System

Abstract

A system is provided.SOLUTION: A system includes an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommendation content according to a user target, and a display means for displaying the generated recommendation content.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, personal ability development and the acquisition of new skills are important, but many people are unsure of which information to choose and how to proceed with their learning. Furthermore, with the development of generative AI, more advanced skills and knowledge are required. Given this background, there is a need to provide optimal learning content and information for individual users and help them effectively achieve their goals. The purpose of this invention is to address these challenges by providing a system that supports users in obtaining qualifications and acquiring hobbies and special skills. [Means for solving the problem]

[0005] The present invention provides a system including an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommended content according to the user's goals, and a display means for displaying the generated recommended content, thereby enabling users to smoothly obtain information and learning resources that are optimal for their goals and effectively achieve their goals.

[0006] "User information" refers to basic information about a user, specifically data such as name, age, occupation, areas of interest, and goals.

[0007] "Input means" refers to the interface or device that a user uses to provide information to a system, and specifically includes a keyboard, touch screen, voice input, etc.

[0008] The "transmission means" refers to a function or process for transmitting user information obtained from the input means to a server or other system.

[0009] The "receiving means" refers to a function or process for receiving user information sent via the transmitting means.

[0010] The "analysis means" refers to an algorithm or model for analyzing the user information received by the receiving means and generating recommended content according to the user's goals.

[0011] "Recommended content" refers to information and resources selected to help users achieve their goals, such as study materials, success stories, recommended study schedules, and cost information.

[0012] "Display means" refers to an interface or device for visually presenting the generated recommended content to the user, and specifically includes a display, monitor, tablet screen, etc. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0035] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0036] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0037] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0038] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0039] The server receives this information and inputs it into the AI ​​model, which generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'."

[0040] The recommended content generated in this way is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, acquiring hobbies, and acquiring special skills.

[0041] The processing flow will be explained below.

[0042] Step 1:

[0043] A user accesses the system and logs in. The user logs in to the system by entering their account information (username, password) and clicking the login button. After that, the user is redirected to the dashboard.

[0044] Step 2:

[0045] The terminal displays an input form to the user, which includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0046] Step 3:

[0047] The user completes the input and clicks the submit button. The device sends the entered user information to the server, using an HTTPS request for security.

[0048] Step 4:

[0049] The server receives the user information and stores it in an internal database. The received data is stored in an appropriate location for use in analysis.

[0050] Step 5:

[0051] The server inputs the stored user information into the AI ​​model, specifically, passing data about the user's name, age, occupation, areas of interest, and goals to the AI ​​analysis algorithm.

[0052] Step 6:

[0053] The AI ​​model analyzes user information and generates recommended content that best suits the user's goals, including relevant learning materials, success stories, recommended study schedules, and required cost information.

[0054] Step 7:

[0055] The generated recommended content is sent from the server to the device, again using HTTPS requests for security.

[0056] Step 8:

[0057] The device receives the recommended content from the server and displays it to the user, who can then view the content and create a specific action plan to achieve their goals.

[0058] Step 9:

[0059] The user can then take action based on the recommended content provided. For example, the user can create a specific study plan to obtain a programming qualification and proceed with the study using the recommended learning materials. In this way, the system supports the user in achieving their goals.

[0060] Example 1

[0061] 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."

[0062] In conventional systems, the acquisition, storage, and analysis of user information, as well as the provision of optimal recommended content, were complex and inconsistent. Furthermore, the utilization of AI models to provide appropriate learning materials and plans was insufficient, resulting in a significant amount of time and effort required for users to achieve their goals. As a result, it was difficult for users to efficiently use the optimal resources according to their goals.

[0063] 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.

[0064] In this invention, the server includes a storage means for storing received user information in a database, an input means for inputting the stored user information into a generative AI model, and a generation means for generating recommended content according to the user's goals. This allows efficient management of user information and automatic generation of optimal recommended content, enabling the user to effectively start taking action toward their goals.

[0065] "User Information" is personal data about a user, such as name, age, occupation, areas of interest, goals, etc.

[0066] An "input means" is the interface that a user uses to enter information, typically a web form or an application input screen.

[0067] The "transmission means" is a mechanism for transmitting the input user information to the server, and is, for example, a process that uses an HTTP request.

[0068] The "receiving means" is a mechanism by which the server receives the transmitted user information, such as an API endpoint on the server side.

[0069] "Storage" refers to the process of recording received user information in persistent storage such as a database.

[0070] "Input means" refers to the mechanism for inputting stored user information into the generative AI model, a process that includes data format conversion and transmission.

[0071] A "generative AI model" is an artificial intelligence model that analyzes user information and generates recommended content based on the user's goals.

[0072] "Generation means" refers to the process by which the generative AI model generates recommended content based on user information.

[0073] A "prompt sentence" is an input sentence that provides the generative AI model with conditions such as user information and goals, and generates optimal content.

[0074] The "display means" is a mechanism for displaying the generated recommended content to the user, such as the screen of a web browser or a mobile app.

[0075] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0076] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0077] The server receives the user information and stores it in an internal database. Specifically, it uses a relational database management system (RDBMS) such as MySQL to store each piece of information in a corresponding table. The server then inputs the stored user information into a generative AI model. The AI ​​model uses a deep learning framework such as TensorFlow or PyTorch.

[0078] The generative AI model analyzes the input user information and generates recommended content based on the user's goals, including learning materials, success stories, recommended study schedules, and cost information.

[0079] The generated recommended content is sent from the server to the device. The device then displays the received recommended content to the user in an easy-to-read format using HTML and CSS. Based on this information, the user can make specific study plans and make the necessary preparations.

[0080] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0081] The server receives this information and inputs it into an AI model, which generates recommended content such as:

[0082] Recommended programming material: 'Introduction to Python'

[0083] Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0084] Recommended schedule: 'Study for 1 hour every day'

[0085] Budget: 'About 30,000 yen for study materials and exam fees'

[0086] The generated recommended content is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, pursuing hobbies, and acquiring special skills.

[0087] An example of a prompt to input to a generative AI model is:

[0088] "User information: Name (Taro Tanaka), Age (30), Occupation (Engineer), Area of ​​Interest (Programming), Goal (Obtaining a programming qualification). Please generate recommended learning materials, success stories, study schedule, and required cost information for this user."

[0089] Based on these prompts, the AI ​​model generates recommended content tailored to the user, enabling the system to efficiently initiate concrete actions toward acquiring qualifications, hobbies, or special skills.

[0090] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0091] Step 1:

[0092] A user accesses the system and logs in.

[0093] A user opens a browser or application, enters their username and password, and clicks the login button. Input: Username, Password. Output: Authentication result (success or failure).

[0094] Step 2:

[0095] After logging in, the device displays a basic information input form.

[0096] A form for entering user information displays fields such as name, age, occupation, interests, goals, etc. Input: Login successful. Output: Basic information input form.

[0097] Step 3:

[0098] The user enters information and clicks the submit button.

[0099] The entered information is temporarily stored in the device's memory. Input: Name, age, occupation, areas of interest, goals. Output: Entered user information.

[0100] Step 4:

[0101] The terminal transmits the input information to the server.

[0102] The terminal encodes the user information in JSON format and sends it to the server as an HTTP request. Input: Entered user information. Output: HTTP request to the server.

[0103] Step 5:

[0104] The server stores the received user information in a database.

[0105] The server receives the HTTP request, parses it, and writes it to a database. Specifically, it uses an RDBMS such as MySQL to store the information in the corresponding table. Input: HTTP request to the server. Output: User information stored in the database.

[0106] Step 6:

[0107] The user information stored by the server is input into the generative AI model.

[0108] The server retrieves user information from the database, converts it into a format suitable for the generative AI model, and inputs it. For example, a Python script is used to pass JSON format data to the AI ​​model. Input: User information stored in the database. Output: Data input to the generative AI model.

[0109] Step 7:

[0110] A generative AI model generates recommended content based on user goals.

[0111] A generative AI model analyzes input data and generates recommended content based on the user's goals. For example, a model built using TensorFlow or PyTorch might generate "recommended programming materials," "success stories," "recommended study schedules," and "necessary cost information." Input: Data input into the generative AI model. Output: Generated recommended content.

[0112] Step 8:

[0113] The server transmits the generated recommended content to the terminal.

[0114] The server sends the recommended content obtained from the generative AI model to the device in JSON format. This communication also uses a secure protocol (HTTPS). Input: Generated recommended content. Output: HTTP response to the device.

[0115] Step 9:

[0116] The terminal displays the received recommended content to the user.

[0117] The device analyzes the received recommended content and displays it in the user interface using HTML and CSS. Input: HTTP response to the device. Output: Recommended content displayed to the user.

[0118] Step 10:

[0119] The user views the displayed recommended content and begins to take action.

[0120] The user checks the recommended content displayed on the device and begins studying, preparing, or other actions based on the content. For example, they purchase the recommended learning materials and start studying for one hour every day. Input: Recommended content displayed to the user. Output: The user's specific action plan.

[0121] (Application example 1)

[0122] 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."

[0123] Conventional learning support systems lacked optimal learning plans and progress management based on individual user needs, and were unable to provide timely notifications or support to users. They also lacked the functionality to track users' learning progress in real time and suggest further learning content based on that information. This made it difficult for users to maintain their own learning pace.

[0124] 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.

[0125] In this invention, the server includes input means for inputting user information, transmission means for transmitting the input user information, reception means for receiving the transmitted user information, analysis means for analyzing the received user information and generating recommended content according to the user's goals, display means for displaying the generated recommended content, notification means for transmitting notifications based on the recommended study schedule, and progress management means for tracking the user's study progress. This enables study support tailored to the individual needs of the user, realizes notifications and progress management at appropriate times, and improves the user's study efficiency.

[0126] "User Information" refers to information such as name, age, occupation, areas of interest, goals, etc. that a user enters into the system.

[0127] "Input means" refers to a form or device that allows a user to input various information into the system.

[0128] "Transmission means" refers to communication means for transmitting input user information to the server.

[0129] "Receiving means" refers to a communication means by which the server receives the transmitted user information.

[0130] "Analysis means" refers to a processing device or algorithm for analyzing received user information and generating recommended content according to the user's goals.

[0131] "Recommended content" refers to information such as learning materials, success stories, recommended study schedules, and necessary cost information provided to help users achieve their goals.

[0132] The "display means" refers to a device or interface for visually presenting the generated recommended content to the user.

[0133] "Notification Method" refers to a communication method or software for sending notifications to the user at appropriate times based on the recommended study schedule.

[0134] "Progress management means" refers to a system or function for tracking the learning and completed tasks of a user and managing their progress.

[0135] "Server" refers to a central processing unit that receives and analyzes user information and generates recommended content.

[0136] The present invention relates to a system that inputs and analyzes user information and provides recommended content according to the user's goals. First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the send button, which sends the entered information from the terminal to a server.

[0137] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes study materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0138] Based on the recommended study schedule, the notification system sends notifications to the user at appropriate times. The notifications include reminders based on the study content and progress. The device also tracks the user's study progress and sends that information to the server in real time. The server can use this data to provide more accurate content recommendations.

[0139] The hardware used to implement this invention is the user's smartphone. The server side uses Python and Flask to build an API, which sends push notifications via Firebase. A generative AI model is used as software for data processing and calculation.

[0140] As a concrete example, consider the case where a user has the goal of "obtaining a programming qualification." In this case, the user enters their name, age, occupation, area of ​​interest (programming), and goal (obtaining a programming qualification). The server receives this information and inputs it into the AI ​​model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Approximately 30,000 yen for materials and exam fees'." This recommended content is displayed to the user through their device.

[0141] Examples of prompt sentences are shown below.

[0142] User information: Name = User A, Age = 25, Occupation = Engineer, Area of ​​interest = Programming, Goal = Python certification

[0143] Generate recommended content based on user goals.

[0144] Expected output:

[0145] 1. Recommended programming textbook: 'Introduction to Python'

[0146] 2. Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0147] 3. Recommended schedule: 'Study for one hour every day'

[0148] 4. Cost information: 'Textbooks and exam fees will cost approximately 30,000 yen.'

[0149] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0150] Step 1:

[0151] The user logs in and accesses the terminal.

[0152] (Operation description)

[0153] The user starts the system, accesses the login screen, and enters the required authentication information. If the login is successful, the user proceeds to the next user information input screen.

[0154] Step 2:

[0155] The user enters basic information and clicks the submit button.

[0156] (Operation description)

[0157] The terminal displays an input form for the user, asking for information such as name, age, occupation, areas of interest, and goals. The user enters this information into the input form and clicks the submit button. The entered information is converted into a data format and sent from the terminal to the server.

[0158] (Input) Information entered by the user into the input form (name, age, occupation, areas of interest, goals).

[0159] (Output) The user information sent.

[0160] Step 3:

[0161] The server receives the transmitted user information and stores it in an internal database.

[0162] (Operation description)

[0163] The server receives the user information sent from the device and stores it in an internal database. When storing the information, it checks the data format and detects duplicate data.

[0164] (Input) User information sent from the terminal.

[0165] (Output) User information stored in the internal database.

[0166] Step 4:

[0167] The server inputs the stored user information into the AI ​​model to generate recommended content.

[0168] (Operation description)

[0169] The server retrieves user information from an internal database and inputs it into a generative AI model. The AI ​​model uses prompts to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0170] (Input) User information retrieved from the database.

[0171] (Output) The generated recommended content.

[0172] Step 5:

[0173] The generated recommended content is sent to the terminal and displayed.

[0174] (Operation description)

[0175] The server sends the generated recommended content to the device, which then constructs a UI to display the received recommended content to the user and presents it visually.

[0176] (Input) The generated recommended content.

[0177] (Output) The recommended content that is displayed to the user.

[0178] Step 6:

[0179] Send notifications based on a recommended study schedule.

[0180] (Operation description)

[0181] Based on the recommended study schedule, the server uses a push notification service such as Firebase to send notifications to the user at the appropriate time, including study content and important reminders.

[0182] (Input) Recommended study schedule.

[0183] (Output) The notification sent to the user.

[0184] Step 7:

[0185] The user's learning progress is tracked and sent to the server.

[0186] (Operation description)

[0187] The device tracks the user's learning activities in real time and periodically transmits progress data to the server, which stores the received progress data in a database and updates the user information.

[0188] (Input) User's learning progress information.

[0189] (Output) Progress data and updated user information sent to the server.

[0190] Step 8:

[0191] The server provides more accurate recommended content based on the updated user information.

[0192] (Operation description)

[0193] The server uses the saved progress data to re-use the AI ​​model to generate even more accurate recommended content and provide it to the user.

[0194] (Input) Updated user information.

[0195] (Output) New, highly accurate recommended content.

[0196] 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.

[0197] The present invention relates to a system that inputs and analyzes user information and provides optimal recommended content, and further provides more personalized support by combining it with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0198] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0199] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0200] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0201] Furthermore, the present invention incorporates an emotion engine. The emotion engine analyzes facial expressions and voice when the user inputs information to recognize the user's emotions. For example, it uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time and identifies their emotional state (joy, sadness, surprise, anger, etc.).

[0202] The recognized emotional information is sent to the server and considered by the analysis means. The server then adjusts the recommended content based on this emotional information. For example, if the user is feeling stressed, the server will provide recommended content including relaxing study methods and encouraging messages. If the user is excited, the server will provide an efficient study plan that utilizes concentration.

[0203] As a concrete example, consider a case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0204] The server receives this information and emotion data and inputs it into an AI model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'," and adjusts the content according to the user's emotions.

[0205] The recommended content generated in this way is displayed to the user via their device. Based on this information, the user can make specific study plans and make the necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications and acquiring hobbies and special skills. The introduction of an emotion engine enables more personalized support, with the goal of improving user satisfaction and success rates.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] A user accesses the system and logs in. The user enters their account information (user name, password) and clicks the login button. This action redirects the user to the dashboard.

[0209] Step 2:

[0210] The terminal displays a basic information input form to the user. The form includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0211] Step 3:

[0212] The terminal displays a send button to send the information entered by the user. When the user clicks the send button, the entered user information is sent from the terminal to the server. This transmission is performed using the HTTPS protocol to ensure security.

[0213] Step 4:

[0214] The server receives the transmitted user information and stores it in an internal database, which is used by subsequent analysis means.

[0215] Step 5:

[0216] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and the collected data is sent to the emotion engine.

[0217] Step 6:

[0218] The emotion engine analyzes the captured facial and voice data to recognize the user's emotions, for example, whether the user is nervous or excited.

[0219] Step 7:

[0220] The emotion engine sends the recognized emotion data to the server, which receives the emotion data and stores it in a database along with user information.

[0221] Step 8:

[0222] The server inputs the stored user information and emotional data into the AI ​​model, which then uses this data to generate optimal content recommendations based on the user's goals.

[0223] Step 9:

[0224] The recommended content generated by the AI ​​model includes learning materials, success stories, recommended study schedules, and cost information, and the content is also tailored to the user's emotions.

[0225] Step 10:

[0226] The server then sends the generated recommendations to the device, again using the HTTPS protocol.

[0227] Step 11:

[0228] The device displays the received recommended content to the user, who can then view the displayed content and create a specific action plan.

[0229] Step 12:

[0230] The user can then take action based on the recommended content displayed. For example, the user can purchase the recommended learning materials and study in a planned manner every day, thereby taking steps toward achieving their goal.

[0231] In this way, the system of the present invention effectively supports users in obtaining qualifications and acquiring hobbies and special skills, and by introducing an emotion engine, can provide even more personalized support.

[0232] Example 2

[0233] 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."

[0234] Conventional content recommendation systems based on user information lack personalization that takes into account the user's emotional state, and have had the problem of not being able to sufficiently increase user satisfaction or goal achievement rates. In particular, when a user is feeling stressed or tense, providing content that ignores that state will not be effective.

[0235] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommended content according to the user's goals, and a display means for displaying the generated recommended content. This enables detailed personalization according to the user's status.

[0236] "User information" refers to personal information and attribute information of a user, specifically including name, age, occupation, areas of interest, goals, and the like.

[0237] "Input means" refers to the means by which a user inputs information into a system, such as a form or interface.

[0238] "Transmission means" refers to a means for transmitting input data to other parts of the system, and specifically refers to a communication device or a network interface.

[0239] "Receiving means" refers to a means for receiving data sent from outside, and specifically refers to a communication device or a network interface.

[0240] "Analysis means" refers to the means for analyzing the received data and generating appropriate output, and specifically refers to a data analysis device or software algorithm.

[0241] "Recommended content" refers to content generated by the analysis means to support the user in achieving their goals, and includes study materials, success stories, recommended study schedules, necessary cost information, and the like.

[0242] The "display means" refers to a means for displaying the generated recommended content to the user, and specifically refers to a monitor, browser screen, or the like.

[0243] An "emotion engine" is an engine that recognizes a user's emotions and analyzes that information, and specifically refers to facial expression recognition and voice analysis technology using a camera and microphone.

[0244] "Emotion information receiving means" refers to means for receiving emotion information recognized by the emotion engine, and specifically refers to a communication device or a network interface.

[0245] The present invention relates to a system that inputs user information and provides recommended content in consideration of the information and the user's emotional state. An embodiment of this system will be described in detail below.

[0246] First, the user accesses the system using a browser or a dedicated application and logs in. The terminal displays a login screen, and the user logs in by entering account information (user name, password). If the login is successful, the user can access the system.

[0247] Next, the terminal displays a form for the user to enter basic information (name, age, occupation, areas of interest, goals). The user enters this information and clicks the submit button. This information is sent from the terminal to the server. The server receives the sent user information and stores it in an internal database. Possible databases used include MySQL and PostgreSQL.

[0248] The server then inputs the saved user information into an AI model to generate recommended content based on the user's goals. The AI ​​model used is OpenAI's GPT-4, among others. Recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays it to the user.

[0249] Furthermore, the present invention incorporates an emotion engine that analyzes the user's facial expressions and tone of voice when entering information. Using a camera and microphone installed on the device, the device monitors the user's facial expressions and voice in real time to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.). The analyzed emotion information is sent to the server. The server receives the emotion information and adjusts the recommended content based on this information.

[0250] Specifically, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0251] Specific examples of prompts are as follows:

[0252] "The user has stated that he wants to obtain a programming qualification. The user's basic information is: Name: Yamada Taro, Age: 25, Occupation: System Engineer, Area of ​​Interest: Python, Goal: Obtaining a Python qualification. The user is nervous while typing, and the emotion engine senses this. Please generate recommended content for the user."

[0253] This system allows users to receive specific and personalized support to achieve their goals. The introduction of an emotion engine enables appropriate recommendations that take into account the user's emotional state, which is expected to improve user satisfaction and success rates.

[0254] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0255] Step 1:

[0256] A user accesses the system using a browser or a dedicated application and logs in. As input, they enter their username and password into the terminal. The terminal sends the entered information to the server. The server receives this and compares it with the user authentication information in an internal database (e.g., MySQL). If authentication is successful, the server generates a session ID and returns it to the terminal. As output, the terminal displays the session ID if authentication is successful, or an error message if authentication is unsuccessful.

[0257] Step 2:

[0258] For users who have been successfully authenticated, the terminal displays a form for entering basic information such as name, age, occupation, areas of interest, and goals. The user enters this information into the form and clicks the submit button. The basic information entered by the user into the form is required as input. The terminal sends this information to the server in JSON format or similar. The server parses the received JSON data and stores it in a database. As output, a message confirming successful submission and the ability to move to the next step are displayed on the terminal.

[0259] Step 3:

[0260] The server uses the stored user information to send prompts to an AI model (e.g., OpenAI GPT-4). As input, the server needs to generate a prompt sentence based on the user information. The server sends the prompt sentence to the AI ​​model, which then generates recommended content based on the user's goals. As output, the AI ​​model returns recommended content including learning materials, success stories, study schedules, and required cost information. The server receives this recommended content.

[0261] Step 4:

[0262] The server sends the generated recommended content to the device. As input, the recommended content received from the AI ​​model is required. The server sends this data to the device in JSON format. The device parses the received JSON data and displays it to the user in an appropriate format. The user views the displayed recommended content and begins taking action toward learning or achieving their goal. As output, the recommended content is displayed on the device.

[0263] Step 5:

[0264] The device uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time while the user is entering information. As input, the device requires the user's facial expression data and voice data. The device sends these data to an emotion analysis engine to identify the user's emotional state. The emotion analysis results are sent to the server in JSON format. As output, the emotional state (such as joy, sadness, surprise, or anger) is identified and sent to the server.

[0265] Step 6:

[0266] The server receives the emotional information and adjusts the recommended content. As input, it requires the result of the emotional analysis. The server runs the received emotional data through an analytical method to generate a new prompt with additional information and adjustments according to the user's emotions. The server then sends this new prompt to the AI ​​model again to generate recommended content according to the emotions. As output, the newly adjusted recommended content is generated.

[0267] Step 7:

[0268] The server sends the final recommended content to the device and displays it to the user. As input, tailored recommended content is required. The server sends the content to the device in JSON format, and the device redisplays the received content. The user can then adjust their learning plan or behavior based on this. As output, the final personalized recommended content is displayed on the device.

[0269] (Application example 2)

[0270] 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."

[0271] In recent years, with the digitalization of markets and the spread of virtual shopping, there has been an increasing demand for personalized support systems that respond to individual users' preferences and emotions. However, conventional systems are unable to recognize users' emotions in real time and dynamically adjust service content based on that, limiting the improvement of user experience. Therefore, there is a need for a system that provides optimal product recommendations and shopping support in virtual stores based on user information and real-time emotional state.

[0272] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0273] In this invention, the server includes an analysis means for analyzing input user information and generating recommended content according to the user's goals, an emotion recognition means for recognizing and considering the user's emotions in real time, and an adjustment means for adjusting the recommended content based on the user's emotion recognition information, thereby enabling dynamic generation and provision of recommended content according to the user's emotional state.

[0274] "User Information" is information about an individual, such as the user's name, age, occupation, areas of interest, goals, etc.

[0275] "Input means" refers to a device or interface for inputting user information.

[0276] "Transmission means" refers to a mechanism for transmitting input user information to a server.

[0277] "Receiving means" refers to a function for receiving user information on the server side.

[0278] The "analysis means" includes an engine or algorithm for analyzing received user information and generating recommended content based on that information.

[0279] The "display means" refers to a display device or digital screen for visually presenting the generated recommended content to the user.

[0280] "Emotion recognition means" refers to technology or devices that recognize emotions in real time from a user's facial expressions, voice, etc.

[0281] The "adjustment means" has the function of dynamically changing and adjusting recommended content based on the recognized emotional information.

[0282] "Recommended content" refers to learning materials, successful people's experiences, recommended study schedules, necessary cost information, etc., provided based on analyzed user information and emotional state.

[0283] The present invention is a system that inputs and analyzes user information to provide optimal recommended content, and further recognizes the user's emotions in real time and adaptively adjusts the recommended content based on the emotions. An embodiment of this system will be described in detail below.

[0284] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0285] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into a generative AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0286] Furthermore, the present invention incorporates an emotion recognition means. The emotion recognition means monitors the user's facial expressions and voice in real time when inputting information, and identifies the user's emotional state (joy, sadness, surprise, anger, etc.). The recognized emotion information is sent to the server and considered by the analysis means. The server adjusts the recommended content based on this emotion information. For example, if the user is feeling stressed, the server may provide recommended content including relaxing content, and if the user is excited, the server may provide an efficient study plan that utilizes the user's concentration.

[0287] As an actual use case, consider a case where a user has the goal of "buying the latest gadget." In this case, the information the user inputs includes name, age, occupation, area of ​​interest (latest gadgets), goal (buying the latest gadget), etc. The emotion recognition means detects the emotional state of the user when inputting and provides recommended content accordingly. For example, if the user is in an excited state, it generates recommended content that introduces particularly noteworthy new products.

[0288] To realize the system of this invention, the following hardware and software are required. The hardware requires a terminal equipped with a camera and microphone for inputting user information and recognizing emotions. The software includes face recognition using Python and OpenCV, a generative AI model using TensorFlow, and emotion analysis using Transformers. Specifically, OpenCV is used for analyzing user facial expressions, and a Transformers model is used for emotion recognition. A generative AI model using TensorFlow is used to generate recommended content.

[0289] An example prompt is:

[0290] "If a user is interested in the latest gadget and is looking to buy it, the system will generate appropriate content recommendations based on the user's profile information and real-time emotional state."

[0291] As a result, the system of the present invention is able to provide a more personalized service that responds to the individual needs and emotional state of the user.

[0292] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0293] Step 1:

[0294] A user accesses the system and logs in.

[0295] Specifically, the user enters and submits account information (user name, password). This information is then sent to the server, which performs authentication and starts a session if the authentication is successful.

[0296] Input: Username, Password

[0297] Output: Authentication result (success / failure), session start

[0298] Step 2:

[0299] The device displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals.

[0300] Specifically, the terminal displays a form, and after the user has finished entering information, they click the submit button, which is then sent from the terminal to the server.

[0301] Input: User basic information (name, age, occupation, areas of interest, goals)

[0302] Output: User information sent to the server

[0303] Step 3:

[0304] The server receives the transmitted user information and stores it in an internal database.

[0305] Specifically, the server converts the user information into an analyzable format and stores it in a database.

[0306] Input: Submitted user basic information

[0307] Output: User information stored in the internal database

[0308] Step 4:

[0309] The server inputs the stored user information into a generative AI model to generate recommended content based on the user's goals.

[0310] Specifically, the server inputs user information into the AI ​​model and generates recommended content such as learning materials, success stories, recommended study schedules, and necessary cost information.

[0311] Input: User information

[0312] Output: Generated recommended content

[0313] Step 5:

[0314] The generated recommended content is transmitted from the server to the terminal, and the terminal displays the received recommended content to the user.

[0315] Specifically, the server transmits the recommended content to the terminal, which then visually displays the content.

[0316] Input: Generated recommended content

[0317] Output: Recommended content displayed to the user

[0318] Step 6:

[0319] An emotion recognition means monitors the user's facial expressions and voice in real time to identify their emotional state.

[0320] Specifically, the system uses the device's built-in camera and microphone to collect the user's facial expressions and voice data, and analyzes their emotional state using an emotion analysis model.

[0321] Input: User facial and voice data

[0322] Output: Perceived emotional state

[0323] Step 7:

[0324] The recognized emotion information is transmitted to the server and taken into account by the analysis means.

[0325] Specifically, the server receives the user's emotion information and adjusts the recommended content based on the analysis algorithm.

[0326] Input: Emotion information

[0327] Output: Tailored recommended content

[0328] Step 8:

[0329] The adjusted recommended content is sent again to the terminal, which then displays it again to the user.

[0330] Specifically, the server transmits the adjusted recommended content to the terminal, and the terminal displays the new content.

[0331] Input: Tailored recommended content

[0332] Output: Recommended content redisplayed to the user

[0333] 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.

[0334] 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.

[0335] 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.

[0336] [Second embodiment]

[0337] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0338] 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.

[0339] 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).

[0340] 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.

[0341] 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.

[0342] 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).

[0343] 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.

[0344] 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.

[0345] 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.

[0346] 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.

[0347] 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.

[0348] 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."

[0349] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0350] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0351] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0352] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0353] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0354] The server receives this information and inputs it into the AI ​​model, which generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'."

[0355] The recommended content generated in this way is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, acquiring hobbies, and acquiring special skills.

[0356] The processing flow will be explained below.

[0357] Step 1:

[0358] A user accesses the system and logs in. The user logs in to the system by entering their account information (username, password) and clicking the login button. After that, the user is redirected to the dashboard.

[0359] Step 2:

[0360] The terminal displays an input form to the user, which includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0361] Step 3:

[0362] The user completes the input and clicks the submit button. The device sends the entered user information to the server, using an HTTPS request for security.

[0363] Step 4:

[0364] The server receives the user information and stores it in an internal database. The received data is stored in an appropriate location for use in analysis.

[0365] Step 5:

[0366] The server inputs the stored user information into the AI ​​model, specifically, passing data about the user's name, age, occupation, areas of interest, and goals to the AI ​​analysis algorithm.

[0367] Step 6:

[0368] The AI ​​model analyzes user information and generates recommended content that best suits the user's goals, including relevant learning materials, success stories, recommended study schedules, and required cost information.

[0369] Step 7:

[0370] The generated recommended content is sent from the server to the device, again using HTTPS requests for security.

[0371] Step 8:

[0372] The device receives the recommended content from the server and displays it to the user, who can then view the content and create a specific action plan to achieve their goals.

[0373] Step 9:

[0374] The user can then take action based on the recommended content provided. For example, the user can create a specific study plan to obtain a programming qualification and proceed with the study using the recommended learning materials. In this way, the system supports the user in achieving their goals.

[0375] Example 1

[0376] 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."

[0377] In conventional systems, the acquisition, storage, and analysis of user information, as well as the provision of optimal recommended content, were complex and inconsistent. Furthermore, the utilization of AI models to provide appropriate learning materials and plans was insufficient, resulting in a significant amount of time and effort required for users to achieve their goals. As a result, it was difficult for users to efficiently use the optimal resources according to their goals.

[0378] 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.

[0379] In this invention, the server includes a storage means for storing received user information in a database, an input means for inputting the stored user information into a generative AI model, and a generation means for generating recommended content according to the user's goals. This allows efficient management of user information and automatic generation of optimal recommended content, enabling the user to effectively start taking action toward their goals.

[0380] "User Information" is personal data about a user, such as name, age, occupation, areas of interest, goals, etc.

[0381] An "input means" is the interface that a user uses to enter information, typically a web form or an application input screen.

[0382] The "transmission means" is a mechanism for transmitting the input user information to the server, and is, for example, a process that uses an HTTP request.

[0383] The "receiving means" is a mechanism by which the server receives the transmitted user information, such as an API endpoint on the server side.

[0384] "Storage" refers to the process of recording received user information in persistent storage such as a database.

[0385] "Input means" refers to the mechanism for inputting stored user information into the generative AI model, a process that includes data format conversion and transmission.

[0386] A "generative AI model" is an artificial intelligence model that analyzes user information and generates recommended content based on the user's goals.

[0387] "Generation means" refers to the process by which the generative AI model generates recommended content based on user information.

[0388] A "prompt sentence" is an input sentence that provides the generative AI model with conditions such as user information and goals, and generates optimal content.

[0389] The "display means" is a mechanism for displaying the generated recommended content to the user, such as the screen of a web browser or a mobile app.

[0390] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0391] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0392] The server receives the user information and stores it in an internal database. Specifically, it uses a relational database management system (RDBMS) such as MySQL to store each piece of information in a corresponding table. The server then inputs the stored user information into a generative AI model. The AI ​​model uses a deep learning framework such as TensorFlow or PyTorch.

[0393] The generative AI model analyzes the input user information and generates recommended content based on the user's goals, including learning materials, success stories, recommended study schedules, and cost information.

[0394] The generated recommended content is sent from the server to the device. The device then displays the received recommended content to the user in an easy-to-read format using HTML and CSS. Based on this information, the user can make specific study plans and make the necessary preparations.

[0395] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0396] The server receives this information and inputs it into an AI model, which generates recommended content such as:

[0397] Recommended programming material: 'Introduction to Python'

[0398] Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0399] Recommended schedule: 'Study for 1 hour every day'

[0400] Budget: 'About 30,000 yen for study materials and exam fees'

[0401] The generated recommended content is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, pursuing hobbies, and acquiring special skills.

[0402] An example of a prompt to input to a generative AI model is:

[0403] "User information: Name (Taro Tanaka), Age (30), Occupation (Engineer), Area of ​​Interest (Programming), Goal (Obtaining a programming qualification). Please generate recommended learning materials, success stories, study schedule, and required cost information for this user."

[0404] Based on these prompts, the AI ​​model generates recommended content tailored to the user, enabling the system to efficiently initiate concrete actions toward acquiring qualifications, hobbies, or special skills.

[0405] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0406] Step 1:

[0407] A user accesses the system and logs in.

[0408] A user opens a browser or application, enters their username and password, and clicks the login button. Input: Username, Password. Output: Authentication result (success or failure).

[0409] Step 2:

[0410] After logging in, the device displays a basic information input form.

[0411] A form for entering user information displays fields such as name, age, occupation, interests, goals, etc. Input: Login successful. Output: Basic information input form.

[0412] Step 3:

[0413] The user enters information and clicks the submit button.

[0414] The entered information is temporarily stored in the device's memory. Input: Name, age, occupation, areas of interest, goals. Output: Entered user information.

[0415] Step 4:

[0416] The terminal transmits the input information to the server.

[0417] The terminal encodes the user information in JSON format and sends it to the server as an HTTP request. Input: Entered user information. Output: HTTP request to the server.

[0418] Step 5:

[0419] The server stores the received user information in a database.

[0420] The server receives the HTTP request, parses it, and writes it to a database. Specifically, it uses an RDBMS such as MySQL to store the information in the corresponding table. Input: HTTP request to the server. Output: User information stored in the database.

[0421] Step 6:

[0422] The user information stored by the server is input into the generative AI model.

[0423] The server retrieves user information from the database, converts it into a format suitable for the generative AI model, and inputs it. For example, a Python script is used to pass JSON format data to the AI ​​model. Input: User information stored in the database. Output: Data input to the generative AI model.

[0424] Step 7:

[0425] A generative AI model generates recommended content based on user goals.

[0426] A generative AI model analyzes input data and generates recommended content based on the user's goals. For example, a model built using TensorFlow or PyTorch might generate "recommended programming materials," "success stories," "recommended study schedules," and "necessary cost information." Input: Data input into the generative AI model. Output: Generated recommended content.

[0427] Step 8:

[0428] The server transmits the generated recommended content to the terminal.

[0429] The server sends the recommended content obtained from the generative AI model to the device in JSON format. This communication also uses a secure protocol (HTTPS). Input: Generated recommended content. Output: HTTP response to the device.

[0430] Step 9:

[0431] The terminal displays the received recommended content to the user.

[0432] The device analyzes the received recommended content and displays it in the user interface using HTML and CSS. Input: HTTP response to the device. Output: Recommended content displayed to the user.

[0433] Step 10:

[0434] The user views the displayed recommended content and begins to take action.

[0435] The user checks the recommended content displayed on the device and begins studying, preparing, or other actions based on the content. For example, they purchase the recommended learning materials and start studying for one hour every day. Input: Recommended content displayed to the user. Output: The user's specific action plan.

[0436] (Application example 1)

[0437] 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."

[0438] Conventional learning support systems lacked optimal learning plans and progress management based on individual user needs, and were unable to provide timely notifications or support to users. They also lacked the functionality to track users' learning progress in real time and suggest further learning content based on that information. This made it difficult for users to maintain their own learning pace.

[0439] 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.

[0440] In this invention, the server includes input means for inputting user information, transmission means for transmitting the input user information, reception means for receiving the transmitted user information, analysis means for analyzing the received user information and generating recommended content according to the user's goals, display means for displaying the generated recommended content, notification means for transmitting notifications based on the recommended study schedule, and progress management means for tracking the user's study progress. This enables study support tailored to the individual needs of the user, realizes notifications and progress management at appropriate times, and improves the user's study efficiency.

[0441] "User Information" refers to information such as name, age, occupation, areas of interest, goals, etc. that a user enters into the system.

[0442] "Input means" refers to a form or device that allows a user to input various information into the system.

[0443] "Transmission means" refers to communication means for transmitting input user information to the server.

[0444] "Receiving means" refers to a communication means by which the server receives the transmitted user information.

[0445] "Analysis means" refers to a processing device or algorithm for analyzing received user information and generating recommended content according to the user's goals.

[0446] "Recommended content" refers to information such as learning materials, success stories, recommended study schedules, and necessary cost information provided to help users achieve their goals.

[0447] The "display means" refers to a device or interface for visually presenting the generated recommended content to the user.

[0448] "Notification Method" refers to a communication method or software for sending notifications to the user at appropriate times based on the recommended study schedule.

[0449] "Progress management means" refers to a system or function for tracking the learning and completed tasks of a user and managing their progress.

[0450] "Server" refers to a central processing unit that receives and analyzes user information and generates recommended content.

[0451] The present invention relates to a system that inputs and analyzes user information and provides recommended content according to the user's goals. First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the send button, which sends the entered information from the terminal to a server.

[0452] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes study materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0453] Based on the recommended study schedule, the notification system sends notifications to the user at appropriate times. The notifications include reminders based on the study content and progress. The device also tracks the user's study progress and sends that information to the server in real time. The server can use this data to provide more accurate content recommendations.

[0454] The hardware used to implement this invention is the user's smartphone. The server side uses Python and Flask to build an API, which sends push notifications via Firebase. A generative AI model is used as software for data processing and calculation.

[0455] As a concrete example, consider the case where a user has the goal of "obtaining a programming qualification." In this case, the user enters their name, age, occupation, area of ​​interest (programming), and goal (obtaining a programming qualification). The server receives this information and inputs it into the AI ​​model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Approximately 30,000 yen for materials and exam fees'." This recommended content is displayed to the user through their device.

[0456] Examples of prompt sentences are shown below.

[0457] User information: Name = User A, Age = 25, Occupation = Engineer, Area of ​​interest = Programming, Goal = Python certification

[0458] Generate recommended content based on user goals.

[0459] Expected output:

[0460] 1. Recommended programming textbook: 'Introduction to Python'

[0461] 2. Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0462] 3. Recommended schedule: 'Study for one hour every day'

[0463] 4. Cost information: 'Textbooks and exam fees will cost approximately 30,000 yen.'

[0464] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0465] Step 1:

[0466] The user logs in and accesses the terminal.

[0467] (Operation description)

[0468] The user starts the system, accesses the login screen, and enters the required authentication information. If the login is successful, the user proceeds to the next user information input screen.

[0469] Step 2:

[0470] The user enters basic information and clicks the submit button.

[0471] (Operation description)

[0472] The terminal displays an input form for the user, asking for information such as name, age, occupation, areas of interest, and goals. The user enters this information into the input form and clicks the submit button. The entered information is converted into a data format and sent from the terminal to the server.

[0473] (Input) Information entered by the user into the input form (name, age, occupation, areas of interest, goals).

[0474] (Output) The user information sent.

[0475] Step 3:

[0476] The server receives the transmitted user information and stores it in an internal database.

[0477] (Operation description)

[0478] The server receives the user information sent from the device and stores it in an internal database. When storing the information, it checks the data format and detects duplicate data.

[0479] (Input) User information sent from the terminal.

[0480] (Output) User information stored in the internal database.

[0481] Step 4:

[0482] The server inputs the stored user information into the AI ​​model to generate recommended content.

[0483] (Operation description)

[0484] The server retrieves user information from an internal database and inputs it into a generative AI model. The AI ​​model uses prompts to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0485] (Input) User information retrieved from the database.

[0486] (Output) The generated recommended content.

[0487] Step 5:

[0488] The generated recommended content is sent to the terminal and displayed.

[0489] (Operation description)

[0490] The server sends the generated recommended content to the device, which then constructs a UI to display the received recommended content to the user and presents it visually.

[0491] (Input) The generated recommended content.

[0492] (Output) The recommended content that is displayed to the user.

[0493] Step 6:

[0494] Send notifications based on a recommended study schedule.

[0495] (Operation description)

[0496] Based on the recommended study schedule, the server uses a push notification service such as Firebase to send notifications to the user at the appropriate time, including study content and important reminders.

[0497] (Input) Recommended study schedule.

[0498] (Output) The notification sent to the user.

[0499] Step 7:

[0500] The user's learning progress is tracked and sent to the server.

[0501] (Operation description)

[0502] The device tracks the user's learning activities in real time and periodically transmits progress data to the server, which stores the received progress data in a database and updates the user information.

[0503] (Input) User's learning progress information.

[0504] (Output) Progress data and updated user information sent to the server.

[0505] Step 8:

[0506] The server provides more accurate recommended content based on the updated user information.

[0507] (Operation description)

[0508] The server uses the saved progress data to re-use the AI ​​model to generate even more accurate recommended content and provide it to the user.

[0509] (Input) Updated user information.

[0510] (Output) New, highly accurate recommended content.

[0511] 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.

[0512] The present invention relates to a system that inputs and analyzes user information and provides optimal recommended content, and further provides more personalized support by combining it with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0513] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0514] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0515] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0516] Furthermore, the present invention incorporates an emotion engine. The emotion engine analyzes facial expressions and voice when the user inputs information to recognize the user's emotions. For example, it uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time and identifies their emotional state (joy, sadness, surprise, anger, etc.).

[0517] The recognized emotional information is sent to the server and considered by the analysis means. The server then adjusts the recommended content based on this emotional information. For example, if the user is feeling stressed, the server will provide recommended content including relaxing study methods and encouraging messages. If the user is excited, the server will provide an efficient study plan that utilizes concentration.

[0518] As a concrete example, consider a case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0519] The server receives this information and emotion data and inputs it into an AI model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'," and adjusts the content according to the user's emotions.

[0520] The recommended content generated in this way is displayed to the user via their device. Based on this information, the user can make specific study plans and make the necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications and acquiring hobbies and special skills. The introduction of an emotion engine enables more personalized support, with the goal of improving user satisfaction and success rates.

[0521] The processing flow will be explained below.

[0522] Step 1:

[0523] A user accesses the system and logs in. The user enters their account information (user name, password) and clicks the login button. This action redirects the user to the dashboard.

[0524] Step 2:

[0525] The terminal displays a basic information input form to the user. The form includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0526] Step 3:

[0527] The terminal displays a send button to send the information entered by the user. When the user clicks the send button, the entered user information is sent from the terminal to the server. This transmission is performed using the HTTPS protocol to ensure security.

[0528] Step 4:

[0529] The server receives the transmitted user information and stores it in an internal database, which is used by subsequent analysis means.

[0530] Step 5:

[0531] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and the collected data is sent to the emotion engine.

[0532] Step 6:

[0533] The emotion engine analyzes the captured facial and voice data to recognize the user's emotions, for example, whether the user is nervous or excited.

[0534] Step 7:

[0535] The emotion engine sends the recognized emotion data to the server, which receives the emotion data and stores it in a database along with user information.

[0536] Step 8:

[0537] The server inputs the stored user information and emotional data into the AI ​​model, which then uses this data to generate optimal content recommendations based on the user's goals.

[0538] Step 9:

[0539] The recommended content generated by the AI ​​model includes learning materials, success stories, recommended study schedules, and cost information, and the content is also tailored to the user's emotions.

[0540] Step 10:

[0541] The server then sends the generated recommendations to the device, again using the HTTPS protocol.

[0542] Step 11:

[0543] The device displays the received recommended content to the user, who can then view the displayed content and create a specific action plan.

[0544] Step 12:

[0545] The user can then take action based on the recommended content displayed. For example, the user can purchase the recommended learning materials and study in a planned manner every day, thereby taking steps toward achieving their goal.

[0546] In this way, the system of the present invention effectively supports users in obtaining qualifications and acquiring hobbies and special skills, and by introducing an emotion engine, can provide even more personalized support.

[0547] Example 2

[0548] 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."

[0549] Conventional content recommendation systems based on user information lack personalization that takes into account the user's emotional state, and have had the problem of not being able to sufficiently increase user satisfaction or goal achievement rates. In particular, when a user is feeling stressed or tense, providing content that ignores that state will not be effective.

[0550] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommended content according to the user's goals, and a display means for displaying the generated recommended content. This enables detailed personalization according to the user's status.

[0551] "User information" refers to personal information and attribute information of a user, specifically including name, age, occupation, areas of interest, goals, and the like.

[0552] "Input means" refers to the means by which a user inputs information into a system, such as a form or interface.

[0553] "Transmission means" refers to a means for transmitting input data to other parts of the system, and specifically refers to a communication device or a network interface.

[0554] "Receiving means" refers to a means for receiving data sent from outside, and specifically refers to a communication device or a network interface.

[0555] "Analysis means" refers to the means for analyzing the received data and generating appropriate output, and specifically refers to a data analysis device or software algorithm.

[0556] "Recommended content" refers to content generated by the analysis means to support the user in achieving their goals, and includes study materials, success stories, recommended study schedules, necessary cost information, and the like.

[0557] The "display means" refers to a means for displaying the generated recommended content to the user, and specifically refers to a monitor, browser screen, or the like.

[0558] An "emotion engine" is an engine that recognizes a user's emotions and analyzes that information, and specifically refers to facial expression recognition and voice analysis technology using a camera and microphone.

[0559] "Emotion information receiving means" refers to means for receiving emotion information recognized by the emotion engine, and specifically refers to a communication device or a network interface.

[0560] The present invention relates to a system that inputs user information and provides recommended content in consideration of the information and the user's emotional state. An embodiment of this system will be described in detail below.

[0561] First, the user accesses the system using a browser or a dedicated application and logs in. The terminal displays a login screen, and the user logs in by entering account information (user name, password). If the login is successful, the user can access the system.

[0562] Next, the terminal displays a form for the user to enter basic information (name, age, occupation, areas of interest, goals). The user enters this information and clicks the submit button. This information is sent from the terminal to the server. The server receives the sent user information and stores it in an internal database. Possible databases used include MySQL and PostgreSQL.

[0563] The server then inputs the saved user information into an AI model to generate recommended content based on the user's goals. The AI ​​model used is OpenAI's GPT-4, among others. Recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays it to the user.

[0564] Furthermore, the present invention incorporates an emotion engine that analyzes the user's facial expressions and tone of voice when entering information. Using a camera and microphone installed on the device, the device monitors the user's facial expressions and voice in real time to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.). The analyzed emotion information is sent to the server. The server receives the emotion information and adjusts the recommended content based on this information.

[0565] Specifically, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0566] Specific examples of prompts are as follows:

[0567] "The user has stated that he wants to obtain a programming qualification. The user's basic information is: Name: Yamada Taro, Age: 25, Occupation: System Engineer, Area of ​​Interest: Python, Goal: Obtaining a Python qualification. The user is nervous while typing, and the emotion engine senses this. Please generate recommended content for the user."

[0568] This system allows users to receive specific and personalized support to achieve their goals. The introduction of an emotion engine enables appropriate recommendations that take into account the user's emotional state, which is expected to improve user satisfaction and success rates.

[0569] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0570] Step 1:

[0571] A user accesses the system using a browser or a dedicated application and logs in. As input, they enter their username and password into the terminal. The terminal sends the entered information to the server. The server receives this and compares it with the user authentication information in an internal database (e.g., MySQL). If authentication is successful, the server generates a session ID and returns it to the terminal. As output, the terminal displays the session ID if authentication is successful, or an error message if authentication is unsuccessful.

[0572] Step 2:

[0573] For users who have been successfully authenticated, the terminal displays a form for entering basic information such as name, age, occupation, areas of interest, and goals. The user enters this information into the form and clicks the submit button. The basic information entered by the user into the form is required as input. The terminal sends this information to the server in JSON format or similar. The server parses the received JSON data and stores it in a database. As output, a message confirming successful submission and the ability to move to the next step are displayed on the terminal.

[0574] Step 3:

[0575] The server uses the stored user information to send prompts to an AI model (e.g., OpenAI GPT-4). As input, the server needs to generate a prompt sentence based on the user information. The server sends the prompt sentence to the AI ​​model, which then generates recommended content based on the user's goals. As output, the AI ​​model returns recommended content including learning materials, success stories, study schedules, and required cost information. The server receives this recommended content.

[0576] Step 4:

[0577] The server sends the generated recommended content to the device. As input, the recommended content received from the AI ​​model is required. The server sends this data to the device in JSON format. The device parses the received JSON data and displays it to the user in an appropriate format. The user views the displayed recommended content and begins taking action toward learning or achieving their goal. As output, the recommended content is displayed on the device.

[0578] Step 5:

[0579] The device uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time while the user is entering information. As input, the device requires the user's facial expression data and voice data. The device sends these data to an emotion analysis engine to identify the user's emotional state. The emotion analysis results are sent to the server in JSON format. As output, the emotional state (such as joy, sadness, surprise, or anger) is identified and sent to the server.

[0580] Step 6:

[0581] The server receives the emotional information and adjusts the recommended content. As input, it requires the result of the emotional analysis. The server runs the received emotional data through an analytical method to generate a new prompt with additional information and adjustments according to the user's emotions. The server then sends this new prompt to the AI ​​model again to generate recommended content according to the emotions. As output, the newly adjusted recommended content is generated.

[0582] Step 7:

[0583] The server sends the final recommended content to the device and displays it to the user. As input, tailored recommended content is required. The server sends the content to the device in JSON format, and the device redisplays the received content. The user can then adjust their learning plan or behavior based on this. As output, the final personalized recommended content is displayed on the device.

[0584] (Application example 2)

[0585] 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."

[0586] In recent years, with the digitalization of markets and the spread of virtual shopping, there has been an increasing demand for personalized support systems that respond to individual users' preferences and emotions. However, conventional systems are unable to recognize users' emotions in real time and dynamically adjust service content based on that, limiting the improvement of user experience. Therefore, there is a need for a system that provides optimal product recommendations and shopping support in virtual stores based on user information and real-time emotional state.

[0587] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0588] In this invention, the server includes an analysis means for analyzing input user information and generating recommended content according to the user's goals, an emotion recognition means for recognizing and considering the user's emotions in real time, and an adjustment means for adjusting the recommended content based on the user's emotion recognition information, thereby enabling dynamic generation and provision of recommended content according to the user's emotional state.

[0589] "User Information" is information about an individual, such as the user's name, age, occupation, areas of interest, goals, etc.

[0590] "Input means" refers to a device or interface for inputting user information.

[0591] "Transmission means" refers to a mechanism for transmitting input user information to a server.

[0592] "Receiving means" refers to a function for receiving user information on the server side.

[0593] The "analysis means" includes an engine or algorithm for analyzing received user information and generating recommended content based on that information.

[0594] The "display means" refers to a display device or digital screen for visually presenting the generated recommended content to the user.

[0595] "Emotion recognition means" refers to technology or devices that recognize emotions in real time from a user's facial expressions, voice, etc.

[0596] The "adjustment means" has the function of dynamically changing and adjusting recommended content based on the recognized emotional information.

[0597] "Recommended content" refers to learning materials, successful people's experiences, recommended study schedules, necessary cost information, etc., provided based on analyzed user information and emotional state.

[0598] The present invention is a system that inputs and analyzes user information to provide optimal recommended content, and further recognizes the user's emotions in real time and adaptively adjusts the recommended content based on the emotions. An embodiment of this system will be described in detail below.

[0599] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0600] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into a generative AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0601] Furthermore, the present invention incorporates an emotion recognition means. The emotion recognition means monitors the user's facial expressions and voice in real time when inputting information, and identifies the user's emotional state (joy, sadness, surprise, anger, etc.). The recognized emotion information is sent to the server and considered by the analysis means. The server adjusts the recommended content based on this emotion information. For example, if the user is feeling stressed, the server may provide recommended content including relaxing content, and if the user is excited, the server may provide an efficient study plan that utilizes the user's concentration.

[0602] As an actual use case, consider a case where a user has the goal of "buying the latest gadget." In this case, the information the user inputs includes name, age, occupation, area of ​​interest (latest gadgets), goal (buying the latest gadget), etc. The emotion recognition means detects the emotional state of the user when inputting and provides recommended content accordingly. For example, if the user is in an excited state, it generates recommended content that introduces particularly noteworthy new products.

[0603] To realize the system of this invention, the following hardware and software are required. The hardware requires a terminal equipped with a camera and microphone for inputting user information and recognizing emotions. The software includes face recognition using Python and OpenCV, a generative AI model using TensorFlow, and emotion analysis using Transformers. Specifically, OpenCV is used for analyzing user facial expressions, and a Transformers model is used for emotion recognition. A generative AI model using TensorFlow is used to generate recommended content.

[0604] An example prompt is:

[0605] "If a user is interested in the latest gadget and is looking to buy it, the system will generate appropriate content recommendations based on the user's profile information and real-time emotional state."

[0606] As a result, the system of the present invention is able to provide a more personalized service that responds to the individual needs and emotional state of the user.

[0607] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0608] Step 1:

[0609] A user accesses the system and logs in.

[0610] Specifically, the user enters and submits account information (user name, password). This information is then sent to the server, which performs authentication and starts a session if the authentication is successful.

[0611] Input: Username, Password

[0612] Output: Authentication result (success / failure), session start

[0613] Step 2:

[0614] The device displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals.

[0615] Specifically, the terminal displays a form, and after the user has finished entering information, they click the submit button, which is then sent from the terminal to the server.

[0616] Input: User basic information (name, age, occupation, areas of interest, goals)

[0617] Output: User information sent to the server

[0618] Step 3:

[0619] The server receives the transmitted user information and stores it in an internal database.

[0620] Specifically, the server converts the user information into an analyzable format and stores it in a database.

[0621] Input: Submitted user basic information

[0622] Output: User information stored in the internal database

[0623] Step 4:

[0624] The server inputs the stored user information into a generative AI model to generate recommended content based on the user's goals.

[0625] Specifically, the server inputs user information into the AI ​​model and generates recommended content such as learning materials, success stories, recommended study schedules, and necessary cost information.

[0626] Input: User information

[0627] Output: Generated recommended content

[0628] Step 5:

[0629] The generated recommended content is transmitted from the server to the terminal, and the terminal displays the received recommended content to the user.

[0630] Specifically, the server transmits the recommended content to the terminal, which then visually displays the content.

[0631] Input: Generated recommended content

[0632] Output: Recommended content displayed to the user

[0633] Step 6:

[0634] An emotion recognition means monitors the user's facial expressions and voice in real time to identify their emotional state.

[0635] Specifically, the system uses the device's built-in camera and microphone to collect the user's facial expressions and voice data, and analyzes their emotional state using an emotion analysis model.

[0636] Input: User facial and voice data

[0637] Output: Perceived emotional state

[0638] Step 7:

[0639] The recognized emotion information is transmitted to the server and taken into account by the analysis means.

[0640] Specifically, the server receives the user's emotion information and adjusts the recommended content based on the analysis algorithm.

[0641] Input: Emotion information

[0642] Output: Tailored recommended content

[0643] Step 8:

[0644] The adjusted recommended content is sent again to the terminal, which then displays it again to the user.

[0645] Specifically, the server transmits the adjusted recommended content to the terminal, and the terminal displays the new content.

[0646] Input: Tailored recommended content

[0647] Output: Recommended content redisplayed to the user

[0648] 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.

[0649] 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.

[0650] 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.

[0651] [Third embodiment]

[0652] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0653] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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).

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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."

[0664] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0665] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0666] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0667] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0668] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0669] The server receives this information and inputs it into the AI ​​model, which generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'."

[0670] The recommended content generated in this way is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, acquiring hobbies, and acquiring special skills.

[0671] The processing flow will be explained below.

[0672] Step 1:

[0673] A user accesses the system and logs in. The user logs in to the system by entering their account information (username, password) and clicking the login button. After that, the user is redirected to the dashboard.

[0674] Step 2:

[0675] The terminal displays an input form to the user, which includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0676] Step 3:

[0677] The user completes the input and clicks the submit button. The device sends the entered user information to the server, using an HTTPS request for security.

[0678] Step 4:

[0679] The server receives the user information and stores it in an internal database. The received data is stored in an appropriate location for use in analysis.

[0680] Step 5:

[0681] The server inputs the stored user information into the AI ​​model, specifically, passing data about the user's name, age, occupation, areas of interest, and goals to the AI ​​analysis algorithm.

[0682] Step 6:

[0683] The AI ​​model analyzes user information and generates recommended content that best suits the user's goals, including relevant learning materials, success stories, recommended study schedules, and required cost information.

[0684] Step 7:

[0685] The generated recommended content is sent from the server to the device, again using HTTPS requests for security.

[0686] Step 8:

[0687] The device receives the recommended content from the server and displays it to the user, who can then view the content and create a specific action plan to achieve their goals.

[0688] Step 9:

[0689] The user can then take action based on the recommended content provided. For example, the user can create a specific study plan to obtain a programming qualification and proceed with the study using the recommended learning materials. In this way, the system supports the user in achieving their goals.

[0690] Example 1

[0691] 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."

[0692] In conventional systems, the acquisition, storage, and analysis of user information, as well as the provision of optimal recommended content, were complex and inconsistent. Furthermore, the utilization of AI models to provide appropriate learning materials and plans was insufficient, resulting in a significant amount of time and effort required for users to achieve their goals. As a result, it was difficult for users to efficiently use the optimal resources according to their goals.

[0693] 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.

[0694] In this invention, the server includes a storage means for storing received user information in a database, an input means for inputting the stored user information into a generative AI model, and a generation means for generating recommended content according to the user's goals. This allows efficient management of user information and automatic generation of optimal recommended content, enabling the user to effectively start taking action toward their goals.

[0695] "User Information" is personal data about a user, such as name, age, occupation, areas of interest, goals, etc.

[0696] An "input means" is the interface that a user uses to enter information, typically a web form or an application input screen.

[0697] The "transmission means" is a mechanism for transmitting the input user information to the server, and is, for example, a process that uses an HTTP request.

[0698] The "receiving means" is a mechanism by which the server receives the transmitted user information, such as an API endpoint on the server side.

[0699] "Storage" refers to the process of recording received user information in persistent storage such as a database.

[0700] "Input means" refers to the mechanism for inputting stored user information into the generative AI model, a process that includes data format conversion and transmission.

[0701] A "generative AI model" is an artificial intelligence model that analyzes user information and generates recommended content based on the user's goals.

[0702] "Generation means" refers to the process by which the generative AI model generates recommended content based on user information.

[0703] A "prompt sentence" is an input sentence that provides the generative AI model with conditions such as user information and goals, and generates optimal content.

[0704] The "display means" is a mechanism for displaying the generated recommended content to the user, such as the screen of a web browser or a mobile app.

[0705] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0706] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0707] The server receives the user information and stores it in an internal database. Specifically, it uses a relational database management system (RDBMS) such as MySQL to store each piece of information in a corresponding table. The server then inputs the stored user information into a generative AI model. The AI ​​model uses a deep learning framework such as TensorFlow or PyTorch.

[0708] The generative AI model analyzes the input user information and generates recommended content based on the user's goals, including learning materials, success stories, recommended study schedules, and cost information.

[0709] The generated recommended content is sent from the server to the device. The device then displays the received recommended content to the user in an easy-to-read format using HTML and CSS. Based on this information, the user can make specific study plans and make the necessary preparations.

[0710] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0711] The server receives this information and inputs it into an AI model, which generates recommended content such as:

[0712] Recommended programming material: 'Introduction to Python'

[0713] Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0714] Recommended schedule: 'Study for 1 hour every day'

[0715] Budget: 'About 30,000 yen for study materials and exam fees'

[0716] The generated recommended content is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, pursuing hobbies, and acquiring special skills.

[0717] An example of a prompt to input to a generative AI model is:

[0718] "User information: Name (Taro Tanaka), Age (30), Occupation (Engineer), Area of ​​Interest (Programming), Goal (Obtaining a programming qualification). Please generate recommended learning materials, success stories, study schedule, and required cost information for this user."

[0719] Based on these prompts, the AI ​​model generates recommended content tailored to the user, enabling the system to efficiently initiate concrete actions toward acquiring qualifications, hobbies, or special skills.

[0720] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0721] Step 1:

[0722] A user accesses the system and logs in.

[0723] A user opens a browser or application, enters their username and password, and clicks the login button. Input: Username, Password. Output: Authentication result (success or failure).

[0724] Step 2:

[0725] After logging in, the device displays a basic information input form.

[0726] A form for entering user information displays fields such as name, age, occupation, interests, goals, etc. Input: Login successful. Output: Basic information input form.

[0727] Step 3:

[0728] The user enters information and clicks the submit button.

[0729] The entered information is temporarily stored in the device's memory. Input: Name, age, occupation, areas of interest, goals. Output: Entered user information.

[0730] Step 4:

[0731] The terminal transmits the input information to the server.

[0732] The terminal encodes the user information in JSON format and sends it to the server as an HTTP request. Input: Entered user information. Output: HTTP request to the server.

[0733] Step 5:

[0734] The server stores the received user information in a database.

[0735] The server receives the HTTP request, parses it, and writes it to a database. Specifically, it uses an RDBMS such as MySQL to store the information in the corresponding table. Input: HTTP request to the server. Output: User information stored in the database.

[0736] Step 6:

[0737] The user information stored by the server is input into the generative AI model.

[0738] The server retrieves user information from the database, converts it into a format suitable for the generative AI model, and inputs it. For example, a Python script is used to pass JSON format data to the AI ​​model. Input: User information stored in the database. Output: Data input to the generative AI model.

[0739] Step 7:

[0740] A generative AI model generates recommended content based on user goals.

[0741] A generative AI model analyzes input data and generates recommended content based on the user's goals. For example, a model built using TensorFlow or PyTorch might generate "recommended programming materials," "success stories," "recommended study schedules," and "necessary cost information." Input: Data input into the generative AI model. Output: Generated recommended content.

[0742] Step 8:

[0743] The server transmits the generated recommended content to the terminal.

[0744] The server sends the recommended content obtained from the generative AI model to the device in JSON format. This communication also uses a secure protocol (HTTPS). Input: Generated recommended content. Output: HTTP response to the device.

[0745] Step 9:

[0746] The terminal displays the received recommended content to the user.

[0747] The device analyzes the received recommended content and displays it in the user interface using HTML and CSS. Input: HTTP response to the device. Output: Recommended content displayed to the user.

[0748] Step 10:

[0749] The user views the displayed recommended content and begins to take action.

[0750] The user checks the recommended content displayed on the device and begins studying, preparing, or other actions based on the content. For example, they purchase the recommended learning materials and start studying for one hour every day. Input: Recommended content displayed to the user. Output: The user's specific action plan.

[0751] (Application example 1)

[0752] 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."

[0753] Conventional learning support systems lacked optimal learning plans and progress management based on individual user needs, and were unable to provide timely notifications or support to users. They also lacked the functionality to track users' learning progress in real time and suggest further learning content based on that information. This made it difficult for users to maintain their own learning pace.

[0754] 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.

[0755] In this invention, the server includes input means for inputting user information, transmission means for transmitting the input user information, reception means for receiving the transmitted user information, analysis means for analyzing the received user information and generating recommended content according to the user's goals, display means for displaying the generated recommended content, notification means for transmitting notifications based on the recommended study schedule, and progress management means for tracking the user's study progress. This enables study support tailored to the individual needs of the user, realizes notifications and progress management at appropriate times, and improves the user's study efficiency.

[0756] "User Information" refers to information such as name, age, occupation, areas of interest, goals, etc. that a user enters into the system.

[0757] "Input means" refers to a form or device that allows a user to input various information into the system.

[0758] "Transmission means" refers to communication means for transmitting input user information to the server.

[0759] "Receiving means" refers to a communication means by which the server receives the transmitted user information.

[0760] "Analysis means" refers to a processing device or algorithm for analyzing received user information and generating recommended content according to the user's goals.

[0761] "Recommended content" refers to information such as learning materials, success stories, recommended study schedules, and necessary cost information provided to help users achieve their goals.

[0762] The "display means" refers to a device or interface for visually presenting the generated recommended content to the user.

[0763] "Notification Method" refers to a communication method or software for sending notifications to the user at appropriate times based on the recommended study schedule.

[0764] "Progress management means" refers to a system or function for tracking the learning and completed tasks of a user and managing their progress.

[0765] "Server" refers to a central processing unit that receives and analyzes user information and generates recommended content.

[0766] The present invention relates to a system that inputs and analyzes user information and provides recommended content according to the user's goals. First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the send button, which sends the entered information from the terminal to a server.

[0767] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes study materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0768] Based on the recommended study schedule, the notification system sends notifications to the user at appropriate times. The notifications include reminders based on the study content and progress. The device also tracks the user's study progress and sends that information to the server in real time. The server can use this data to provide more accurate content recommendations.

[0769] The hardware used to implement this invention is the user's smartphone. The server side uses Python and Flask to build an API, which sends push notifications via Firebase. A generative AI model is used as software for data processing and calculation.

[0770] As a concrete example, consider the case where a user has the goal of "obtaining a programming qualification." In this case, the user enters their name, age, occupation, area of ​​interest (programming), and goal (obtaining a programming qualification). The server receives this information and inputs it into the AI ​​model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Approximately 30,000 yen for materials and exam fees'." This recommended content is displayed to the user through their device.

[0771] Examples of prompt sentences are shown below.

[0772] User information: Name = User A, Age = 25, Occupation = Engineer, Area of ​​interest = Programming, Goal = Python certification

[0773] Generate recommended content based on user goals.

[0774] Expected output:

[0775] 1. Recommended programming textbook: 'Introduction to Python'

[0776] 2. Successful Experience: 'How I Obtained a Programming Certification in One Year'

[0777] 3. Recommended schedule: 'Study for one hour every day'

[0778] 4. Cost information: 'Textbooks and exam fees will cost approximately 30,000 yen.'

[0779] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0780] Step 1:

[0781] The user logs in and accesses the terminal.

[0782] (Operation description)

[0783] The user starts the system, accesses the login screen, and enters the required authentication information. If the login is successful, the user proceeds to the next user information input screen.

[0784] Step 2:

[0785] The user enters basic information and clicks the submit button.

[0786] (Operation description)

[0787] The terminal displays an input form for the user, asking for information such as name, age, occupation, areas of interest, and goals. The user enters this information into the input form and clicks the submit button. The entered information is converted into a data format and sent from the terminal to the server.

[0788] (Input) Information entered by the user into the input form (name, age, occupation, areas of interest, goals).

[0789] (Output) The user information sent.

[0790] Step 3:

[0791] The server receives the transmitted user information and stores it in an internal database.

[0792] (Operation description)

[0793] The server receives the user information sent from the device and stores it in an internal database. When storing the information, it checks the data format and detects duplicate data.

[0794] (Input) User information sent from the terminal.

[0795] (Output) User information stored in the internal database.

[0796] Step 4:

[0797] The server inputs the stored user information into the AI ​​model to generate recommended content.

[0798] (Operation description)

[0799] The server retrieves user information from an internal database and inputs it into a generative AI model. The AI ​​model uses prompts to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0800] (Input) User information retrieved from the database.

[0801] (Output) The generated recommended content.

[0802] Step 5:

[0803] The generated recommended content is sent to the terminal and displayed.

[0804] (Operation description)

[0805] The server sends the generated recommended content to the device, which then constructs a UI to display the received recommended content to the user and presents it visually.

[0806] (Input) The generated recommended content.

[0807] (Output) The recommended content that is displayed to the user.

[0808] Step 6:

[0809] Send notifications based on a recommended study schedule.

[0810] (Operation description)

[0811] Based on the recommended study schedule, the server uses a push notification service such as Firebase to send notifications to the user at the appropriate time, including study content and important reminders.

[0812] (Input) Recommended study schedule.

[0813] (Output) The notification sent to the user.

[0814] Step 7:

[0815] The user's learning progress is tracked and sent to the server.

[0816] (Operation description)

[0817] The device tracks the user's learning activities in real time and periodically transmits progress data to the server, which stores the received progress data in a database and updates the user information.

[0818] (Input) User's learning progress information.

[0819] (Output) Progress data and updated user information sent to the server.

[0820] Step 8:

[0821] The server provides more accurate recommended content based on the updated user information.

[0822] (Operation description)

[0823] The server uses the saved progress data to re-use the AI ​​model to generate even more accurate recommended content and provide it to the user.

[0824] (Input) Updated user information.

[0825] (Output) New, highly accurate recommended content.

[0826] 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.

[0827] The present invention relates to a system that inputs and analyzes user information and provides optimal recommended content, and further provides more personalized support by combining it with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0828] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0829] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0830] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0831] Furthermore, the present invention incorporates an emotion engine. The emotion engine analyzes facial expressions and voice when the user inputs information to recognize the user's emotions. For example, it uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time and identifies their emotional state (joy, sadness, surprise, anger, etc.).

[0832] The recognized emotional information is sent to the server and considered by the analysis means. The server then adjusts the recommended content based on this emotional information. For example, if the user is feeling stressed, the server will provide recommended content including relaxing study methods and encouraging messages. If the user is excited, the server will provide an efficient study plan that utilizes concentration.

[0833] As a concrete example, consider a case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0834] The server receives this information and emotion data and inputs it into an AI model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'," and adjusts the content according to the user's emotions.

[0835] The recommended content generated in this way is displayed to the user via their device. Based on this information, the user can make specific study plans and make the necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications and acquiring hobbies and special skills. The introduction of an emotion engine enables more personalized support, with the goal of improving user satisfaction and success rates.

[0836] The processing flow will be explained below.

[0837] Step 1:

[0838] A user accesses the system and logs in. The user enters their account information (user name, password) and clicks the login button. This action redirects the user to the dashboard.

[0839] Step 2:

[0840] The terminal displays a basic information input form to the user. The form includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0841] Step 3:

[0842] The terminal displays a send button to send the information entered by the user. When the user clicks the send button, the entered user information is sent from the terminal to the server. This transmission is performed using the HTTPS protocol to ensure security.

[0843] Step 4:

[0844] The server receives the transmitted user information and stores it in an internal database, which is used by subsequent analysis means.

[0845] Step 5:

[0846] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and the collected data is sent to the emotion engine.

[0847] Step 6:

[0848] The emotion engine analyzes the captured facial and voice data to recognize the user's emotions, for example, whether the user is nervous or excited.

[0849] Step 7:

[0850] The emotion engine sends the recognized emotion data to the server, which receives the emotion data and stores it in a database along with user information.

[0851] Step 8:

[0852] The server inputs the stored user information and emotional data into the AI ​​model, which then uses this data to generate optimal content recommendations based on the user's goals.

[0853] Step 9:

[0854] The recommended content generated by the AI ​​model includes learning materials, success stories, recommended study schedules, and cost information, and the content is also tailored to the user's emotions.

[0855] Step 10:

[0856] The server then sends the generated recommendations to the device, again using the HTTPS protocol.

[0857] Step 11:

[0858] The device displays the received recommended content to the user, who can then view the displayed content and create a specific action plan.

[0859] Step 12:

[0860] The user can then take action based on the recommended content displayed. For example, the user can purchase the recommended learning materials and study in a planned manner every day, thereby taking steps toward achieving their goal.

[0861] In this way, the system of the present invention effectively supports users in obtaining qualifications and acquiring hobbies and special skills, and by introducing an emotion engine, can provide even more personalized support.

[0862] Example 2

[0863] 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."

[0864] Conventional content recommendation systems based on user information lack personalization that takes into account the user's emotional state, and have had the problem of not being able to sufficiently increase user satisfaction or goal achievement rates. In particular, when a user is feeling stressed or tense, providing content that ignores that state will not be effective.

[0865] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommended content according to the user's goals, and a display means for displaying the generated recommended content. This enables detailed personalization according to the user's status.

[0866] "User information" refers to personal information and attribute information of a user, specifically including name, age, occupation, areas of interest, goals, and the like.

[0867] "Input means" refers to the means by which a user inputs information into a system, such as a form or interface.

[0868] "Transmission means" refers to a means for transmitting input data to other parts of the system, and specifically refers to a communication device or a network interface.

[0869] "Receiving means" refers to a means for receiving data sent from outside, and specifically refers to a communication device or a network interface.

[0870] "Analysis means" refers to the means for analyzing the received data and generating appropriate output, and specifically refers to a data analysis device or software algorithm.

[0871] "Recommended content" refers to content generated by the analysis means to support the user in achieving their goals, and includes study materials, success stories, recommended study schedules, necessary cost information, and the like.

[0872] The "display means" refers to a means for displaying the generated recommended content to the user, and specifically refers to a monitor, browser screen, or the like.

[0873] An "emotion engine" is an engine that recognizes a user's emotions and analyzes that information, and specifically refers to facial expression recognition and voice analysis technology using a camera and microphone.

[0874] "Emotion information receiving means" refers to means for receiving emotion information recognized by the emotion engine, and specifically refers to a communication device or a network interface.

[0875] The present invention relates to a system that inputs user information and provides recommended content in consideration of the information and the user's emotional state. An embodiment of this system will be described in detail below.

[0876] First, the user accesses the system using a browser or a dedicated application and logs in. The terminal displays a login screen, and the user logs in by entering account information (user name, password). If the login is successful, the user can access the system.

[0877] Next, the terminal displays a form for the user to enter basic information (name, age, occupation, areas of interest, goals). The user enters this information and clicks the submit button. This information is sent from the terminal to the server. The server receives the sent user information and stores it in an internal database. Possible databases used include MySQL and PostgreSQL.

[0878] The server then inputs the saved user information into an AI model to generate recommended content based on the user's goals. The AI ​​model used is OpenAI's GPT-4, among others. Recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays it to the user.

[0879] Furthermore, the present invention incorporates an emotion engine that analyzes the user's facial expressions and tone of voice when entering information. Using a camera and microphone installed on the device, the device monitors the user's facial expressions and voice in real time to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.). The analyzed emotion information is sent to the server. The server receives the emotion information and adjusts the recommended content based on this information.

[0880] Specifically, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[0881] Specific examples of prompts are as follows:

[0882] "The user has stated that he wants to obtain a programming qualification. The user's basic information is: Name: Yamada Taro, Age: 25, Occupation: System Engineer, Area of ​​Interest: Python, Goal: Obtaining a Python qualification. The user is nervous while typing, and the emotion engine senses this. Please generate recommended content for the user."

[0883] This system allows users to receive specific and personalized support to achieve their goals. The introduction of an emotion engine enables appropriate recommendations that take into account the user's emotional state, which is expected to improve user satisfaction and success rates.

[0884] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0885] Step 1:

[0886] A user accesses the system using a browser or a dedicated application and logs in. As input, they enter their username and password into the terminal. The terminal sends the entered information to the server. The server receives this and compares it with the user authentication information in an internal database (e.g., MySQL). If authentication is successful, the server generates a session ID and returns it to the terminal. As output, the terminal displays the session ID if authentication is successful, or an error message if authentication is unsuccessful.

[0887] Step 2:

[0888] For users who have been successfully authenticated, the terminal displays a form for entering basic information such as name, age, occupation, areas of interest, and goals. The user enters this information into the form and clicks the submit button. The basic information entered by the user into the form is required as input. The terminal sends this information to the server in JSON format or similar. The server parses the received JSON data and stores it in a database. As output, a message confirming successful submission and the ability to move to the next step are displayed on the terminal.

[0889] Step 3:

[0890] The server uses the stored user information to send prompts to an AI model (e.g., OpenAI GPT-4). As input, the server needs to generate a prompt sentence based on the user information. The server sends the prompt sentence to the AI ​​model, which then generates recommended content based on the user's goals. As output, the AI ​​model returns recommended content including learning materials, success stories, study schedules, and required cost information. The server receives this recommended content.

[0891] Step 4:

[0892] The server sends the generated recommended content to the device. As input, the recommended content received from the AI ​​model is required. The server sends this data to the device in JSON format. The device parses the received JSON data and displays it to the user in an appropriate format. The user views the displayed recommended content and begins taking action toward learning or achieving their goal. As output, the recommended content is displayed on the device.

[0893] Step 5:

[0894] The device uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time while the user is entering information. As input, the device requires the user's facial expression data and voice data. The device sends these data to an emotion analysis engine to identify the user's emotional state. The emotion analysis results are sent to the server in JSON format. As output, the emotional state (such as joy, sadness, surprise, or anger) is identified and sent to the server.

[0895] Step 6:

[0896] The server receives the emotional information and adjusts the recommended content. As input, it requires the result of the emotional analysis. The server runs the received emotional data through an analytical method to generate a new prompt with additional information and adjustments according to the user's emotions. The server then sends this new prompt to the AI ​​model again to generate recommended content according to the emotions. As output, the newly adjusted recommended content is generated.

[0897] Step 7:

[0898] The server sends the final recommended content to the device and displays it to the user. As input, tailored recommended content is required. The server sends the content to the device in JSON format, and the device redisplays the received content. The user can then adjust their learning plan or behavior based on this. As output, the final personalized recommended content is displayed on the device.

[0899] (Application example 2)

[0900] 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."

[0901] In recent years, with the digitalization of markets and the spread of virtual shopping, there has been an increasing demand for personalized support systems that respond to individual users' preferences and emotions. However, conventional systems are unable to recognize users' emotions in real time and dynamically adjust service content based on that, limiting the improvement of user experience. Therefore, there is a need for a system that provides optimal product recommendations and shopping support in virtual stores based on user information and real-time emotional state.

[0902] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0903] In this invention, the server includes an analysis means for analyzing input user information and generating recommended content according to the user's goals, an emotion recognition means for recognizing and considering the user's emotions in real time, and an adjustment means for adjusting the recommended content based on the user's emotion recognition information, thereby enabling dynamic generation and provision of recommended content according to the user's emotional state.

[0904] "User Information" is information about an individual, such as the user's name, age, occupation, areas of interest, goals, etc.

[0905] "Input means" refers to a device or interface for inputting user information.

[0906] "Transmission means" refers to a mechanism for transmitting input user information to a server.

[0907] "Receiving means" refers to a function for receiving user information on the server side.

[0908] The "analysis means" includes an engine or algorithm for analyzing received user information and generating recommended content based on that information.

[0909] The "display means" refers to a display device or digital screen for visually presenting the generated recommended content to the user.

[0910] "Emotion recognition means" refers to technology or devices that recognize emotions in real time from a user's facial expressions, voice, etc.

[0911] The "adjustment means" has the function of dynamically changing and adjusting recommended content based on the recognized emotional information.

[0912] "Recommended content" refers to learning materials, successful people's experiences, recommended study schedules, necessary cost information, etc., provided based on analyzed user information and emotional state.

[0913] The present invention is a system that inputs and analyzes user information to provide optimal recommended content, and further recognizes the user's emotions in real time and adaptively adjusts the recommended content based on the emotions. An embodiment of this system will be described in detail below.

[0914] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[0915] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into a generative AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[0916] Furthermore, the present invention incorporates an emotion recognition means. The emotion recognition means monitors the user's facial expressions and voice in real time when inputting information, and identifies the user's emotional state (joy, sadness, surprise, anger, etc.). The recognized emotion information is sent to the server and considered by the analysis means. The server adjusts the recommended content based on this emotion information. For example, if the user is feeling stressed, the server may provide recommended content including relaxing content, and if the user is excited, the server may provide an efficient study plan that utilizes the user's concentration.

[0917] As an actual use case, consider a case where a user has the goal of "buying the latest gadget." In this case, the information the user inputs includes name, age, occupation, area of ​​interest (latest gadgets), goal (buying the latest gadget), etc. The emotion recognition means detects the emotional state of the user when inputting and provides recommended content accordingly. For example, if the user is in an excited state, it generates recommended content that introduces particularly noteworthy new products.

[0918] To realize the system of this invention, the following hardware and software are required. The hardware requires a terminal equipped with a camera and microphone for inputting user information and recognizing emotions. The software includes face recognition using Python and OpenCV, a generative AI model using TensorFlow, and emotion analysis using Transformers. Specifically, OpenCV is used for analyzing user facial expressions, and a Transformers model is used for emotion recognition. A generative AI model using TensorFlow is used to generate recommended content.

[0919] An example prompt is:

[0920] "If a user is interested in the latest gadget and is looking to buy it, the system will generate appropriate content recommendations based on the user's profile information and real-time emotional state."

[0921] As a result, the system of the present invention is able to provide a more personalized service that responds to the individual needs and emotional state of the user.

[0922] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0923] Step 1:

[0924] A user accesses the system and logs in.

[0925] Specifically, the user enters and submits account information (user name, password). This information is then sent to the server, which performs authentication and starts a session if the authentication is successful.

[0926] Input: Username, Password

[0927] Output: Authentication result (success / failure), session start

[0928] Step 2:

[0929] The device displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals.

[0930] Specifically, the terminal displays a form, and after the user has finished entering information, they click the submit button, which is then sent from the terminal to the server.

[0931] Input: User basic information (name, age, occupation, areas of interest, goals)

[0932] Output: User information sent to the server

[0933] Step 3:

[0934] The server receives the transmitted user information and stores it in an internal database.

[0935] Specifically, the server converts the user information into an analyzable format and stores it in a database.

[0936] Input: Submitted user basic information

[0937] Output: User information stored in the internal database

[0938] Step 4:

[0939] The server inputs the stored user information into a generative AI model to generate recommended content based on the user's goals.

[0940] Specifically, the server inputs user information into the AI ​​model and generates recommended content such as learning materials, success stories, recommended study schedules, and necessary cost information.

[0941] Input: User information

[0942] Output: Generated recommended content

[0943] Step 5:

[0944] The generated recommended content is transmitted from the server to the terminal, and the terminal displays the received recommended content to the user.

[0945] Specifically, the server transmits the recommended content to the terminal, which then visually displays the content.

[0946] Input: Generated recommended content

[0947] Output: Recommended content displayed to the user

[0948] Step 6:

[0949] An emotion recognition means monitors the user's facial expressions and voice in real time to identify their emotional state.

[0950] Specifically, the system uses the device's built-in camera and microphone to collect the user's facial expressions and voice data, and analyzes their emotional state using an emotion analysis model.

[0951] Input: User facial and voice data

[0952] Output: Perceived emotional state

[0953] Step 7:

[0954] The recognized emotion information is transmitted to the server and taken into account by the analysis means.

[0955] Specifically, the server receives the user's emotion information and adjusts the recommended content based on the analysis algorithm.

[0956] Input: Emotion information

[0957] Output: Tailored recommended content

[0958] Step 8:

[0959] The adjusted recommended content is sent again to the terminal, which then displays it again to the user.

[0960] Specifically, the server transmits the adjusted recommended content to the terminal, and the terminal displays the new content.

[0961] Input: Tailored recommended content

[0962] Output: Recommended content redisplayed to the user

[0963] 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.

[0964] 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.

[0965] 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.

[0966] [Fourth embodiment]

[0967] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0968] 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.

[0969] 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).

[0970] 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.

[0971] 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.

[0972] 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).

[0973] 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.

[0974] 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.

[0975] 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.

[0976] 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.

[0977] 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.

[0978] 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.

[0979] 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."

[0980] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[0981] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[0982] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[0983] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[0984] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[0985] The server receives this information and inputs it into the AI ​​model, which generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'."

[0986] The recommended content generated in this way is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, acquiring hobbies, and acquiring special skills.

[0987] The processing flow will be explained below.

[0988] Step 1:

[0989] A user accesses the system and logs in. The user logs in to the system by entering their account information (username, password) and clicking the login button. After that, the user is redirected to the dashboard.

[0990] Step 2:

[0991] The terminal displays an input form to the user, which includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[0992] Step 3:

[0993] The user completes the input and clicks the submit button. The device sends the entered user information to the server, using an HTTPS request for security.

[0994] Step 4:

[0995] The server receives the user information and stores it in an internal database. The received data is stored in an appropriate location for use in analysis.

[0996] Step 5:

[0997] The server inputs the stored user information into the AI ​​model, specifically, passing data about the user's name, age, occupation, areas of interest, and goals to the AI ​​analysis algorithm.

[0998] Step 6:

[0999] The AI ​​model analyzes user information and generates recommended content that best suits the user's goals, including relevant learning materials, success stories, recommended study schedules, and required cost information.

[1000] Step 7:

[1001] The generated recommended content is sent from the server to the device, again using HTTPS requests for security.

[1002] Step 8:

[1003] The device receives the recommended content from the server and displays it to the user, who can then view the content and create a specific action plan to achieve their goals.

[1004] Step 9:

[1005] The user can then take action based on the recommended content provided. For example, the user can create a specific study plan to obtain a programming qualification and proceed with the study using the recommended learning materials. In this way, the system supports the user in achieving their goals.

[1006] Example 1

[1007] 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."

[1008] In conventional systems, the acquisition, storage, and analysis of user information, as well as the provision of optimal recommended content, were complex and inconsistent. Furthermore, the utilization of AI models to provide appropriate learning materials and plans was insufficient, resulting in a significant amount of time and effort required for users to achieve their goals. As a result, it was difficult for users to efficiently use the optimal resources according to their goals.

[1009] 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.

[1010] In this invention, the server includes a storage means for storing received user information in a database, an input means for inputting the stored user information into a generative AI model, and a generation means for generating recommended content according to the user's goals. This allows efficient management of user information and automatic generation of optimal recommended content, enabling the user to effectively start taking action toward their goals.

[1011] "User Information" is personal data about a user, such as name, age, occupation, areas of interest, goals, etc.

[1012] An "input means" is the interface that a user uses to enter information, typically a web form or an application input screen.

[1013] The "transmission means" is a mechanism for transmitting the input user information to the server, and is, for example, a process that uses an HTTP request.

[1014] The "receiving means" is a mechanism by which the server receives the transmitted user information, such as an API endpoint on the server side.

[1015] "Storage" refers to the process of recording received user information in persistent storage such as a database.

[1016] "Input means" refers to the mechanism for inputting stored user information into the generative AI model, a process that includes data format conversion and transmission.

[1017] A "generative AI model" is an artificial intelligence model that analyzes user information and generates recommended content based on the user's goals.

[1018] "Generation means" refers to the process by which the generative AI model generates recommended content based on user information.

[1019] A "prompt sentence" is an input sentence that provides the generative AI model with conditions such as user information and goals, and generates optimal content.

[1020] The "display means" is a mechanism for displaying the generated recommended content to the user, such as the screen of a web browser or a mobile app.

[1021] The present invention relates to a system for inputting and analyzing user information and providing optimal recommended content. An embodiment of this system will be described in detail below.

[1022] First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, goals, etc. The user enters this information and clicks the submit button, which sends the entered information from the terminal to the server.

[1023] The server receives the user information and stores it in an internal database. Specifically, it uses a relational database management system (RDBMS) such as MySQL to store each piece of information in a corresponding table. The server then inputs the stored user information into a generative AI model. The AI ​​model uses a deep learning framework such as TensorFlow or PyTorch.

[1024] The generative AI model analyzes the input user information and generates recommended content based on the user's goals, including learning materials, success stories, recommended study schedules, and cost information.

[1025] The generated recommended content is sent from the server to the device. The device then displays the received recommended content to the user in an easy-to-read format using HTML and CSS. Based on this information, the user can make specific study plans and make the necessary preparations.

[1026] As a concrete example, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc.

[1027] The server receives this information and inputs it into an AI model, which generates recommended content such as:

[1028] Recommended programming material: 'Introduction to Python'

[1029] Successful Experience: 'How I Obtained a Programming Certification in One Year'

[1030] Recommended schedule: 'Study for 1 hour every day'

[1031] Budget: 'About 30,000 yen for study materials and exam fees'

[1032] The generated recommended content is displayed to the user via the terminal. Based on this information, the user can make specific study plans and make necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications, pursuing hobbies, and acquiring special skills.

[1033] An example of a prompt to input to a generative AI model is:

[1034] "User information: Name (Taro Tanaka), Age (30), Occupation (Engineer), Area of ​​Interest (Programming), Goal (Obtaining a programming qualification). Please generate recommended learning materials, success stories, study schedule, and required cost information for this user."

[1035] Based on these prompts, the AI ​​model generates recommended content tailored to the user, enabling the system to efficiently initiate concrete actions toward acquiring qualifications, hobbies, or special skills.

[1036] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1037] Step 1:

[1038] A user accesses the system and logs in.

[1039] A user opens a browser or application, enters their username and password, and clicks the login button. Input: Username, Password. Output: Authentication result (success or failure).

[1040] Step 2:

[1041] After logging in, the device displays a basic information input form.

[1042] A form for entering user information displays fields such as name, age, occupation, interests, goals, etc. Input: Login successful. Output: Basic information input form.

[1043] Step 3:

[1044] The user enters information and clicks the submit button.

[1045] The entered information is temporarily stored in the device's memory. Input: Name, age, occupation, areas of interest, goals. Output: Entered user information.

[1046] Step 4:

[1047] The terminal transmits the input information to the server.

[1048] The terminal encodes the user information in JSON format and sends it to the server as an HTTP request. Input: Entered user information. Output: HTTP request to the server.

[1049] Step 5:

[1050] The server stores the received user information in a database.

[1051] The server receives the HTTP request, parses it, and writes it to a database. Specifically, it uses an RDBMS such as MySQL to store the information in the corresponding table. Input: HTTP request to the server. Output: User information stored in the database.

[1052] Step 6:

[1053] The user information stored by the server is input into the generative AI model.

[1054] The server retrieves user information from the database, converts it into a format suitable for the generative AI model, and inputs it. For example, a Python script is used to pass JSON format data to the AI ​​model. Input: User information stored in the database. Output: Data input to the generative AI model.

[1055] Step 7:

[1056] A generative AI model generates recommended content based on user goals.

[1057] A generative AI model analyzes input data and generates recommended content based on the user's goals. For example, a model built using TensorFlow or PyTorch might generate "recommended programming materials," "success stories," "recommended study schedules," and "necessary cost information." Input: Data input into the generative AI model. Output: Generated recommended content.

[1058] Step 8:

[1059] The server transmits the generated recommended content to the terminal.

[1060] The server sends the recommended content obtained from the generative AI model to the device in JSON format. This communication also uses a secure protocol (HTTPS). Input: Generated recommended content. Output: HTTP response to the device.

[1061] Step 9:

[1062] The terminal displays the received recommended content to the user.

[1063] The device analyzes the received recommended content and displays it in the user interface using HTML and CSS. Input: HTTP response to the device. Output: Recommended content displayed to the user.

[1064] Step 10:

[1065] The user views the displayed recommended content and begins to take action.

[1066] The user checks the recommended content displayed on the device and begins studying, preparing, or other actions based on the content. For example, they purchase the recommended learning materials and start studying for one hour every day. Input: Recommended content displayed to the user. Output: The user's specific action plan.

[1067] (Application example 1)

[1068] 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."

[1069] Conventional learning support systems lacked optimal learning plans and progress management based on individual user needs, and were unable to provide timely notifications or support to users. They also lacked the functionality to track users' learning progress in real time and suggest further learning content based on that information. This made it difficult for users to maintain their own learning pace.

[1070] 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.

[1071] In this invention, the server includes input means for inputting user information, transmission means for transmitting the input user information, reception means for receiving the transmitted user information, analysis means for analyzing the received user information and generating recommended content according to the user's goals, display means for displaying the generated recommended content, notification means for transmitting notifications based on the recommended study schedule, and progress management means for tracking the user's study progress. This enables study support tailored to the individual needs of the user, realizes notifications and progress management at appropriate times, and improves the user's study efficiency.

[1072] "User Information" refers to information such as name, age, occupation, areas of interest, goals, etc. that a user enters into the system.

[1073] "Input means" refers to a form or device that allows a user to input various information into the system.

[1074] "Transmission means" refers to communication means for transmitting input user information to the server.

[1075] "Receiving means" refers to a communication means by which the server receives the transmitted user information.

[1076] "Analysis means" refers to a processing device or algorithm for analyzing received user information and generating recommended content according to the user's goals.

[1077] "Recommended content" refers to information such as learning materials, success stories, recommended study schedules, and necessary cost information provided to help users achieve their goals.

[1078] The "display means" refers to a device or interface for visually presenting the generated recommended content to the user.

[1079] "Notification Method" refers to a communication method or software for sending notifications to the user at appropriate times based on the recommended study schedule.

[1080] "Progress management means" refers to a system or function for tracking the learning and completed tasks of a user and managing their progress.

[1081] "Server" refers to a central processing unit that receives and analyzes user information and generates recommended content.

[1082] The present invention relates to a system that inputs and analyzes user information and provides recommended content according to the user's goals. First, the user accesses the system and logs in. After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the send button, which sends the entered information from the terminal to a server.

[1083] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes study materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[1084] Based on the recommended study schedule, the notification system sends notifications to the user at appropriate times. The notifications include reminders based on the study content and progress. The device also tracks the user's study progress and sends that information to the server in real time. The server can use this data to provide more accurate content recommendations.

[1085] The hardware used to implement this invention is the user's smartphone. The server side uses Python and Flask to build an API, which sends push notifications via Firebase. A generative AI model is used as software for data processing and calculation.

[1086] As a concrete example, consider the case where a user has the goal of "obtaining a programming qualification." In this case, the user enters their name, age, occupation, area of ​​interest (programming), and goal (obtaining a programming qualification). The server receives this information and inputs it into the AI ​​model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Approximately 30,000 yen for materials and exam fees'." This recommended content is displayed to the user through their device.

[1087] Examples of prompt sentences are shown below.

[1088] User information: Name = User A, Age = 25, Occupation = Engineer, Area of ​​interest = Programming, Goal = Python certification

[1089] Generate recommended content based on user goals.

[1090] Expected output:

[1091] 1. Recommended programming textbook: 'Introduction to Python'

[1092] 2. Successful Experience: 'How I Obtained a Programming Certification in One Year'

[1093] 3. Recommended schedule: 'Study for one hour every day'

[1094] 4. Cost information: 'Textbooks and exam fees will cost approximately 30,000 yen.'

[1095] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1096] Step 1:

[1097] The user logs in and accesses the terminal.

[1098] (Operation description)

[1099] The user starts the system, accesses the login screen, and enters the required authentication information. If the login is successful, the user proceeds to the next user information input screen.

[1100] Step 2:

[1101] The user enters basic information and clicks the submit button.

[1102] (Operation description)

[1103] The terminal displays an input form for the user, asking for information such as name, age, occupation, areas of interest, and goals. The user enters this information into the input form and clicks the submit button. The entered information is converted into a data format and sent from the terminal to the server.

[1104] (Input) Information entered by the user into the input form (name, age, occupation, areas of interest, goals).

[1105] (Output) The user information sent.

[1106] Step 3:

[1107] The server receives the transmitted user information and stores it in an internal database.

[1108] (Operation description)

[1109] The server receives the user information sent from the device and stores it in an internal database. When storing the information, it checks the data format and detects duplicate data.

[1110] (Input) User information sent from the terminal.

[1111] (Output) User information stored in the internal database.

[1112] Step 4:

[1113] The server inputs the stored user information into the AI ​​model to generate recommended content.

[1114] (Operation description)

[1115] The server retrieves user information from an internal database and inputs it into a generative AI model. The AI ​​model uses prompts to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[1116] (Input) User information retrieved from the database.

[1117] (Output) The generated recommended content.

[1118] Step 5:

[1119] The generated recommended content is sent to the terminal and displayed.

[1120] (Operation description)

[1121] The server sends the generated recommended content to the device, which then constructs a UI to display the received recommended content to the user and presents it visually.

[1122] (Input) The generated recommended content.

[1123] (Output) The recommended content that is displayed to the user.

[1124] Step 6:

[1125] Send notifications based on a recommended study schedule.

[1126] (Operation description)

[1127] Based on the recommended study schedule, the server uses a push notification service such as Firebase to send notifications to the user at the appropriate time, including study content and important reminders.

[1128] (Input) Recommended study schedule.

[1129] (Output) The notification sent to the user.

[1130] Step 7:

[1131] The user's learning progress is tracked and sent to the server.

[1132] (Operation description)

[1133] The device tracks the user's learning activities in real time and periodically transmits progress data to the server, which stores the received progress data in a database and updates the user information.

[1134] (Input) User's learning progress information.

[1135] (Output) Progress data and updated user information sent to the server.

[1136] Step 8:

[1137] The server provides more accurate recommended content based on the updated user information.

[1138] (Operation description)

[1139] The server uses the saved progress data to re-use the AI ​​model to generate even more accurate recommended content and provide it to the user.

[1140] (Input) Updated user information.

[1141] (Output) New, highly accurate recommended content.

[1142] 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.

[1143] The present invention relates to a system that inputs and analyzes user information and provides optimal recommended content, and further provides more personalized support by combining it with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[1144] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[1145] The server receives the user information and stores it in an internal database. The server then inputs the stored user information into an AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information.

[1146] The generated recommended content is sent from the server to the device, and the device displays the received recommended content to the user. The user can view the displayed content and take appropriate action to achieve their goal.

[1147] Furthermore, the present invention incorporates an emotion engine. The emotion engine analyzes facial expressions and voice when the user inputs information to recognize the user's emotions. For example, it uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time and identifies their emotional state (joy, sadness, surprise, anger, etc.).

[1148] The recognized emotional information is sent to the server and considered by the analysis means. The server then adjusts the recommended content based on this emotional information. For example, if the user is feeling stressed, the server will provide recommended content including relaxing study methods and encouraging messages. If the user is excited, the server will provide an efficient study plan that utilizes concentration.

[1149] As a concrete example, consider a case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[1150] The server receives this information and emotion data and inputs it into an AI model. The AI ​​model generates recommended content such as "Recommended programming materials: 'Introduction to Python'," "Successful people's experiences: 'How to obtain a programming qualification in one year'," "Recommended schedule: 'Study for one hour every day'," and "Budget: 'Materials and exam fees will cost approximately 30,000 yen'," and adjusts the content according to the user's emotions.

[1151] The recommended content generated in this way is displayed to the user via their device. Based on this information, the user can make specific study plans and make the necessary preparations. In this way, the present invention is a system that effectively supports users in obtaining qualifications and acquiring hobbies and special skills. The introduction of an emotion engine enables more personalized support, with the goal of improving user satisfaction and success rates.

[1152] The processing flow will be explained below.

[1153] Step 1:

[1154] A user accesses the system and logs in. The user enters their account information (user name, password) and clicks the login button. This action redirects the user to the dashboard.

[1155] Step 2:

[1156] The terminal displays a basic information input form to the user. The form includes fields for entering name, age, occupation, areas of interest, and goals. The user enters the required information into these fields.

[1157] Step 3:

[1158] The terminal displays a send button to send the information entered by the user. When the user clicks the send button, the entered user information is sent from the terminal to the server. This transmission is performed using the HTTPS protocol to ensure security.

[1159] Step 4:

[1160] The server receives the transmitted user information and stores it in an internal database, which is used by subsequent analysis means.

[1161] Step 5:

[1162] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and the collected data is sent to the emotion engine.

[1163] Step 6:

[1164] The emotion engine analyzes the captured facial and voice data to recognize the user's emotions, for example, whether the user is nervous or excited.

[1165] Step 7:

[1166] The emotion engine sends the recognized emotion data to the server, which receives the emotion data and stores it in a database along with user information.

[1167] Step 8:

[1168] The server inputs the stored user information and emotional data into the AI ​​model, which then uses this data to generate optimal content recommendations based on the user's goals.

[1169] Step 9:

[1170] The recommended content generated by the AI ​​model includes learning materials, success stories, recommended study schedules, and cost information, and the content is also tailored to the user's emotions.

[1171] Step 10:

[1172] The server then sends the generated recommendations to the device, again using the HTTPS protocol.

[1173] Step 11:

[1174] The device displays the received recommended content to the user, who can then view the displayed content and create a specific action plan.

[1175] Step 12:

[1176] The user can then take action based on the recommended content displayed. For example, the user can purchase the recommended learning materials and study in a planned manner every day, thereby taking steps toward achieving their goal.

[1177] In this way, the system of the present invention effectively supports users in obtaining qualifications and acquiring hobbies and special skills, and by introducing an emotion engine, can provide even more personalized support.

[1178] Example 2

[1179] 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."

[1180] Conventional content recommendation systems based on user information lack personalization that takes into account the user's emotional state, and have had the problem of not being able to sufficiently increase user satisfaction or goal achievement rates. In particular, when a user is feeling stressed or tense, providing content that ignores that state will not be effective.

[1181] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for inputting user information, a transmission means for transmitting the input user information, a reception means for receiving the transmitted user information, an analysis means for analyzing the received user information and generating recommended content according to the user's goals, and a display means for displaying the generated recommended content. This enables detailed personalization according to the user's status.

[1182] "User information" refers to personal information and attribute information of a user, specifically including name, age, occupation, areas of interest, goals, and the like.

[1183] "Input means" refers to the means by which a user inputs information into a system, such as a form or interface.

[1184] "Transmission means" refers to a means for transmitting input data to other parts of the system, and specifically refers to a communication device or a network interface.

[1185] "Receiving means" refers to a means for receiving data sent from outside, and specifically refers to a communication device or a network interface.

[1186] "Analysis means" refers to the means for analyzing the received data and generating appropriate output, and specifically refers to a data analysis device or software algorithm.

[1187] "Recommended content" refers to content generated by the analysis means to support the user in achieving their goals, and includes study materials, success stories, recommended study schedules, necessary cost information, and the like.

[1188] The "display means" refers to a means for displaying the generated recommended content to the user, and specifically refers to a monitor, browser screen, or the like.

[1189] An "emotion engine" is an engine that recognizes a user's emotions and analyzes that information, and specifically refers to facial expression recognition and voice analysis technology using a camera and microphone.

[1190] "Emotion information receiving means" refers to means for receiving emotion information recognized by the emotion engine, and specifically refers to a communication device or a network interface.

[1191] The present invention relates to a system that inputs user information and provides recommended content in consideration of the information and the user's emotional state. An embodiment of this system will be described in detail below.

[1192] First, the user accesses the system using a browser or a dedicated application and logs in. The terminal displays a login screen, and the user logs in by entering account information (user name, password). If the login is successful, the user can access the system.

[1193] Next, the terminal displays a form for the user to enter basic information (name, age, occupation, areas of interest, goals). The user enters this information and clicks the submit button. This information is sent from the terminal to the server. The server receives the sent user information and stores it in an internal database. Possible databases used include MySQL and PostgreSQL.

[1194] The server then inputs the saved user information into an AI model to generate recommended content based on the user's goals. The AI ​​model used is OpenAI's GPT-4, among others. Recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays it to the user.

[1195] Furthermore, the present invention incorporates an emotion engine that analyzes the user's facial expressions and tone of voice when entering information. Using a camera and microphone installed on the device, the device monitors the user's facial expressions and voice in real time to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.). The analyzed emotion information is sent to the server. The server receives the emotion information and adjusts the recommended content based on this information.

[1196] Specifically, consider the case where a user has a goal of "obtaining a programming qualification." In this case, the information the user enters includes name, age, occupation, field of interest (programming), goal (obtaining a programming qualification), etc. The emotion engine detects tension or anxiety when the user enters information and adds corresponding kind words or encouraging messages to the recommended content.

[1197] Specific examples of prompts are as follows:

[1198] "The user has stated that he wants to obtain a programming qualification. The user's basic information is: Name: Yamada Taro, Age: 25, Occupation: System Engineer, Area of ​​Interest: Python, Goal: Obtaining a Python qualification. The user is nervous while typing, and the emotion engine senses this. Please generate recommended content for the user."

[1199] This system allows users to receive specific and personalized support to achieve their goals. The introduction of an emotion engine enables appropriate recommendations that take into account the user's emotional state, which is expected to improve user satisfaction and success rates.

[1200] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1201] Step 1:

[1202] A user accesses the system using a browser or a dedicated application and logs in. As input, they enter their username and password into the terminal. The terminal sends the entered information to the server. The server receives this and compares it with the user authentication information in an internal database (e.g., MySQL). If authentication is successful, the server generates a session ID and returns it to the terminal. As output, the terminal displays the session ID if authentication is successful, or an error message if authentication is unsuccessful.

[1203] Step 2:

[1204] For users who have been successfully authenticated, the terminal displays a form for entering basic information such as name, age, occupation, areas of interest, and goals. The user enters this information into the form and clicks the submit button. The basic information entered by the user into the form is required as input. The terminal sends this information to the server in JSON format or similar. The server parses the received JSON data and stores it in a database. As output, a message confirming successful submission and the ability to move to the next step are displayed on the terminal.

[1205] Step 3:

[1206] The server uses the stored user information to send prompts to an AI model (e.g., OpenAI GPT-4). As input, the server needs to generate a prompt sentence based on the user information. The server sends the prompt sentence to the AI ​​model, which then generates recommended content based on the user's goals. As output, the AI ​​model returns recommended content including learning materials, success stories, study schedules, and required cost information. The server receives this recommended content.

[1207] Step 4:

[1208] The server sends the generated recommended content to the device. As input, the recommended content received from the AI ​​model is required. The server sends this data to the device in JSON format. The device parses the received JSON data and displays it to the user in an appropriate format. The user views the displayed recommended content and begins taking action toward learning or achieving their goal. As output, the recommended content is displayed on the device.

[1209] Step 5:

[1210] The device uses a camera and microphone to monitor the user's facial expressions and tone of voice in real time while the user is entering information. As input, the device requires the user's facial expression data and voice data. The device sends these data to an emotion analysis engine to identify the user's emotional state. The emotion analysis results are sent to the server in JSON format. As output, the emotional state (such as joy, sadness, surprise, or anger) is identified and sent to the server.

[1211] Step 6:

[1212] The server receives the emotional information and adjusts the recommended content. As input, it requires the result of the emotional analysis. The server runs the received emotional data through an analytical method to generate a new prompt with additional information and adjustments according to the user's emotions. The server then sends this new prompt to the AI ​​model again to generate recommended content according to the emotions. As output, the newly adjusted recommended content is generated.

[1213] Step 7:

[1214] The server sends the final recommended content to the device and displays it to the user. As input, tailored recommended content is required. The server sends the content to the device in JSON format, and the device redisplays the received content. The user can then adjust their learning plan or behavior based on this. As output, the final personalized recommended content is displayed on the device.

[1215] (Application example 2)

[1216] 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."

[1217] In recent years, with the digitalization of markets and the spread of virtual shopping, there has been an increasing demand for personalized support systems that respond to individual users' preferences and emotions. However, conventional systems are unable to recognize users' emotions in real time and dynamically adjust service content based on that, limiting the improvement of user experience. Therefore, there is a need for a system that provides optimal product recommendations and shopping support in virtual stores based on user information and real-time emotional state.

[1218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1219] In this invention, the server includes an analysis means for analyzing input user information and generating recommended content according to the user's goals, an emotion recognition means for recognizing and considering the user's emotions in real time, and an adjustment means for adjusting the recommended content based on the user's emotion recognition information, thereby enabling dynamic generation and provision of recommended content according to the user's emotional state.

[1220] "User Information" is information about an individual, such as the user's name, age, occupation, areas of interest, goals, etc.

[1221] "Input means" refers to a device or interface for inputting user information.

[1222] "Transmission means" refers to a mechanism for transmitting input user information to a server.

[1223] "Receiving means" refers to a function for receiving user information on the server side.

[1224] The "analysis means" includes an engine or algorithm for analyzing received user information and generating recommended content based on that information.

[1225] The "display means" refers to a display device or digital screen for visually presenting the generated recommended content to the user.

[1226] "Emotion recognition means" refers to technology or devices that recognize emotions in real time from a user's facial expressions, voice, etc.

[1227] The "adjustment means" has the function of dynamically changing and adjusting recommended content based on the recognized emotional information.

[1228] "Recommended content" refers to learning materials, successful people's experiences, recommended study schedules, necessary cost information, etc., provided based on analyzed user information and emotional state.

[1229] The present invention is a system that inputs and analyzes user information to provide optimal recommended content, and further recognizes the user's emotions in real time and adaptively adjusts the recommended content based on the emotions. An embodiment of this system will be described in detail below.

[1230] First, the user accesses the system and logs in. The user logs in by entering account information (username, password). After logging in, the terminal displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals. The user enters this information and clicks the submit button. This sends the entered information from the terminal to the server.

[1231] The server receives the transmitted user information and stores it in an internal database. The server then inputs the stored user information into a generative AI model to generate recommended content based on the user's goals. This recommended content includes learning materials, success stories, recommended study schedules, and cost information. The generated recommended content is sent from the server to the device, which then displays the received recommended content to the user.

[1232] Furthermore, the present invention incorporates an emotion recognition means. The emotion recognition means monitors the user's facial expressions and voice in real time when inputting information, and identifies the user's emotional state (joy, sadness, surprise, anger, etc.). The recognized emotion information is sent to the server and considered by the analysis means. The server adjusts the recommended content based on this emotion information. For example, if the user is feeling stressed, the server may provide recommended content including relaxing content, and if the user is excited, the server may provide an efficient study plan that utilizes the user's concentration.

[1233] As an actual use case, consider a case where a user has the goal of "buying the latest gadget." In this case, the information the user inputs includes name, age, occupation, area of ​​interest (latest gadgets), goal (buying the latest gadget), etc. The emotion recognition means detects the emotional state of the user when inputting and provides recommended content accordingly. For example, if the user is in an excited state, it generates recommended content that introduces particularly noteworthy new products.

[1234] To realize the system of this invention, the following hardware and software are required. The hardware requires a terminal equipped with a camera and microphone for inputting user information and recognizing emotions. The software includes face recognition using Python and OpenCV, a generative AI model using TensorFlow, and emotion analysis using Transformers. Specifically, OpenCV is used for analyzing user facial expressions, and a Transformers model is used for emotion recognition. A generative AI model using TensorFlow is used to generate recommended content.

[1235] An example prompt is:

[1236] "If a user is interested in the latest gadget and is looking to buy it, the system will generate appropriate content recommendations based on the user's profile information and real-time emotional state."

[1237] As a result, the system of the present invention is able to provide a more personalized service that responds to the individual needs and emotional state of the user.

[1238] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1239] Step 1:

[1240] A user accesses the system and logs in.

[1241] Specifically, the user enters and submits account information (user name, password). This information is then sent to the server, which performs authentication and starts a session if the authentication is successful.

[1242] Input: Username, Password

[1243] Output: Authentication result (success / failure), session start

[1244] Step 2:

[1245] The device displays a form for the user to enter basic information such as name, age, occupation, areas of interest, and goals.

[1246] Specifically, the terminal displays a form, and after the user has finished entering information, they click the submit button, which is then sent from the terminal to the server.

[1247] Input: User basic information (name, age, occupation, areas of interest, goals)

[1248] Output: User information sent to the server

[1249] Step 3:

[1250] The server receives the transmitted user information and stores it in an internal database.

[1251] Specifically, the server converts the user information into an analyzable format and stores it in a database.

[1252] Input: Submitted user basic information

[1253] Output: User information stored in the internal database

[1254] Step 4:

[1255] The server inputs the stored user information into a generative AI model to generate recommended content based on the user's goals.

[1256] Specifically, the server inputs user information into the AI ​​model and generates recommended content such as learning materials, success stories, recommended study schedules, and necessary cost information.

[1257] Input: User information

[1258] Output: Generated recommended content

[1259] Step 5:

[1260] The generated recommended content is transmitted from the server to the terminal, and the terminal displays the received recommended content to the user.

[1261] Specifically, the server transmits the recommended content to the terminal, which then visually displays the content.

[1262] Input: Generated recommended content

[1263] Output: Recommended content displayed to the user

[1264] Step 6:

[1265] An emotion recognition means monitors the user's facial expressions and voice in real time to identify their emotional state.

[1266] Specifically, the system uses the device's built-in camera and microphone to collect the user's facial expressions and voice data, and analyzes their emotional state using an emotion analysis model.

[1267] Input: User facial and voice data

[1268] Output: Perceived emotional state

[1269] Step 7:

[1270] The recognized emotion information is transmitted to the server and taken into account by the analysis means.

[1271] Specifically, the server receives the user's emotion information and adjusts the recommended content based on the analysis algorithm.

[1272] Input: Emotion information

[1273] Output: Tailored recommended content

[1274] Step 8:

[1275] The adjusted recommended content is sent again to the terminal, which then displays it again to the user.

[1276] Specifically, the server transmits the adjusted recommended content to the terminal, and the terminal displays the new content.

[1277] Input: Tailored recommended content

[1278] Output: Recommended content redisplayed to the user

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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.

[1284] 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.

[1285] 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).

[1286] 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.

[1287] 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."

[1288] 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.

[1289] 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).

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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.

[1297] 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.

[1298] 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.

[1299] 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.

[1300] The following is further disclosed regarding the above embodiment.

[1301] (Claim 1)

[1302] an input means for inputting user information;

[1303] a transmitting means for transmitting the input user information;

[1304] a receiving means for receiving the transmitted user information;

[1305] an analysis means for analyzing the received user information and generating recommended content according to the user's goals;

[1306] a display means for displaying the generated recommended content;

[1307] A system including:

[1308] (Claim 2)

[1309] 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

[1310] (Claim 3)

[1311] 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information.

[1312] "Example 1"

[1313] (Claim 1)

[1314] an input means for inputting user information;

[1315] a transmitting means for transmitting the input user information;

[1316] a receiving means for receiving the transmitted user information;

[1317] a storage means for storing the received user information in a database;

[1318] an input means for inputting the stored user information into the generative AI model;

[1319] A generating means for generating recommended content according to a user goal;

[1320] a transmitting means for transmitting the generated recommended content;

[1321] a display means for displaying the transmitted recommended content;

[1322] A system including:

[1323] (Claim 2)

[1324] 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

[1325] (Claim 3)

[1326] 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information.

[1327] "Application Example 1"

[1328] (Claim 1)

[1329] an input means for inputting user information;

[1330] a transmitting means for transmitting the input user information;

[1331] a receiving means for receiving the transmitted user information;

[1332] an analysis means for analyzing the received user information and generating recommended content according to the user's goals;

[1333] a display means for displaying the generated recommended content;

[1334] a notification mechanism that sends notifications based on a recommended study schedule;

[1335] progress management means for tracking the user's learning progress;

[1336] A system including:

[1337] (Claim 2)

[1338] 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

[1339] (Claim 3)

[1340] 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information.

[1341] "Example 2: Combining Emotion Engines"

[1342] (Claim 1)

[1343] an input means for inputting user information;

[1344] a transmitting means for transmitting the input user information;

[1345] a receiving means for receiving the transmitted user information;

[1346] an analysis means for analyzing the received user information and generating recommended content according to the user's goals;

[1347] a display means for displaying the generated recommended content;

[1348] an emotion engine for recognizing the emotion of a user when inputting information;

[1349] emotion information receiving means for receiving emotion information recognized by the emotion engine;

[1350] an analysis means for adjusting recommended content based on the received emotional information;

[1351] A system including:

[1352] (Claim 2)

[1353] 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

[1354] (Claim 3)

[1355] 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information.

[1356] "Application example 2 when combining emotion engines"

[1357] (Claim 1)

[1358] an input means for inputting user information;

[1359] a transmitting means for transmitting the input user information;

[1360] a receiving means for receiving the transmitted user information;

[1361] an analysis means for analyzing the received user information and generating recommended content according to the user's goals;

[1362] a display means for displaying the generated recommended content;

[1363] emotion recognition means for recognizing and considering the user's emotions in real time;

[1364] an adjusting means for adjusting recommended content based on emotion recognition information of the user;

[1365] A system including:

[1366] (Claim 2)

[1367] 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

[1368] (Claim 3)

[1369] 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information. [Explanation of symbols]

[1370] 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. an input means for inputting user information; a transmitting means for transmitting the input user information; a receiving means for receiving the transmitted user information; an analysis means for analyzing the received user information and generating recommended content according to the user's goals; a display means for displaying the generated recommended content; A system including:

2. 2. The system according to claim 1, wherein the user information includes name, age, occupation, areas of interest, and goals.

3. 2. The system according to claim 1, wherein the recommended content includes study materials, success stories, recommended study schedules, and necessary cost information.

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