link: https: / / example.com / photo_career."

[0903] As described above, this invention uses a generative AI model to analyze user information and propose occupations and career paths in a concrete and visually easy-to-understand format, making it easier for users to make appropriate decisions. In addition, by providing a consultation environment in a physical store, detailed face-to-face counseling is possible.

[0904] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0905] Step 1:

[0906] Users input their information using a robot or tablet device in a physical store. The input information includes hobbies, favorite subjects, least favorite subjects, future goals, desired place to live, family environment, friendships, etc. This information is saved on the device. Input data includes "hobbies: photography," "favorite subject: art," "least favorite subject: physics," etc., and the collected data is sent to a server in real time.

[0907] Step 2:

[0908] The collected user information is sent from the device to the server. The server receives it in POST format using the Python requests library. The input data is the information the user entered earlier. The server then inputs the received data into a generative AI model ready for analysis.

[0909] Step 3:

[0910] The server has the generative AI model analyze the input data. The generative AI model analyzes the data based on the prompt. This analysis identifies the user's strengths and suitable occupations. For example, it may determine that "creativity is a strength, so professional photography or advertising photography would be suitable." The results of this data calculation are output in JSON format.

[0911] Step 4:

[0912] The server sends the analysis results of the generative AI model in JSON format to the device. The data sent includes career suggestions based on the analysis results and information about the user's strengths. Specifically, it includes information such as, "Your strength is creativity. A suitable career would be professional photography or advertising photography."

[0913] Step 5:

[0914] The device receives the analysis results from the server and displays them to the user. The analysis results are displayed as the user's strengths, suitable careers, and even specific images and video links. For example, the link might include "More information here: https: / / example.com / photo_career."

[0915] Step 6:

[0916] The in-store guidance device visually displays the analysis results to the user, allowing the user to obtain more specific and detailed information. This display is linked to the user's device to provide detailed images and videos.

[0917] Step 7:

[0918] Dedicated consultation booths and terminals provide additional information to users, who can receive detailed counseling and learn more about specific career plans and future goals based on the analysis results.

[0919] Through these steps, the system supports users in choosing the right occupation or career path, and provides an environment where users can receive face-to-face counseling in a physical store.

[0920] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0921] This invention combines a system that collects user information, analyzes it using a generative AI model, and suggests optimal career paths and occupations with an emotion engine that recognizes the user's emotions. This system makes it possible to suggest personalized career paths and occupations that take the user's emotional aspects into consideration. Below, we will explain each component of the system and how they work together.

[0922] Collection and transmission of user information and emotional data

[0923] Device:

[0924] The device provides an interface that users can access, and allows them to input information such as their hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, and their friendships. The device also has a built-in emotion engine that collects emotional data from the user's facial expressions and voice. The information collected in this way is sent to the server as user information.

[0925] For example, User A might enter, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," and the emotion engine would then recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0926] Data reception and analysis

[0927] server:

[0928] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotion engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotion engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state.

[0929] For example, the server receives information about user A and analyzes that "communication skills are his strengths, and a career as a teacher or consultant would be suitable," and also reads from his emotional data that user A is in a relaxed state. Taking this information into consideration, the server generates appropriate advice.

[0930] Sending analysis results

[0931] server:

[0932] The server sends the analysis results of the generative AI model and emotion engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0933] Displaying analysis results

[0934] Device:

[0935] The device receives the analysis results from the server and displays them to the user. The analysis results include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[0936] For example, user A might see the following message on their device: "Your strength is communication skills. A suitable career would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0937] Specific examples

[0938] As a concrete example, suppose User B enters the following information:

[0939] Hobbies: Listening to music

[0940] Favorite subject: Music

[0941] Least Favorite Subject: Physical Education

[0942] What I want to do in the future: Become a music producer

[0943] Where I want to live: Urban area

[0944] Family environment: Only child

[0945] Current friendships: I have a few close friends

[0946] The emotion engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[0947] In this way, the system of the present invention uses a generative AI model and emotion engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[0948] The processing flow will be explained below.

[0949] Step 1: User enters information

[0950] Users access the device's interface and input information such as hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, friendships, etc. The device's built-in emotion engine also recognizes the user's emotions in real time from their facial expressions and voice and collects them as data.

[0951] Step 2: Collect user information and sentiment data

[0952] The device temporarily stores the information entered by the user and the emotional data collected by the emotion engine, which is then used in subsequent processing.

[0953] Step 3: Sending user information and emotion data

[0954] The device sends the collected user information and emotion data to the server, for example, using an HTTP POST request.

[0955] Step 4: Receiving data on the server

[0956] The server receives the user information and emotion data sent from the device, and stores the received data for analysis.

[0957] Step 5: Analysis by generative AI models and emotion engines

[0958] The server inputs the received user information into a generative AI model to perform personality assessment and career suggestions, and also uses an emotion engine to analyze the user's emotional data and perform additional personalized analysis based on the user's emotional state.

[0959] Step 6: Generate analysis results

[0960] The server combines the analysis results from the generative AI model with the emotion data from the emotion engine to generate final advice for the user, including the user's strengths, recommended occupations, a personality summary, and advice based on the user's emotions.

[0961] Step 7: Submitting the analysis results

[0962] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[0963] Step 8: Viewing the analysis results

[0964] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[0965] Step 9: User Feedback

[0966] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[0967] Example 2

[0968] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0969] Conventional career and occupation suggestion systems only considered the user's personality and aptitude, ignoring emotional aspects, which resulted in suggestions that were inappropriate for some users. Furthermore, the suggested results were difficult to visually understand, resulting in low user understanding and satisfaction. Furthermore, there were limited methods for improving the accuracy of the information entered by users and their motivation.

[0970] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0971] In this invention, the server includes means for collecting information and emotional data input by the user, means for transmitting the collected user information and emotional data to the server, means for analyzing the user information and emotional data received by the server using a generative AI model and an emotional analysis engine, means for transmitting the analysis results by the generative AI model and the emotional analysis engine from the server to the terminal, and means for the terminal to visually display the analysis results sent to the user. This enables personalized career and occupation suggestions that take the user's emotional aspects into consideration, and by displaying the suggestion results in a visually easy-to-understand manner, it is possible to improve the user's understanding and satisfaction.

[0972] "User" refers to an individual who uses the system or who inputs information and receives analysis results.

[0973] "Information" includes data entered by the user, such as hobbies, special skills, favorite subjects, least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[0974] "Emotion data" is information about the emotional state collected from the user's facial expressions and voice.

[0975] "Server" refers to a central computer system that receives user information and emotion data, analyzes it using a generative AI model and emotion analysis engine, and transmits the results to the device.

[0976] "Terminal" refers to a device for users to input information and a device for displaying analysis results, and specifically includes smartphones, PCs, tablets, etc.

[0977] "Means for collection" refers to the functions and devices that allow a terminal to input or acquire user information and emotion data.

[0978] "Means for transmitting" refers to the means for transmitting user information and emotion data collected by the terminal to the server, as well as the functions and technologies for transmitting the analysis results generated by the server to the terminal.

[0979] "Means of analysis" refers to the functions and algorithms that analyze the user information and emotional data received by the server using a generative AI model and an emotion analysis engine.

[0980] A "generative AI model" refers to an artificial intelligence model that performs personality diagnosis and career suggestions based on user information.

[0981] An "emotion analysis engine" refers to a system that analyzes emotional data from a user's facial expressions and voice and identifies the user's emotional state.

[0982] "Display means" refers to the functions and technologies that allow the terminal to visually present the analysis results to the user.

[0983] "Visually displaying" means providing the analysis results to the user in a form that is intuitively easy to understand, and includes forms such as text information, images, and video links.

[0984] This invention is a system that collects user information and emotional data, analyzes it using a generative AI model and an emotional analysis engine, and then suggests optimal career paths and occupations. This system makes it possible to suggest personalized career paths and occupations that also take into account the user's emotional aspects. This section describes in detail each component of the system and how they work together.

[0985] Collection and transmission of user information and emotional data

[0986] Terminal

[0987] The device provides an interface accessible to users, through which they input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and their friendships. The device also incorporates an emotion engine that collects emotional data from the user's facial expressions and voice. This collected information is then sent to the server as user information. For example, if User A inputs, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the emotion engine will recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[0988] Data reception and analysis

[0989] server

[0990] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotional analysis engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotional analysis engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state. As a concrete example, the server receives information about User A and analyzes that "communication skills are his strengths and that teaching or consulting would be suitable occupations," while also reading from the emotional data that User A is in a relaxed state. Taking this information into consideration, appropriate advice is generated.

[0991] Sending analysis results

[0992] server

[0993] The server sends the analysis results from the generative AI model and the emotion analysis engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[0994] Displaying analysis results

[0995] Terminal

[0996] The device displays the analysis results received from the server to the user. The analysis results also include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format. For example, user A might see the following message on his device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[0997] Specific examples

[0998] As a concrete example, suppose User B enters the following information:

[0999] Hobbies: Listening to music

[1000] Favorite subject: Music

[1001] Least Favorite Subject: Physical Education

[1002] What I want to do in the future: Become a music producer

[1003] Where I want to live: Urban area

[1004] Family environment: Only child

[1005] Current friendships: I have a few close friends

[1006] The emotion analysis engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion analysis engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable for you." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[1007] In this way, the system of the present invention uses a generative AI model and an emotion analysis engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[1008] Prompt Sentence Examples

[1009] "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I would like to live abroad in the future, I would like to live in an urban area, I get along well with my siblings at home, and I currently have many friends. Based on this, please suggest a suitable occupation or career path."

[1010] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] The device collects information entered by the user. The input information includes the user's hobbies and special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and friendships. After the user has completed their input, the device temporarily stores it. For example, if the user inputs "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the information will be temporarily stored.

[1013] Step 2:

[1014] The device uses an emotion engine to collect user emotional data. It uses a camera and microphone as input to collect the user's facial expressions and voice. For example, the camera detects whether the user is smiling, and the microphone analyzes the tone and speed of the voice. Based on this, emotional data such as whether the user is relaxed or excited is collected.

[1015] Step 3:

[1016] The device transmits the collected user information and emotional data to the server. The input includes user information and emotional data, and the integrated data is transmitted to the server as output. For example, data such as "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends" and "I feel relaxed" are transmitted.

[1017] Step 4:

[1018] The server receives user information and emotion data sent from the device. It takes user information and emotion data as input and prepares them for analysis as output. Specifically, it stores the received data in a database and passes it to the analysis engine.

[1019] Step 5:

[1020] The server analyzes user information using a generative AI model. The input includes user information (hobbies, favorite subjects, least favorite subjects, etc.), and the output generates a personality assessment result for the user and suggestions for suitable careers. For example, if the result is "good communication skills," "teacher" or "consultant" will be suggested.

[1021] Step 6:

[1022] The server analyzes the emotional data using an emotion analysis engine. The input includes the collected emotional data, and the output generates advice based on the user's emotional state. For example, if the user is "relaxed," advice to maintain that state is provided.

[1023] Step 7:

[1024] The server combines the analysis results of the generative AI model and the emotion analysis engine to generate the final analysis result. The input includes the personality assessment results, suitable career suggestions, and emotion-based advice, and the output is a report that integrates these. For example, the report may say, "Your strength is communication skills. Suitable careers are teaching or consulting. A relaxed state will be beneficial for these suggestions."

[1025] Step 8:

[1026] The server sends the generated analysis results to the user's device. The final analysis results are included as input, and the results are sent to the device as output. For example, the result sent to the device might be, "Your strength is communication skills. Suitable occupations are teaching or consulting. A relaxed state will be beneficial for this suggestion."

[1027] Step 9:

[1028] The device displays the analysis results received from the server to the user. The input contains the final analysis results, and the output displays them visually. Specifically, text information, images, video links, etc. are displayed. For example, it might say, "Your strength is communication skills. Suitable occupations are teaching or consulting. For more information, please refer to this link: https: / / example.com / video."

[1029] (Application example 2)

[1030] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1031] Conventional systems only provide analysis results based on user input, making it difficult to provide personalized recommendations that match the user's emotions and preferences. Furthermore, these systems are limited in their ability to improve the user experience, and online shopping sites, in particular, lack the means to efficiently recommend the most suitable products for each user. As a result, users' purchasing motivation cannot be fully stimulated, resulting in a decrease in satisfaction and lost purchasing opportunities.

[1032] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user information and emotion data, means for analyzing the collected user information and emotion data, and means for generating personalized proposals based on the analysis results. This enables personalized product proposals that take into account the user's preferences and emotions.

[1033] "User information" refers to data entered by the user, such as hobbies, special skills, preferred types, desired product categories, colors, styles, etc.

[1034] "Emotion data" refers to data relating to the user's emotional state, such as excitement or relaxation, obtained from the user's facial expressions and voice.

[1035] The term "server" refers to a computer system that receives and analyzes user information and emotion data, and includes a processing device, a storage device, a communication device, and the like for performing specific analytical processing.

[1036] "Terminal" refers to a device that provides an interface for a user to access and a device that displays the analysis results sent from the server.

[1037] A "generative AI model" refers to an artificial intelligence model that analyzes collected user information to diagnose personality and suggest future careers and products.

[1038] An "emotion engine" refers to a system that recognizes emotions from a user's facial expressions and voice data and generates data corresponding to that emotional state.

[1039] "Personalized suggestions" means suggesting the most suitable products or occupations based on the user's individual preferences and emotional state.

[1040] "Image and video links" refers to media links and visual information that provide information in a form that is visually easy for users to understand.

[1041] The present invention is a system that collects user information and emotional data, analyzes them using a generative AI model, and makes optimal product or career recommendations. This system also takes into account the user's emotional state, allowing for more personalized recommendations.

[1042] Program and system configuration

[1043] The system mainly consists of a user's device and a server. The device is a device such as a smartphone, smart glasses, or head-mounted display, and uses a camera and microphone to collect the user's facial expression and voice data. Based on this data, the user's information and emotional data are collected. The device also provides an interface for inputting information such as the user's hobbies and skills, preferred type, desired product category, color, and style.

[1044] 1. Collecting user information and sentiment data:

[1045] Users collect facial expression data through the camera on their smartphone or smart glasses, and collect voice data using a microphone.

[1046] Using this data, an emotion engine (e.g., EmotionRecognizer) analyzes the user's emotional state.

[1047] 2. Data transmission:

[1048] The collected user information and emotion data are transmitted from the terminal to a server.

[1049] 3. Data analysis on the server:

[1050] Based on the received data, the server analyzes the user's preferences and emotional state using a generative AI model (e.g., RecommendationEngine).

[1051] Based on the analysis results, the server suggests the most suitable product or occupation to the user.

[1052] 4. Displaying the proposed results:

[1053] The analysis results sent from the server are displayed on the terminal.

[1054] The proposed results include concrete images and video links, and are displayed in a way that is easy for users to understand visually.

[1055] For example, if User C enters the following information:

[1056] Hobbies: Fashion

[1057] Favorite color: Blue

[1058] Category of product you want:Outerwear

[1059] Facial expression data: excited

[1060] Based on this user information and emotional data, the generative AI model and emotion engine perform analysis and make optimal product recommendations. User C is recommended a "blue trench coat," offering a stylish design that suits their current excited mood. Detailed information and a purchase link are also provided, displaying a message such as "Click here for more details" (e.g., https: / / example.com / outerwear).

[1061] Example prompt sentence:

[1062] User information: Hobbies are fashion, favorite color is blue, desired product category is outerwear

[1063] Facial expression data: excited

[1064] Based on the analysis results, we will propose the most suitable product.

[1065] This system will be able to appropriately consider the user's preferences and emotions and make optimal product and occupation suggestions, which is expected to improve user satisfaction and stimulate purchasing motivation.

[1066] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1067] Step 1:

[1068] Users input information such as hobbies, special skills, preferred types, desired product categories, colors, and styles. Furthermore, facial expression data is collected using the camera on a smartphone or smart glasses, and voice data is collected using a microphone. The input information and emotional data are temporarily stored on the device.

[1069] Input: Hobbies, special skills, preferred type, desired product category, color, style, facial expression data, voice data

[1070] Output: Temporarily saved user information and emotion data

[1071] Step 2:

[1072] The device sends the user information and emotion data collected and saved in step 1 to the server. The transmitted data is encrypted and handled securely.

[1073] Input: Temporarily saved user information and emotional data

[1074] Output: User information and emotion data sent to the server

[1075] Step 3:

[1076] The server analyzes the received user information and emotional data. First, it uses an emotion engine to analyze facial expression and voice data to recognize the user's emotional state. Then, it uses a generative AI model to perform analysis based on the user's preferences and emotional state.

[1077] Input: User information and emotion data sent to the server

[1078] Output: Analyzed user preference and emotional state data

[1079] Step 4:

[1080] The server then generates optimal product or job suggestions based on the analyzed data, including specific images and video links.

[1081] Input: Parsed user preference and emotional state data

[1082] Output: Generated product or job proposal data (including specific images and video links)

[1083] Step 5:

[1084] The server generates and sends the proposed data to the device, which is personalized to the user in real time.

[1085] Input: Generated product or occupation proposal data

[1086] Output: Proposal data sent to the device

[1087] Step 6:

[1088] The device receives the proposed data sent from the server and displays it to the user, who can visually confirm the images and video links and obtain more detailed information.

[1089] Input: Proposal data sent to the device

[1090] Output: The proposal data displayed to the user (including images and video links)

[1091] As a concrete example, when User C inputs information such as his hobbies, special skills, and preferences and collects emotional data, the server analyzes the data using a generative AI model and an emotion engine to generate a blue trench coat recommendation. This recommendation includes a link to more details, which User C can visually check on his device.

[1092] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1093] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1094] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1095] [Fourth embodiment]

[1096] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1097] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1098] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1099] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1100] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1102] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1103] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1104] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1105] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1106] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1107] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1108] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1109] This invention relates to a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. Below, we will explain each component of the system and how they work together.

[1110] Collection and transmission of user information

[1111] Device:

[1112] The terminal provides an interface that users can access, and users input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, friendships, etc. This information is collected as user information and sent to the server.

[1113] For example, suppose User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends." This information is saved on the device and immediately sent to the server.

[1114] Data reception and analysis

[1115] server:

[1116] The server receives the user information sent from the device and analyzes it using a generative AI model. The generative AI model performs a personality diagnosis based on the user's characteristics and suggests suitable occupations and future career paths for the user.

[1117] For example, the server receives information about user A, analyzes that "communication skills" are a strength, and suggests suitable jobs such as "teacher" or "consultant."

[1118] Sending analysis results

[1119] server:

[1120] The server sends the analysis results of the generative AI model to the user's device, which include an overview of the user's strengths, suitable occupations, and personality assessment.

[1121] Displaying analysis results

[1122] Device:

[1123] The device receives the analysis results from the server and displays them to the user, including specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[1124] For example, user A receives advice through his device such as, "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please see this link: https: / / example.com / video."

[1125] Specific examples

[1126] As a concrete example, suppose User B enters the following information:

[1127] Hobbies: Listening to music

[1128] Favorite subject: Music

[1129] Least Favorite Subject: Physical Education

[1130] What I want to do in the future: Become a music producer

[1131] Where I want to live: Urban area

[1132] Family environment: Only child

[1133] Current friendships: I have a few close friends

[1134] The server receives this information, and the generative AI model analyzes it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, it suggests "music producer" or "music teacher." The analysis results are sent to User B's device along with images and video links, and User B receives advice such as, "Your strength is creativity. A music producer or music teacher would be suitable occupations. For more information, please refer to this link: https: / / example.com / music_video."

[1135] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[1136] The processing flow will be explained below.

[1137] Step 1: User enters information

[1138] Users access the device interface and enter information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, friendships, etc. This is user information.

[1139] Step 2: Collect user information

[1140] The terminal temporarily stores the information entered by the user, which is used for subsequent processing.

[1141] Step 3: Submit user information

[1142] The device sends the collected user information to the server, for example, using an HTTP POST request.

[1143] Step 4: Receiving data on the server

[1144] The server receives the user information sent from the device and stores the received data for analysis.

[1145] Step 5: Analysis by generative AI model

[1146] The server inputs the received user information into the generative AI model, which then uses this information to diagnose the user's personality and suggest careers.

[1147] Step 6: Generate analysis results

[1148] The server compiles the analysis results obtained from the generative AI model, including the user's strengths, recommended occupations, and occupation details.

[1149] Step 7: Submitting the analysis results

[1150] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[1151] Step 8: Viewing the analysis results

[1152] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[1153] Step 9: User Feedback

[1154] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[1155] Example 1

[1156] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1157] In today's world, there is a strong demand for systems that suggest optimal careers and paths for individual users. However, conventional systems have struggled to provide comprehensive and accurate results in the collection, analysis, and proposal of user information. For example, problems exist such as insufficient analysis of individually input information or generalized proposals. A system that can solve these problems and support users in making appropriate and satisfactory career choices is needed.

[1158] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1159] In this invention, the server includes means for providing an interface accessible to the user and inputting information, means for transmitting collected user information to the server, means for the server to store the received user information in a database, means for the server to analyze the user information using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, and means for the terminal to display the transmitted analysis results to the user. This makes it possible to accurately analyze user information and make suggestions in a specific and visually easy-to-understand format.

[1160] A "user-accessible interface" is any form or screen that a user can use to enter information.

[1161] "Means for inputting information" refers to a function that allows users to collect information such as their hobbies and special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their family environment, and friendships.

[1162] "Means for sending to the server" refers to the communication protocol and network functions for sending collected user information to the server.

[1163] "Means for storing in a database" refers to a database or storage system for temporarily or permanently storing the user information received by the server.

[1164] A "generative AI model" is an artificial intelligence model that analyzes user information and uses that information to make personality diagnoses and career suggestions.

[1165] The "means of analysis" is a processing function that uses a generative AI model to analyze user information and derive results.

[1166] "Means for transmitting to the terminal" refers to the communication protocols and network functions for transmitting the analysis results obtained by the generative AI model to the user's terminal.

[1167] "Means for displaying to the user" refers to a screen or interface for presenting the analysis results received by the terminal to the user.

[1168] "Personality diagnosis" refers to analyzing a user's characteristics and personality based on information entered by the user and providing the results.

[1169] "Means to suggest future careers" is a function that suggests suitable careers and career paths for users based on analysis by a generative AI model.

[1170] "Means for displaying specific images and video links" refers to a function that displays the results of the analysis in a format that includes related images and video links in order to communicate the results to the user in an easy-to-understand manner.

[1171] The present invention is a system that collects user information and uses a generative AI model to suggest optimal career paths and occupations. This system uses a user-accessible interface, a server, a generative AI model, a database, a communication protocol, and a display terminal.

[1172] First, the device provides the user with an interface for inputting information. The user inputs information on the device screen, such as their hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and their friendships. This interface can be realized as a web application or a mobile application.

[1173] The entered information is then collected by the device and sent to the server in real time using a communication protocol such as HTTP or HTTPS. The server then stores the received user information in a database, which can be a relational database such as MySQL or PostgreSQL.

[1174] The server performs analysis using a generative AI model based on the saved user information. This generative AI model may use existing generative AI technology such as OpenAI's GPT-3. Analysis begins by inputting a prompt statement to the model. The following is an example of a prompt statement:

[1175] Based on your user information, we will suggest the best career path for you. Enter the following user information:

[1176] Hobbies: Listening to music

[1177] Favorite subject: Music

[1178] Least Favorite Subject: Physical Education

[1179] What I want to do in the future: Become a music producer

[1180] Where I want to live: Urban area

[1181] Family environment: Only child

[1182] Current friendships: I have a few close friends

[1183] Based on the user's information, the generative AI model analyzes the user's characteristics and strengths and suggests suitable occupations and future paths. The analysis results include an overview of the user's strengths, suitable occupations, and personality assessment.

[1184] The server sends the analysis results obtained by the generative AI model to the user's device. For example, the result might be, "Your strength is creativity. A suitable career would be a music producer or music teacher. For more information, please see this link: https: / / example.com / music_video."

[1185] Finally, the device displays the analysis results received from the server to the user. At this time, the analysis results are displayed including concrete images and video links, so the user can obtain information in a visually easy-to-understand format.

[1186] For example, if User A inputs the following information: "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the generative AI model will analyze this information, determine that "communication skills are a strength," and suggest jobs like "teacher" or "consultant." The server sends this result to the device, which then displays it to the user as "Your strength is communication skills. Suitable occupations are teacher or consultant. For more information, please see this link: https: / / example.com / video."

[1187] In this way, the system of the present invention uses a generative AI model based on user information to suggest occupations and career paths in a concrete and visually easy-to-understand manner, providing an environment where users can easily speak frankly and supporting them in making career choices without regrets.

[1188] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1189] Step 1:

[1190] The terminal provides the user with an interface for inputting information, such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[1191] Input: Personal information entered by the user on the device (e.g., "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math").

[1192] Output: A dataset of the input user information.

[1193] Specific behavior:

[1194] User A enters "My hobby is reading, my favorite subject is Japanese, and my least favorite subject is math" into the input form displayed on the device screen. When the user presses the "Send" button, the information is temporarily saved on the device.

[1195] Step 2:

[1196] The device sends the collected user information to the server using a communication protocol such as HTTP / HTTPS.

[1197] Input: User information stored on the device.

[1198] Output: The user information sent to the server.

[1199] Specific behavior:

[1200] After the information entered by User A is temporarily saved on the device, the device immediately sends the information to the server, which receives the data using the HTTPS protocol.

[1201] Step 3:

[1202] The server stores the received user information in a database, where the data is processed and stored as needed.

[1203] Input: User information received by the server.

[1204] Output: User information stored in the database.

[1205] Specific behavior:

[1206] The server receives User A's information (hobbies, favorite subjects, least favorite subjects, etc.) and stores it in the database as "User A: Hobbies are reading, favorite subject is Japanese, least favorite subject is math." This makes it available for use in later steps.

[1207] Step 4:

[1208] The server uses the generative AI model to analyze the stored user information, which includes creating prompt sentences and inputting them into the AI ​​model.

[1209] Input: User information stored in the database.

[1210] Output: Analysis results from the generative AI model.

[1211] Specific behavior:

[1212] The server generates the following prompt and inputs it into the generative AI model: "Based on the information about user A, please suggest the most suitable occupation or career path. The following user information is entered: hobby is reading, favorite subject is Japanese, least favorite subject is math, and wants to live abroad in the future." Based on this, the generative AI model obtains the result that "communication skills are a strength," and suggests "teacher" or "consultant."

[1213] Step 5:

[1214] The server transmits the generated analysis results to the user's terminal.

[1215] Input: Analysis results from the generative AI model.

[1216] Output: Analysis results sent to the device.

[1217] Specific behavior:

[1218] The analysis results provided by the generative AI model (communication skills are a strength, and suitable occupations are teaching or consulting) are compiled on a server and sent to the device using the HTTPS protocol.

[1219] Step 6:

[1220] The device displays the analysis results received from the server to the user, including specific images and video links.

[1221] Input: Analysis results received from the server.

[1222] Output: Analysis results displayed to the user.

[1223] Specific behavior:

[1224] The analysis result will be displayed on User A's device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. For more information, please refer to this link: https: / / example.com / video." User A can click the link to visually check the detailed information.

[1225] Through these steps, user information is collected, analyzed using a generative AI model, and a system is created that suggests optimal occupations and career paths.

[1226] (Application example 1)

[1227] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1228] Conventional career and career suggestion systems have the problem that detailed face-to-face counseling is difficult because the process of collecting and analyzing user information is carried out only online. If the consultation environment in a physical store is insufficient, it may be difficult for users to fully understand the content of the suggestions, making it difficult to make an appropriate decision. Another issue is that the provision of additional information is limited, making it difficult for users to concretely imagine the career or career path that is best suited to them.

[1229] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1230] In this invention, the server includes means for collecting information entered by the user, means for transmitting the collected user information to the server, means for analyzing using a generative AI model, means for transmitting the analysis results of the generative AI model from the server to the terminal, means for the terminal to display the analysis results transmitted to the user, means for the terminal to display the analysis results transmitted on a guidance device in the physical store, means for using a robot in the physical store to input user information and display the analysis results, and means for providing additional information in a dedicated consultation booth or at a terminal. This enables detailed face-to-face counseling and allows users to specifically understand the occupations and career paths that are best suited to them.

[1231] "Information gathering means" refers to a means of providing an interface that users can access and input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[1232] The "means for transmitting to the server" is a communication means for transmitting the collected user information to the server.

[1233] The "analysis means" is a means for analyzing the user information received by the server using a generative AI model.

[1234] The "means for transmitting analysis results by the generative AI model" is a means for transmitting analysis results by the generative AI model from the server to the terminal.

[1235] The "analysis result display means" is a means for visually displaying the analysis results transmitted by the terminal to the user.

[1236] The "guide device display means" is a means for displaying the analysis results sent by the terminal on a guide device in a physical store.

[1237] The "user information input means and analysis result display means" refers to a means for inputting user information using a robot in a physical store and displaying the analysis results.

[1238] "Means for providing additional information" refers to means for providing detailed information at dedicated consultation booths or terminals.

[1239] This invention provides a system that collects information entered by users, analyzes it, and suggests optimal occupations and career paths. The system uses robots and terminals for users to enter information in physical stores, and transmits the collected data to a server. The system then analyzes the results using a generative AI model and displays them on information displays and terminals in the physical stores, providing detailed information to users face-to-face.

[1240] Hardware and software used

[1241] Hardware: In-store guide robot, user tablet, server

[1242] Software: Server with API endpoint, Python script, generative AI model

[1243] Data collection

[1244] Users use a robot or tablet device in a physical store to input information about themselves, such as hobbies, favorite subjects, least favorite subjects, future goals, where they want to live, their home environment, and friendships. This allows the system to collect specific information about the user's characteristics and wishes.

[1245] Data transmission and analysis

[1246] The collected user information is sent to the server in real time. Here, the data is sent to the server as a POST request using Python's requests library. The server inputs the received data into a generative AI model to analyze the optimal occupation and career path.

[1247] Displaying analysis results

[1248] When the server returns the analysis results from the generated AI model, the results are returned to the client (robot or tablet device) in JSON format. The analysis results include suitable occupations, the user's strengths, and a summary of their personality. The device visually displays these results to the user. In addition, in-store guide devices and robots present detailed information and related content (images, video links, etc.) to help users understand the situation more concretely.

[1249] Specific examples

[1250] For example, if a user enters the following information:

[1251] Hobbies: Photography

[1252] Favorite subject: Art

[1253] Least Favorite Subject: Physics

[1254] What I want to do in the future: Become a professional photographer

[1255] Where I want to live: Local area

[1256] Family: Large family

[1257] Friendships: A few very close friends

[1258] When this information is input into a generative AI model, it analyzes it and concludes that "creativity is a strength, and a career such as professional photography or commercial photography would be suitable." The analysis result is displayed as "Your strength is creativity. A suitable career would be professional photography or commercial photography. For more information, please see this link: https: / / example.com / photo_career."

[1259] As described above, this invention uses a generative AI model to analyze user information and propose occupations and career paths in a concrete and visually easy-to-understand format, making it easier for users to make appropriate decisions. In addition, by providing a consultation environment in a physical store, detailed face-to-face counseling is possible.

[1260] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1261] Step 1:

[1262] Users input their information using a robot or tablet device in a physical store. The input information includes hobbies, favorite subjects, least favorite subjects, future goals, desired place to live, family environment, friendships, etc. This information is saved on the device. Input data includes "hobbies: photography," "favorite subject: art," "least favorite subject: physics," etc., and the collected data is sent to a server in real time.

[1263] Step 2:

[1264] The collected user information is sent from the device to the server. The server receives it in POST format using the Python requests library. The input data is the information the user entered earlier. The server then inputs the received data into a generative AI model ready for analysis.

[1265] Step 3:

[1266] The server has the generative AI model analyze the input data. The generative AI model analyzes the data based on the prompt. This analysis identifies the user's strengths and suitable occupations. For example, it may determine that "creativity is a strength, so professional photography or advertising photography would be suitable." The results of this data calculation are output in JSON format.

[1267] Step 4:

[1268] The server sends the analysis results of the generative AI model in JSON format to the device. The data sent includes career suggestions based on the analysis results and information about the user's strengths. Specifically, it includes information such as, "Your strength is creativity. A suitable career would be professional photography or advertising photography."

[1269] Step 5:

[1270] The device receives the analysis results from the server and displays them to the user. The analysis results are displayed as the user's strengths, suitable careers, and even specific images and video links. For example, the link might include "More information here: https: / / example.com / photo_career."

[1271] Step 6:

[1272] The in-store guidance device visually displays the analysis results to the user, allowing the user to obtain more specific and detailed information. This display is linked to the user's device to provide detailed images and videos.

[1273] Step 7:

[1274] Dedicated consultation booths and terminals provide additional information to users, who can receive detailed counseling and learn more about specific career plans and future goals based on the analysis results.

[1275] Through these steps, the system supports users in choosing the right occupation or career path, and provides an environment where users can receive face-to-face counseling in a physical store.

[1276] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1277] This invention combines a system that collects user information, analyzes it using a generative AI model, and suggests optimal career paths and occupations with an emotion engine that recognizes the user's emotions. This system makes it possible to suggest personalized career paths and occupations that take the user's emotional aspects into consideration. Below, we will explain each component of the system and how they work together.

[1278] Collection and transmission of user information and emotional data

[1279] Device:

[1280] The device provides an interface that users can access, and allows them to input information such as their hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, and their friendships. The device also has a built-in emotion engine that collects emotional data from the user's facial expressions and voice. The information collected in this way is sent to the server as user information.

[1281] For example, User A might enter, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," and the emotion engine would then recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[1282] Data reception and analysis

[1283] server:

[1284] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotion engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotion engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state.

[1285] For example, the server receives information about user A and analyzes that "communication skills are his strengths, and a career as a teacher or consultant would be suitable," and also reads from his emotional data that user A is in a relaxed state. Taking this information into consideration, the server generates appropriate advice.

[1286] Sending analysis results

[1287] server:

[1288] The server sends the analysis results of the generative AI model and emotion engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[1289] Displaying analysis results

[1290] Device:

[1291] The device receives the analysis results from the server and displays them to the user. The analysis results include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format.

[1292] For example, user A might see the following message on their device: "Your strength is communication skills. A suitable career would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[1293] Specific examples

[1294] As a concrete example, suppose User B enters the following information:

[1295] Hobbies: Listening to music

[1296] Favorite subject: Music

[1297] Least Favorite Subject: Physical Education

[1298] What I want to do in the future: Become a music producer

[1299] Where I want to live: Urban area

[1300] Family environment: Only child

[1301] Current friendships: I have a few close friends

[1302] The emotion engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[1303] In this way, the system of the present invention uses a generative AI model and emotion engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[1304] The processing flow will be explained below.

[1305] Step 1: User enters information

[1306] Users access the device's interface and input information such as hobbies, special skills, favorite and least favorite subjects, what they would like to do in the future, where they would like to live, their home environment, friendships, etc. The device's built-in emotion engine also recognizes the user's emotions in real time from their facial expressions and voice and collects them as data.

[1307] Step 2: Collect user information and sentiment data

[1308] The device temporarily stores the information entered by the user and the emotional data collected by the emotion engine, which is then used in subsequent processing.

[1309] Step 3: Sending user information and emotion data

[1310] The device sends the collected user information and emotion data to the server, for example, using an HTTP POST request.

[1311] Step 4: Receiving data on the server

[1312] The server receives the user information and emotion data sent from the device, and stores the received data for analysis.

[1313] Step 5: Analysis by generative AI models and emotion engines

[1314] The server inputs the received user information into a generative AI model to perform personality assessment and career suggestions, and also uses an emotion engine to analyze the user's emotional data and perform additional personalized analysis based on the user's emotional state.

[1315] Step 6: Generate analysis results

[1316] The server combines the analysis results from the generative AI model with the emotion data from the emotion engine to generate final advice for the user, including the user's strengths, recommended occupations, a personality summary, and advice based on the user's emotions.

[1317] Step 7: Submitting the analysis results

[1318] The server then sends the generated analysis results to the terminal in a format that is easy for the user to understand.

[1319] Step 8: Viewing the analysis results

[1320] The device receives the analysis results from the server and displays them to the user, along with specific advice and links to related images and videos. Based on this, the user can consider their future career path and career choices.

[1321] Step 9: User Feedback

[1322] The device has an interface that allows the user to ask further questions or provide more information if they wish to know more about the proposed career path or occupation. The user can provide feedback as needed and send the new information back to the server for further analysis and advice.

[1323] Example 2

[1324] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1325] Conventional career and occupation suggestion systems only considered the user's personality and aptitude, ignoring emotional aspects, which resulted in suggestions that were inappropriate for some users. Furthermore, the suggested results were difficult to visually understand, resulting in low user understanding and satisfaction. Furthermore, there were limited methods for improving the accuracy of the information entered by users and their motivation.

[1326] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1327] In this invention, the server includes means for collecting information and emotional data input by the user, means for transmitting the collected user information and emotional data to the server, means for analyzing the user information and emotional data received by the server using a generative AI model and an emotional analysis engine, means for transmitting the analysis results by the generative AI model and the emotional analysis engine from the server to the terminal, and means for the terminal to visually display the analysis results sent to the user. This enables personalized career and occupation suggestions that take the user's emotional aspects into consideration, and by displaying the suggestion results in a visually easy-to-understand manner, it is possible to improve the user's understanding and satisfaction.

[1328] "User" refers to an individual who uses the system or who inputs information and receives analysis results.

[1329] "Information" includes data entered by the user, such as hobbies, special skills, favorite subjects, least favorite subjects, what they want to do in the future, where they want to live, their family environment, and friendships.

[1330] "Emotion data" is information about the emotional state collected from the user's facial expressions and voice.

[1331] "Server" refers to a central computer system that receives user information and emotion data, analyzes it using a generative AI model and emotion analysis engine, and transmits the results to the device.

[1332] "Terminal" refers to a device for users to input information and a device for displaying analysis results, and specifically includes smartphones, PCs, tablets, etc.

[1333] "Means for collection" refers to the functions and devices that allow a terminal to input or acquire user information and emotion data.

[1334] "Means for transmitting" refers to the means for transmitting user information and emotion data collected by the terminal to the server, as well as the functions and technologies for transmitting the analysis results generated by the server to the terminal.

[1335] "Means of analysis" refers to the functions and algorithms that analyze the user information and emotional data received by the server using a generative AI model and an emotion analysis engine.

[1336] A "generative AI model" refers to an artificial intelligence model that performs personality diagnosis and career suggestions based on user information.

[1337] An "emotion analysis engine" refers to a system that analyzes emotional data from a user's facial expressions and voice and identifies the user's emotional state.

[1338] "Display means" refers to the functions and technologies that allow the terminal to visually present the analysis results to the user.

[1339] "Visually displaying" means providing the analysis results to the user in a form that is intuitively easy to understand, and includes forms such as text information, images, and video links.

[1340] This invention is a system that collects user information and emotional data, analyzes it using a generative AI model and an emotional analysis engine, and then suggests optimal career paths and occupations. This system makes it possible to suggest personalized career paths and occupations that also take into account the user's emotional aspects. This section describes in detail each component of the system and how they work together.

[1341] Collection and transmission of user information and emotional data

[1342] Terminal

[1343] The device provides an interface accessible to users, through which they input information such as hobbies, special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and their friendships. The device also incorporates an emotion engine that collects emotional data from the user's facial expressions and voice. This collected information is then sent to the server as user information. For example, if User A inputs, "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the emotion engine will recognize User A's current emotions (e.g., excited, relaxed, etc.) and collect the data. This information is stored on the device and immediately sent to the server.

[1344] Data reception and analysis

[1345] server

[1346] The server receives user information and emotional data sent from the device. It then analyzes the information using a generative AI model and an emotional analysis engine. The generative AI model performs a personality diagnosis based on the user information and suggests suitable occupations and future career paths for the user. The emotional analysis engine analyzes the user's emotional data and provides more personalized advice based on the user's emotional state. As a concrete example, the server receives information about User A and analyzes that "communication skills are his strengths and that teaching or consulting would be suitable occupations," while also reading from the emotional data that User A is in a relaxed state. Taking this information into consideration, appropriate advice is generated.

[1347] Sending analysis results

[1348] server

[1349] The server sends the analysis results from the generative AI model and the emotion analysis engine to the user's device, which include the user's strengths, suitable occupations, a personality summary, and advice based on the user's emotions.

[1350] Displaying analysis results

[1351] Terminal

[1352] The device displays the analysis results received from the server to the user. The analysis results also include specific images and video links, allowing the user to obtain information in a visually easy-to-understand format. For example, user A might see the following message on his device: "Your strength is communication skills. Suitable occupations would be teaching or consulting. Your current relaxed state is a plus for this suggestion. For more information, please see this link: https: / / example.com / video."

[1353] Specific examples

[1354] As a concrete example, suppose User B enters the following information:

[1355] Hobbies: Listening to music

[1356] Favorite subject: Music

[1357] Least Favorite Subject: Physical Education

[1358] What I want to do in the future: Become a music producer

[1359] Where I want to live: Urban area

[1360] Family environment: Only child

[1361] Current friendships: I have a few close friends

[1362] The emotion analysis engine collects information about User B and recognizes that User B is in an excited state. The server receives this information, and the generative AI model and emotion analysis engine analyze it to determine that "creativity is your strength, and a music-related occupation would be suitable for you." Specifically, "music producer" or "music teacher" are suggested. Taking into account the excited state, advice is also provided recommending further investigation. The analysis results are sent to User B's device along with an image and video link, and User B is told, "Your strength is creativity. A suitable occupation would be a music producer or music teacher. Your current excited state is a good time to gain a deeper understanding of these occupations. For more information, please refer to this link: https: / / example.com / music_video."

[1363] In this way, the system of the present invention uses a generative AI model and an emotion analysis engine based on user information and emotion data to suggest occupations and career paths in a personalized, specific, and visually easy-to-understand manner, providing an environment where users can easily consult frankly and supporting them in making career choices without regrets.

[1364] Prompt Sentence Examples

[1365] "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I would like to live abroad in the future, I would like to live in an urban area, I get along well with my siblings at home, and I currently have many friends. Based on this, please suggest a suitable occupation or career path."

[1366] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1367] Step 1:

[1368] The device collects information entered by the user. The input information includes the user's hobbies and special skills, favorite and least favorite subjects, what they want to do in the future, where they want to live, their home environment, and friendships. After the user has completed their input, the device temporarily stores it. For example, if the user inputs "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends," the information will be temporarily stored.

[1369] Step 2:

[1370] The device uses an emotion engine to collect user emotional data. It uses a camera and microphone as input to collect the user's facial expressions and voice. For example, the camera detects whether the user is smiling, and the microphone analyzes the tone and speed of the voice. Based on this, emotional data such as whether the user is relaxed or excited is collected.

[1371] Step 3:

[1372] The device transmits the collected user information and emotional data to the server. The input includes user information and emotional data, and the integrated data is transmitted to the server as output. For example, data such as "My hobby is reading, my favorite subject is Japanese, my least favorite subject is math, I want to live abroad in the future, I want to live in an urban area, I get along well with my siblings at home, and I currently have many friends" and "I feel relaxed" are transmitted.

[1373] Step 4:

[1374] The server receives user information and emotion data sent from the device. It takes user information and emotion data as input and prepares them for analysis as output. Specifically, it stores the received data in a database and passes it to the analysis engine.

[1375] Step 5:

[1376] The server analyzes user information using a generative AI model. The input includes user information (hobbies, favorite subjects, least favorite subjects, etc.), and the output generates a personality assessment result for the user and suggestions for suitable careers. For example, if the result is "good communication skills," "teacher" or "consultant" will be suggested.

[1377] Step 6:

[1378] The server analyzes the emotional data using an emotion analysis engine. The input includes the collected emotional data, and the output generates advice based on the user's emotional state. For example, if the user is "relaxed," advice to maintain that state is provided.

[1379] Step 7:

[1380] The server combines the analysis results of the generative AI model and the emotion analysis engine to generate the final analysis result. The input includes the personality assessment results, suitable career suggestions, and emotion-based advice, and the output is a report that integrates these. For example, the report may say, "Your strength is communication skills. Suitable careers are teaching or consulting. A relaxed state will be beneficial for these suggestions."

[1381] Step 8:

[1382] The server sends the generated analysis results to the user's device. The final analysis results are included as input, and the results are sent to the device as output. For example, the result sent to the device might be, "Your strength is communication skills. Suitable occupations are teaching or consulting. A relaxed state will be beneficial for this suggestion."

[1383] Step 9:

[1384] The device displays the analysis results received from the server to the user. The input contains the final analysis results, and the output displays them visually. Specifically, text information, images, video links, etc. are displayed. For example, it might say, "Your strength is communication skills. Suitable occupations are teaching or consulting. For more information, please refer to this link: https: / / example.com / video."

[1385] (Application example 2)

[1386] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1387] Conventional systems only provide analysis results based on user input, making it difficult to provide personalized recommendations that match the user's emotions and preferences. Furthermore, these systems are limited in their ability to improve the user experience, and online shopping sites, in particular, lack the means to efficiently recommend the most suitable products for each user. As a result, users' purchasing motivation cannot be fully stimulated, resulting in a decrease in satisfaction and lost purchasing opportunities.

[1388] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user information and emotion data, means for analyzing the collected user information and emotion data, and means for generating personalized proposals based on the analysis results. This enables personalized product proposals that take into account the user's preferences and emotions.

[1389] "User information" refers to data entered by the user, such as hobbies, special skills, preferred types, desired product categories, colors, styles, etc.

[1390] "Emotion data" refers to data relating to the user's emotional state, such as excitement or relaxation, obtained from the user's facial expressions and voice.

[1391] The term "server" refers to a computer system that receives and analyzes user information and emotion data, and includes a processing device, a storage device, a communication device, and the like for performing specific analytical processing.

[1392] "Terminal" refers to a device that provides an interface for a user to access and a device that displays the analysis results sent from the server.

[1393] A "generative AI model" refers to an artificial intelligence model that analyzes collected user information to diagnose personality and suggest future careers and products.

[1394] An "emotion engine" refers to a system that recognizes emotions from a user's facial expressions and voice data and generates data corresponding to that emotional state.

[1395] "Personalized suggestions" means suggesting the most suitable products or occupations based on the user's individual preferences and emotional state.

[1396] "Image and video links" refers to media links and visual information that provide information in a form that is visually easy for users to understand.

[1397] The present invention is a system that collects user information and emotional data, analyzes them using a generative AI model, and makes optimal product or career recommendations. This system also takes into account the user's emotional state, allowing for more personalized recommendations.

[1398] Program and system configuration

[1399] The system mainly consists of a user's device and a server. The device is a device such as a smartphone, smart glasses, or head-mounted display, and uses a camera and microphone to collect the user's facial expression and voice data. Based on this data, the user's information and emotional data are collected. The device also provides an interface for inputting information such as the user's hobbies and skills, preferred type, desired product category, color, and style.

[1400] 1. Collecting user information and sentiment data:

[1401] Users collect facial expression data through the camera on their smartphone or smart glasses, and collect voice data using a microphone.

[1402] Using this data, an emotion engine (e.g., EmotionRecognizer) analyzes the user's emotional state.

[1403] 2. Data transmission:

[1404] The collected user information and emotion data are transmitted from the terminal to a server.

[1405] 3. Data analysis on the server:

[1406] Based on the received data, the server analyzes the user's preferences and emotional state using a generative AI model (e.g., RecommendationEngine).

[1407] Based on the analysis results, the server suggests the most suitable product or occupation to the user.

[1408] 4. Displaying the proposed results:

[1409] The analysis results sent from the server are displayed on the terminal.

[1410] The proposed results include concrete images and video links, and are displayed in a way that is easy for users to understand visually.

[1411] For example, if User C enters the following information:

[1412] Hobbies: Fashion

[1413] Favorite color: Blue

[1414] Category of product you want:Outerwear

[1415] Facial expression data: excited

[1416] Based on this user information and emotional data, the generative AI model and emotion engine perform analysis and make optimal product recommendations. User C is recommended a "blue trench coat," offering a stylish design that suits their current excited mood. Detailed information and a purchase link are also provided, displaying a message such as "Click here for more details" (e.g., https: / / example.com / outerwear).

[1417] Example prompt sentence:

[1418] User information: Hobbies are fashion, favorite color is blue, desired product category is outerwear

[1419] Facial expression data: excited

[1420] Based on the analysis results, we will propose the most suitable product.

[1421] This system will be able to appropriately consider the user's preferences and emotions and make optimal product and occupation suggestions, which is expected to improve user satisfaction and stimulate purchasing motivation.

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] Users input information such as hobbies, special skills, preferred types, desired product categories, colors, and styles. Furthermore, facial expression data is collected using the camera on a smartphone or smart glasses, and voice data is collected using a microphone. The input information and emotional data are temporarily stored on the device.

[1425] Input: Hobbies, special skills, preferred type, desired product category, color, style, facial expression data, voice data

[1426] Output: Temporarily saved user information and emotion data

[1427] Step 2:

[1428] The device sends the user information and emotion data collected and saved in step 1 to the server. The transmitted data is encrypted and handled securely.

[1429] Input: Temporarily saved user information and emotional data

[1430] Output: User information and emotion data sent to the server

[1431] Step 3:

[1432] The server analyzes the received user information and emotional data. First, it uses an emotion engine to analyze facial expression and voice data to recognize the user's emotional state. Then, it uses a generative AI model to perform analysis based on the user's preferences and emotional state.

[1433] Input: User information and emotion data sent to the server

[1434] Output: Analyzed user preference and emotional state data

[1435] Step 4:

[1436] The server then generates optimal product or job suggestions based on the analyzed data, including specific images and video links.

[1437] Input: Parsed user preference and emotional state data

[1438] Output: Generated product or job proposal data (including specific images and video links)

[1439] Step 5:

[1440] The server generates and sends the proposed data to the device, which is personalized to the user in real time.

[1441] Input: Generated product or occupation proposal data

[1442] Output: Proposal data sent to the device

[1443] Step 6:

[1444] The device receives the proposed data sent from the server and displays it to the user, who can visually confirm the images and video links and obtain more detailed information.

[1445] Input: Proposal data sent to the device

[1446] Output: The proposal data displayed to the user (including images and video links)

[1447] As a concrete example, when User C inputs information such as his hobbies, special skills, and preferences and collects emotional data, the server analyzes the data using a generative AI model and an emotion engine to generate a blue trench coat recommendation. This recommendation includes a link to more details, which User C can visually check on his device.

[1448] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1449] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1450] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1451] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1452] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1453] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1454] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1455] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1456] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1457] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1458] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1459] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1460] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1461] 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.

[1462] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1463] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1464] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1465] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1466] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1467] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1468] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1469] The following is further disclosed regarding the above embodiment.

[1470] (Claim 1)

[1471] a means for collecting user-entered information;

[1472] means for transmitting the collected user information to a server;

[1473] A means for analyzing the user information received by the server using a generative AI model;

[1474] A means for transmitting the analysis results of the generative AI model from the server to the terminal;

[1475] means for displaying the transmitted analysis results to the user by the terminal;

[1476] A system including:

[1477] (Claim 2)

[1478] The system of claim 1, wherein the generative AI model suggests personality assessments and future careers based on user information.

[1479] (Claim 3)

[1480] The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links.

[1481] "Example 1"

[1482] (Claim 1)

[1483] providing a user-accessible interface for inputting information; and

[1484] means for transmitting the collected user information to a server;

[1485] A means for storing the received user information in a database by the server;

[1486] A means for the server to analyze user information using the generated AI model;

[1487] A means for transmitting the analysis results of the generative AI model from the server to the terminal;

[1488] means for displaying the transmitted analysis results to the user by the terminal;

[1489] A system including:

[1490] (Claim 2)

[1491] The system of claim 1, wherein the generative AI model uses user information to analyze the user's characteristics and aptitudes and provide personality assessments and suggestions for future careers.

[1492] (Claim 3)

[1493] The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links.

[1494] "Application Example 1"

[1495] (Claim 1)

[1496] a means for collecting user-entered information;

[1497] means for transmitting the collected user information to a server;

[1498] A means for analyzing the user information received by the server using a generative AI model;

[1499] A means for transmitting the analysis results of the generative AI model from the server to the terminal;

[1500] means for displaying the transmitted analysis results to the user by the terminal;

[1501] A means for displaying the analysis results transmitted by the terminal on a guidance device in the physical store;

[1502] A means for inputting user information and displaying analysis results using a robot in a physical store;

[1503] A means of providing additional information through dedicated consultation booths and terminals, and

[1504] A system including:

[1505] (Claim 2)

[1506] The system of claim 1, wherein the generative AI model suggests personality assessments and future careers based on user information.

[1507] (Claim 3)

[1508] The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links.

[1509] "Example 2: Combining Emotion Engines"

[1510] (Claim 1)

[1511] means for collecting user input information and emotion data;

[1512] means for transmitting the collected user information and emotion data to a server;

[1513] A means for analyzing the user information and emotion data received by the server using a generation AI model and an emotion analysis engine;

[1514] A means for transmitting the analysis results of the generative AI model and the emotion analysis engine from the server to the terminal;

[1515] a means for visually displaying the transmitted analysis results to a user by the terminal;

[1516] A system including:

[1517] (Claim 2)

[1518] 10. The system of claim 1, wherein the generative AI model and sentiment analysis engine suggest personality assessments and future careers based on user information and sentiment data.

[1519] (Claim 3)

[1520] The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links.

[1521] "Application example 2 when combining emotion engines"

[1522] (Claim 1)

[1523] a means for collecting user-entered information;

[1524] means for transmitting the collected user information and emotion data to a server;

[1525] A means for analyzing the user information and emotion data received by the server using a generative AI model;

[1526] A means for transmitting the analysis results of the generative AI model from the server to the terminal;

[1527] means for displaying the transmitted analysis results to the user by the terminal;

[1528] A means for collecting emotional data such as facial expressions and voice of a user;

[1529] A means to personalize the analysis results based on the collected emotional data;

[1530] A system including:

[1531] (Claim 2)

[1532] The system of claim 1, wherein the generative AI model suggests a personality diagnosis and future careers or products based on user information.

[1533] (Claim 3)

[1534] The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links. [Explanation of symbols]

[1535] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for collecting user-entered information; means for transmitting the collected user information to a server; A means for analyzing the user information received by the server using a generative AI model; A means for transmitting the analysis results of the generative AI model from the server to the terminal; means for displaying the transmitted analysis results to the user by the terminal; A system including:

2. The system of claim 1, wherein the generative AI model suggests personality assessments and future careers based on user information.

3. The system according to claim 1, further comprising means for displaying the analysis results as concrete images or video links.

Images