System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving basic investment questions from a user; means for generating and presenting to the user basic investment information relevant to the questions; means for generating and displaying to the user interactive learning content in the form of a quiz; means for receiving user answers to the quiz and analyzing the answers to generate feedback; and means for presenting the feedback to the user.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] The current situation in Japan is that most of the financial assets of households are concentrated in savings, with little investment in financial products such as stocks and investment trusts. This is due to psychological barriers such as "investing is gambling" and "I don't want to lose money," which prevent many people from taking the first step. Furthermore, the difficulty of efficiently obtaining accurate and reliable information also presents challenges, leading to a lack of knowledge about investing and increased anxiety. To solve this, there is a need for support measures that enable beginner and intermediate investors to efficiently obtain accurate information, deepen their understanding of investing, and take actual investment action. [Means for solving the problem]

[0005] The present invention provides a system for enabling investors from beginners to intermediate investors to efficiently learn about investment information and to support their actual investment activities. The system includes the following means.

[0006] 1. A means for receiving basic questions about investments from users, generating appropriate basic information about investments in response to those questions, and presenting it to the users. Also, a means for generating interactive learning content in the form of quizzes and displaying it to the users, allowing the users to learn about investments while having fun.

[0007] 2. A means of receiving the user's answers to the quiz, analyzing the answers, generating feedback, and presenting it to the user, allowing the user to assess their understanding and progress further.

[0008] 3. A means for receiving questions from users about how to open a securities account, aggregating information on opening an appropriate securities account in response to those questions, and presenting it to the user. Also, a means for aggregating information again in response to additional questions from users, generating answers, and presenting them to the user. This allows users to smoothly proceed with specific investment preparations.

[0009] 4. A means for receiving a question about a company's analysis from a user, and collecting and summarizing the company's public information, stock price charts, and related news reports in response to the question. Then, a means for generating a company analysis report based on the summarized information and presenting it to the user. Also, a means for collecting information again in response to additional questions from the user, generating and presenting answers. This allows the user to make investment decisions based on in-depth analysis and understanding.

[0010] By combining these methods, users can gradually deepen their knowledge about investing and receive support to take concrete action, effectively eliminating the psychological barriers and lack of information regarding investing.

[0011] "User" refers to a person who uses this system to receive investment information and support.

[0012] A "server" is a computer system that acquires and generates information in response to user requests and sends it to terminals.

[0013] A "terminal" is a device that is directly operated by a user and displays information sent from a server.

[0014] "Basic information about investing" refers to the basic knowledge necessary to make an investment, such as investment concepts, methods, risks, and benefits.

[0015] "Quiz-style interactive learning content" refers to educational content that is presented in the form of questions so that users can actively participate and advance their learning.

[0016] "Feedback" refers to information such as grades, evaluations, and advice for improvement that are displayed based on the user's quiz answers.

[0017] "Information regarding opening a securities account" refers to specific information such as the procedures and documents required to open a securities account, and a list of recommended securities companies.

[0018] "Corporate public information" refers to information such as financial reports, press releases, and business plans that a company makes public.

[0019] A "stock price chart" is a graph that visually represents fluctuations in stock prices over a specific period of time.

[0020] "Relevant coverage" refers to information that is useful for making investment decisions, such as the latest news and analytical articles about companies and markets.

[0021] A "corporate analysis report" is a report that summarizes a company's financial situation, performance, future outlook, etc. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0030] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0043] This invention is a system that allows beginners to intermediate investors to efficiently learn about investment information and support their actual investment activities. This system is mainly comprised of users, servers, and terminals, and operates smoothly through the interaction of these elements.

[0044] A natural language description of the program's operation

[0045] 1. Support for understanding the basics of investing

[0046] User: Launches the application and enters a request: "I want to learn the basics of investing."

[0047] Terminal: Sends the user's request to the server.

[0048] Server: Generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.) and also creates interactive learning content in the form of quizzes.

[0049] Server: Sends the generated information and quiz content to the device.

[0050] Terminal: Displays the submitted information and quiz content to the user.

[0051] User: Answers the quiz and sends the answers to the device.

[0052] Server: Collects user answers, analyzes correct and incorrect answers, generates feedback, and sends it to the device.

[0053] Terminal: Display feedback to the user.

[0054] 2. Discussion Consulting (1) How to Start Investing

[0055] User: Enter a question about opening a brokerage account.

[0056] Terminal: Sends a question to the server.

[0057] Server: Searches for and aggregates the necessary information about opening a brokerage account (e.g., required documents, procedural steps, and a list of reputable brokerage firms) in a concise format.

[0058] Server: Sends the generated information to the terminal.

[0059] Terminal: displays information to the user.

[0060] User: Review the information and enter any additional questions.

[0061] Terminal: Sends a follow-up question to the server.

[0062] Server: Aggregates information from additional questions, generates answers, and sends them to the device.

[0063] Terminal: Display the answer to the user.

[0064] 3. Discussion Consulting (2) Market and Company Analysis

[0065] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[0066] Terminal: Sends the request to the server.

[0067] Server: Collects and summarizes company public information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[0068] Server: Generates a company analysis report based on the summarized information and sends it to the terminal.

[0069] Terminal: Display company analysis reports to the user.

[0070] User: Review the analysis report and enter any additional questions.

[0071] Terminal: Sends a follow-up question to the server.

[0072] Server: Collects information again for any additional questions, generates answers, and sends them to the device.

[0073] Terminal: Display the answer to the user.

[0074] 4. Investment simulation in a virtual environment

[0075] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0076] Terminal: Sends the request to the server.

[0077] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[0078] Server: Runs a double-speed simulation in the configured virtual environment and generates results (e.g., if held for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen).

[0079] Server: Sends the simulation results to the device.

[0080] Terminal: Displays the results to the user.

[0081] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, virtual investment simulations allow users to understand risks before actually starting an investment and deepen their knowledge for safe investments.

[0082] The processing flow will be explained below.

[0083] Support for understanding the basics of investing

[0084] Step 1:

[0085] User: Launches the application and enters a request: "I want to learn the basics of investing."

[0086] Step 2:

[0087] Terminal: Sends the user's request to the server.

[0088] Step 3:

[0089] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[0090] Step 4:

[0091] Server: Sends the generated basic information and quiz content to the device.

[0092] Step 5:

[0093] Terminal: Displays the submitted basic information and quiz content to the user.

[0094] Step 6:

[0095] User: Takes a quiz and enters the answer into the device.

[0096] Step 7:

[0097] Terminal: Sends the user's answer to the server.

[0098] Step 8:

[0099] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[0100] Step 9:

[0101] Server: Sends feedback to the device.

[0102] Step 10:

[0103] Terminal: Display feedback to the user.

[0104] Consulting (1) How to get started with investing

[0105] Step 1:

[0106] User: Enter a question about opening a brokerage account.

[0107] Step 2:

[0108] Terminal: Sends a question to the server.

[0109] Step 3:

[0110] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[0111] Step 4:

[0112] Server: Sends the aggregated information to the device.

[0113] Step 5:

[0114] Terminal: displays information to the user.

[0115] Step 6:

[0116] User: Review the information and re-enter any additional questions.

[0117] Step 7:

[0118] Terminal: Sends a follow-up question to the server.

[0119] Step 8:

[0120] Server: Re-aggregates information and generates answers for additional questions.

[0121] Step 9:

[0122] Server: Sends the generated answer to the device.

[0123] Step 10:

[0124] Terminal: Display the answer to the user.

[0125] Discussion Consulting (2) Market and Company Analysis

[0126] Step 1:

[0127] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[0128] Step 2:

[0129] Terminal: Sends the request to the server.

[0130] Step 3:

[0131] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[0132] Step 4:

[0133] Server: Summarizes the collected data and generates company analysis reports.

[0134] Step 5:

[0135] Server: Sends the generated company analysis report to the terminal.

[0136] Step 6:

[0137] Terminal: Display company analysis reports to the user.

[0138] Step 7:

[0139] User: Review the analysis report and enter any additional questions.

[0140] Step 8:

[0141] Terminal: Sends a follow-up question to the server.

[0142] Step 9:

[0143] Server: Collects information again for additional questions and generates answers.

[0144] Step 10:

[0145] Server: Sends the generated answer to the device.

[0146] Step 11:

[0147] Terminal: Display the answer to the user.

[0148] Investment simulation in a virtual environment

[0149] Step 1:

[0150] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0151] Step 2:

[0152] Terminal: Sends the request to the server.

[0153] Step 3:

[0154] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[0155] Step 4:

[0156] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[0157] Step 5:

[0158] Server: Sends the generated simulation results to the device.

[0159] Step 6:

[0160] Terminal: displays the simulation results to the user.

[0161] Through the above process steps, users can gradually learn the basics of investing and receive support for specific investment actions. Through virtual investment simulations, users can understand the risks before actually starting an investment and deepen their knowledge for safe investment.

[0162] Example 1

[0163] 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."

[0164] Conventional investment learning systems lack sufficient interactivity and feedback functions to enable beginners and intermediate users to efficiently learn investment information and support their actual investment behavior. As a result, users encounter many difficulties in the self-learning process and are at a high risk of making incorrect decisions. The present invention aims to solve these problems and provide a system that enables users to efficiently learn investment information and supports their actual investment behavior.

[0165] 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.

[0166] In this invention, the server includes means for receiving basic investment questions from a user, means for generating appropriate basic investment information in response to the questions and presenting it to the user, means for generating interactive learning content in the form of a quiz using a generative AI model and displaying it to the user, means for receiving answers to the quizzes from the user, analyzing the answers and generating feedback, and means for presenting the feedback to the user. This allows the user to intuitively acquire investment knowledge and prepare for actual investment behavior.

[0167] "User" refers to an individual or organization who uses the system to obtain investment information, learn, or ask questions.

[0168] A "server" is a dedicated computer system that receives requests from users, generates information about appropriate investments, and provides feedback and content.

[0169] A "terminal" is a device (e.g., smartphone, tablet, or PC) that a user uses to communicate with a server, obtain information, and perform operations.

[0170] "Basic information about investments" refers to information that includes the definition of investments, basic investment knowledge and terminology such as stocks and bonds.

[0171] A "generative AI model" is a model generated using artificial intelligence technology, and is a program that generates appropriate responses to user input.

[0172] "Quiz-style interactive learning content" refers to educational content designed to enable users to acquire knowledge about investments by answering quizzes.

[0173] "Feedback" is a response to a user's quiz answers, including whether they were correct or incorrect, as well as additional study information and advice.

[0174] "Basic questions" are questions that users ask the server about basic knowledge and procedures related to investment.

[0175] "Information on opening a securities account" refers to information on the documents and procedural steps required to open a securities account, as well as information on recommended securities companies.

[0176] A "corporate analysis report" is a document containing a summary and analysis results generated from public information, stock price charts, and related press reports of a specific company.

[0177] A "virtual investment environment" is a simulation environment in which users can make virtual investments and predict investment results using actual market data.

[0178] MODE FOR CARRYING OUT THE INVENTION

[0179] The present invention is a system that allows users to efficiently learn about investment information and supports actual investment behavior, and is operated through the interaction of users, a server, and terminals. Specifically, the system is implemented in the following manner.

[0180] Hardware and software used

[0181] Hardware: Server (general cloud-based server system), user device (smartphone, tablet, PC)

[0182] Software: Investment learning applications, generative AI models (e.g., GPT-3), database management systems (e.g., MySQL), data collection APIs (e.g., Google Finance API)

[0183] System operation explanation

[0184] 1. Support for understanding the basics of investing

[0185] The user starts the application and inputs a request to learn the basics of investing. For example, the user directly inputs "I want to learn the basics of investing."

[0186] The device sends the user's request to the server. The request data is sent in JSON format.

[0187] The server retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates quiz-style learning content using a generative AI model (e.g., GPT-3).

[0188] The server transmits the generated information and quiz content to the terminal.

[0189] The terminal visually displays the transmitted information and quiz content to the user.

[0190] The user answers the quiz and transmits the answers to the terminal.

[0191] The server analyzes the user's answers, generates feedback, and sends it to the terminal.

[0192] The terminal displays the feedback to the user.

[0193] Examples:

[0194] Prompt: "I want to learn the basics of investing."

[0195] Example feedback: "Your answer is correct! You understand the basics of investing."

[0196] 2. Discussion Consulting (1) How to Start Investing

[0197] The user inputs a question about opening a securities account, for example, "What documents do I need to open a securities account?"

[0198] The terminal sends a query to the server.

[0199] The server collects information regarding the opening of a securities account, compiles it into a concise form, and transmits it to the terminal.

[0200] The terminal displays the transmitted information to the user.

[0201] The user will review the information and re-enter any additional questions.

[0202] The terminal sends a follow-up question to the server.

[0203] The server aggregates the information for the additional questions, generates an answer, and sends it to the terminal.

[0204] The terminal displays the answer to the user.

[0205] Examples:

[0206] Prompt: "What documents do I need to open a brokerage account?"

[0207] Example feedback: "The documents required are identification (passport or driver's license), proof of current address (resident registration card), etc."

[0208] 3. Discussion Consulting (2) Market and Company Analysis

[0209] A user requests an analysis of a specific company, for example, "Tell me about the recent performance of Company X."

[0210] The terminal sends a request to the server.

[0211] The server collects public company information, stock charts, and related press reports, and generates company analysis reports.

[0212] The server transmits the generated company analysis report to the terminal.

[0213] The terminal displays the company analysis report to the user.

[0214] The user reviews the report and re-enters any additional questions.

[0215] The terminal sends a follow-up question to the server.

[0216] The server collects information for the additional questions, generates answers, and sends them to the terminal.

[0217] The terminal displays the answer to the user.

[0218] Examples:

[0219] Prompt: "Tell me about Company X's recent performance."

[0220] Example feedback: "Company X has seen a 10% increase in sales compared to the same month last year, and a 15% increase in profits."

[0221] 4. Investment simulation in a virtual environment

[0222] The user requests an investment simulation in a virtual environment, for example, by entering "What would happen if I invested 100,000 yen for three years?"

[0223] The terminal sends a request to the server.

[0224] The server sets up a virtual investment environment based on the user's input data (e.g., investment amount, investment period).

[0225] The server runs the simulation in the virtual environment and generates the results.

[0226] The server transmits the simulation results to the terminal.

[0227] The terminal displays the simulation results to the user.

[0228] Examples:

[0229] Prompt: "What would happen if you invested $1,000 for three years?"

[0230] Example feedback: "If you hold the investment for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen."

[0231] This allows users to understand the risks before they actually begin investing and deepen the knowledge they need to make appropriate decisions.

[0232] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0233] 1. Support for understanding the basics of investing

[0234] Step 1:

[0235] A user launches the application and types, "I want to learn the basics of investing."

[0236] Input: User request ("I want to learn the basics of investing")

[0237] What it does: Enter a request into a text input field within the app.

[0238] Output: Request data (text format)

[0239] Step 2:

[0240] The device sends a request to the server.

[0241] Input: User request data

[0242] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[0243] Output: Request data sent to the server

[0244] Step 3:

[0245] The server generates basic information about investments and creates learning content in the form of quizzes.

[0246] Input: Request data

[0247] How it works: It retrieves basic investment information from a database and uses a generative AI model (e.g., GPT-3) to generate interactive learning content in the form of quizzes.

[0248] Output: Basic information and quiz content (JSON format)

[0249] Step 4:

[0250] The server transmits the generated information and quiz content to the terminal.

[0251] Input: Basic information and quiz content

[0252] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[0253] Output: Data sent to the terminal

[0254] Step 5:

[0255] The terminal displays the transmitted information and quiz content to the user.

[0256] Input: Data from the server

[0257] Behavior: Parses the received JSON data and visually displays basic information and quiz content on the screen.

[0258] Output: The information displayed to the user and the quiz

[0259] Step 6:

[0260] The user answers the quiz and transmits the answers to the terminal.

[0261] Input: User's quiz answer

[0262] Action: Enter the quiz answer in the input field and press the submit button.

[0263] Output: Quiz answers sent to the device

[0264] Step 7:

[0265] The server collects the user's answers, analyzes whether they are correct or incorrect, and generates feedback.

[0266] Input: Quiz response data

[0267] How it works: Your answers are matched against existing ground truth data and feedback is generated using a generative AI model.

[0268] Output: Feedback data (JSON format)

[0269] Step 8:

[0270] The server sends the feedback to the device.

[0271] Input: Feedback data

[0272] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[0273] Output: Feedback data sent to the device

[0274] Step 9:

[0275] The device displays the feedback to the user.

[0276] Input: Feedback data

[0277] Behavior: Parses the received JSON data and displays feedback on the screen.

[0278] Output: Feedback displayed to the user

[0279] 2. Discussion Consulting (1) How to Start Investing

[0280] Step 1:

[0281] The user enters a question about opening a securities account.

[0282] Input: User question ("What documents do I need to open a brokerage account?")

[0283] What it does: Type a question into a text input field within the app.

[0284] Output: Question data (text format)

[0285] Step 2:

[0286] The terminal sends a question to the server.

[0287] Input: User question data

[0288] What it does: It converts question data into JSON format and sends it to the server via HTTP protocol.

[0289] Output: Question data sent to the server

[0290] Step 3:

[0291] The server collects and summarizes information about opening a securities account.

[0292] Input: User question data

[0293] What it does: Retrieves the necessary information from databases and external APIs, then aggregates and summarizes the information concisely.

[0294] Output: Aggregated information data (JSON format)

[0295] Step 4:

[0296] The server transmits the generated information to the terminal.

[0297] Input: Aggregated information data

[0298] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[0299] Output: Information data sent to the terminal

[0300] Step 5:

[0301] The terminal displays the information to the user.

[0302] Input: Information data from the server

[0303] What it does: Parses the received JSON data and displays the information visually on the screen.

[0304] Output: Information displayed to the user

[0305] Step 6:

[0306] The user enters a follow-up question.

[0307] Input: User's additional question

[0308] Action: Enter a follow-up question into the text entry field.

[0309] Output: Additional question data (text format)

[0310] Step 7:

[0311] The terminal sends a follow-up question to the server.

[0312] Input: User's additional question data

[0313] Behavior: The question data is converted to JSON format and sent to the server.

[0314] Output: Additional question data sent to the server

[0315] Step 8:

[0316] The server aggregates the information for the follow-up questions and generates an answer.

[0317] Input: Additional question data

[0318] What it does: Recollects information from databases and external APIs and generates answers.

[0319] Output: Generated response data (JSON format)

[0320] Step 9:

[0321] The server sends the response to the terminal.

[0322] Input: Generated response data

[0323] What it does: Composes data in JSON format and sends it to the device.

[0324] Output: Answer data sent to the device

[0325] Step 10:

[0326] The terminal displays the answer to the user.

[0327] Input: Response data from the server

[0328] Behavior: Parses the received JSON data and displays the answer on the screen.

[0329] Output: The answer displayed to the user

[0330] 3. Discussion Consulting (2) Market and Company Analysis

[0331] Step 1:

[0332] A user requests an analysis of a specific company.

[0333] Input: User's company analysis request ("Tell me about company X's recent performance")

[0334] What it does: Enter a request into a text input field within the app.

[0335] Output: Request data (text format)

[0336] Step 2:

[0337] The device sends a request to the server.

[0338] Input: User request data

[0339] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[0340] Output: Request data sent to the server

[0341] Step 3:

[0342] The server collects and summarizes company public information, stock charts, and related press coverage.

[0343] Input: User request data

[0344] What it does: Uses databases and external APIs to collect and summarize company public information, stock charts, and related press.

[0345] Output: Summarized company information data (JSON format)

[0346] Step 4:

[0347] The server generates a company analysis report and sends it to the terminal.

[0348] Input: Summarized company information data

[0349] What it does: Generates a company analysis report based on the summary data and sends it to the device in JSON format.

[0350] Output: Generated company analysis report data (JSON format)

[0351] Step 5:

[0352] The terminal displays the company analysis report to the user.

[0353] Input: Report data from the server

[0354] What it does: Parses the received JSON data and displays a report on the screen.

[0355] Output: Company analysis report displayed to the user

[0356] Step 6:

[0357] The user enters a follow-up question.

[0358] Input: User's additional question

[0359] Action: Enter a follow-up question into the text entry field.

[0360] Output: Additional question data (text format)

[0361] Step 7:

[0362] The terminal sends a follow-up question to the server.

[0363] Input: User's additional question data

[0364] Behavior: The question data is converted to JSON format and sent to the server.

[0365] Output: Additional question data sent to the server

[0366] Step 8:

[0367] The server recollects information for additional questions and generates answers.

[0368] Input: Additional question data

[0369] How it works: Generates an answer based on the recollected information and sends it to the device in JSON format.

[0370] Output: Generated response data (JSON format)

[0371] Step 9:

[0372] The server sends the response to the terminal.

[0373] Input: Generated response data

[0374] What it does: Composes data in JSON format and sends it to the device.

[0375] Output: Answer data sent to the device

[0376] Step 10:

[0377] The terminal displays the answer to the user.

[0378] Input: Response data from the server

[0379] Behavior: Parses the received JSON data and displays the answer on the screen.

[0380] Output: The answer displayed to the user

[0381] 4. Investment simulation in a virtual environment

[0382] Step 1:

[0383] A user requests an investment simulation.

[0384] Input: User simulation request ("What happens if I invest $1,000 for three years?")

[0385] What it does: Enter a request into a text input field within the app.

[0386] Output: Request data (text format)

[0387] Step 2:

[0388] The device sends a request to the server.

[0389] Input: User request data

[0390] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[0391] Output: Request data sent to the server

[0392] Step 3:

[0393] The server sets up a virtual investment environment based on the user's input data.

[0394] Input: Request data (investment amount, investment period, etc.)

[0395] How it works: Runs an algorithm to create a virtual investment environment based on input data.

[0396] Output: Set virtual investment environment data

[0397] Step 4:

[0398] The server runs the double-speed simulation in a configured virtual environment and generates the results.

[0399] Input: Hypothetical investment environment data

[0400] How it works: Runs simulations twice as fast in a virtual environment to calculate investment results.

[0401] Output: Simulation result data (e.g., 115,700 yen over 3 years at an annual interest rate of 5%)

[0402] Step 5:

[0403] The server transmits the simulation results to the terminal.

[0404] Input: Simulation result data

[0405] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[0406] Output: Simulation result data sent to the terminal

[0407] Step 6:

[0408] The terminal displays the simulation results to the user.

[0409] Input: Simulation result data

[0410] Operation: Parses the received JSON data and visually displays the simulation results on the screen.

[0411] Output: Simulation results displayed to the user

[0412] This allows users to intuitively acquire investment knowledge and prepare for actual investment actions. Virtual investment simulations also allow users to understand risks and deepen their knowledge for safe investments.

[0413] (Application example 1)

[0414] 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."

[0415] Existing systems that enable users from beginners to intermediate investors to efficiently learn investment information and support actual investment activities tend to be one-way, lacking interactivity. It was also difficult to provide a wide range of information and support necessary for investing, such as opening a securities account, company analysis, and virtual investment simulations, all in one system. Therefore, a system was needed that would allow users to intuitively learn about investment from the basics to advanced applications, while also allowing them to move smoothly and safely into actual investment activities.

[0416] 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.

[0417] In this invention, the server includes: means for receiving basic investment questions from a user; means for generating appropriate basic investment information in response to the questions and presenting it to the user; means for generating quiz-style interactive learning content and displaying it to the user; means for receiving user answers to the quizzes and analyzing the answers to generate feedback; means for presenting the feedback to the user; means for receiving user questions regarding company analysis; means for collecting and summarizing public company information, stock price charts, and related news reports in response to the questions; means for generating a company analysis report based on the summarized information; means for presenting the company analysis report to the user; means for re-collecting information in response to additional user questions and generating answers; means for presenting the answers to the user; means for receiving user requests for virtual investment simulations; means for designing a virtual investment environment based on the request; means for executing a virtual simulation and generating results; and means for presenting the simulation results to the user. This provides comprehensive support for users as they transition to actual investment behavior while consistently learning about investment from the basics to applications and practice, enabling beginners to intermediate investors to invest safely and efficiently.

[0418] "User" refers to a person who uses the electronic payment application to learn investment-related information and take actual investment actions.

[0419] "Server" refers to a computer system that generates investment information in response to a request from a user and provides it to the user.

[0420] "Basic information" refers to basic knowledge and definitions of investment, as well as information on basic investment vehicles such as stocks and bonds.

[0421] "Quiz" refers to an interactive set of questions that allows users to test their investing knowledge.

[0422] "Interactive learning content" refers to learning materials and activities that progress through two-way interaction between the user and the system.

[0423] "Feedback" refers to evaluations and advice information generated by the system through analysis of users' quiz answers and requests.

[0424] "Company analysis" refers to the process of evaluating the performance and market position of a particular company using public information, stock charts, and related press coverage.

[0425] "Public information" refers to information such as financial reports and press releases that companies make public.

[0426] "Virtual investment simulation" refers to a system that predicts investment results in a virtual investment environment based on the investment amount and period specified by the user.

[0427] "Virtual investment environment" refers to virtual market conditions and investment conditions for simulations set based on user input data.

[0428] "Results" refers to the predicted investment return and risk output based on a hypothetical investment simulation.

[0429] This invention is a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities. The system is mainly operated through the interaction between the server, terminals, and users. The implementation method for each main function is shown below.

[0430] First, the system has a means for receiving basic questions about investment from users. When a user inputs a question about the basics of investing from a terminal, the request is sent to the server. The server generates basic information about investment and presents it to the user. This basic information is provided as interactive learning content in the form of quizzes to make it easy for beginners to understand, such as the definitions of stocks and bonds. For example, in response to the question, "What is investment?", the system provides feedback in the form of a quiz, such as, "Investment is a means of increasing funds."

[0431] The server then receives questions from users about how to open a securities account and aggregates the appropriate information to present to the user. When a user requests "How do I open a securities account?" via a terminal, the server provides the necessary documents, procedural steps, a list of highly rated securities companies, and so on.

[0432] Furthermore, the system has a function to receive questions about company analysis from users. When a user types "Tell me about Company X's latest performance," the server collects and summarizes the company's public information, stock price charts, and related news reports. It then generates a company analysis report based on the summarized information and presents it to the user.

[0433] It also has a virtual investment simulation function. When a user inputs a request into the terminal, such as "What will be the results if I invest 100,000 yen for three years?", the request is sent to the server. The server designs a virtual investment environment based on the data entered by the user, runs a simulation, and generates the results. The simulation results are presented to the user via the terminal. For example, if you hold the investment for three years under the condition of an annual interest rate of 5%, the total amount will be approximately 115,700 yen.

[0434] This system is implemented using programming languages ​​such as Python, and frameworks and libraries (e.g., Flask and Django) for managing HTTP requests. The server runs on a RESTful API, and the database stores the latest investment information, company disclosures, and user learning history. It also uses machine learning models to analyze users' quiz answers and simulation results and generate personalized feedback and advice.

[0435] To illustrate this, here are some example prompts generated using a generative AI model:

[0436] Prompt Sentence Examples

[0437] "A user types in 'What is the recent performance of Company X?' The server processes it in the following steps:

[0438] 1. Search for public information about Company X.

[0439] 2. Collect financial reports, press releases, and related media coverage.

[0440] 3. Summarize the collected information and generate a company analysis report.

[0441] 4. Provide the generated report to the user.

[0442] In this way, the user is supported in making safe and efficient investment decisions while consistently learning everything from the basics to the practical aspects of investing.

[0443] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0444] Step 1:

[0445] The user enters basic investment questions.

[0446] In this step, the user launches the smartphone app and inputs a request such as "I want to learn the basics of investing." The input request is sent to the server via the device. The input data is natural language text data containing the user's question.

[0447] Step 2:

[0448] The server generates basic information about the investment and presents it to the user.

[0449] The server analyzes the received question data and generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.). The generated data is organized into interactive learning content in the form of a quiz. The generated information and quiz content are then sent back to the device. In this step, the server uses a generative AI model to generate this data.

[0450] Step 3:

[0451] The terminal displays the transmitted information and quiz content to the user.

[0452] The terminal receives the information from the server and displays it to the user, who then inputs answers to the displayed quiz questions.

[0453] Step 4:

[0454] The server receives the user's quiz answers, analyzes them and generates feedback.

[0455] The user's answer data is sent from the device to the server. The server analyzes this data and determines whether the user's answer is correct or incorrect. Feedback is generated based on the analysis results and sent to the device. Here too, a generative AI model is used to generate the feedback.

[0456] Step 5:

[0457] The terminal displays the feedback to the user.

[0458] The device displays the feedback received from the server to the user, including whether the answer was correct or incorrect and any additional advice.

[0459] Step 6:

[0460] A user requests an analysis of a specific company.

[0461] The user inputs a request such as "Tell me about the recent performance of Company X." The input data is sent to the server via the terminal.

[0462] Step 7:

[0463] The server collects and summarizes company public information, stock charts, and related press coverage.

[0464] Based on the received request, the server searches and collects public information, stock charts, and related press reports related to Company X. The collected data is then summarized and organized into a company analysis report. This summarization process utilizes a generative AI model.

[0465] Step 8:

[0466] The terminal presents the company analysis report to the user.

[0467] The terminal displays the company analysis report received from the server to the user, who then checks the contents.

[0468] Step 9:

[0469] A user requests a virtual investment simulation.

[0470] The user inputs a request such as "What will be the result if I invest 100,000 yen for three years?" The input data is sent to the server via the terminal.

[0471] Step 10:

[0472] The server designs the virtual investment environment and runs the simulation.

[0473] The server designs a virtual investment environment based on user input data (investment amount, investment period, etc.), then runs a virtual simulation to generate investment results. The simulation is performed using a generative AI model and simulation algorithm.

[0474] Step 11:

[0475] The terminal presents the simulation results to the user.

[0476] The terminal receives simulation results from the server and displays them to the user, including estimated investment returns and risk information.

[0477] 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.

[0478] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[0479] A natural language description of the program's operation

[0480] 1. Support for understanding the basics of investing

[0481] User: Launches the application and enters a request: "I want to learn the basics of investing."

[0482] Terminal: Sends the user's request to the server.

[0483] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[0484] Server: Sends the generated basic information and quiz content to the device.

[0485] Terminal: Displays the submitted basic information and quiz content to the user.

[0486] User: Takes a quiz and enters the answer into the device.

[0487] Terminal: Sends the user's answer to the server.

[0488] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[0489] Server: Sends feedback to the device.

[0490] Terminal: Display feedback to the user.

[0491] 2. Discussion Consulting (1) How to Start Investing

[0492] User: Enter a question about opening a brokerage account.

[0493] Terminal: Sends a question to the server.

[0494] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[0495] Server: Sends the aggregated information to the device.

[0496] Terminal: displays information to the user.

[0497] User: Review the information and re-enter any additional questions.

[0498] Terminal: Sends a follow-up question to the server.

[0499] Server: Re-aggregates information and generates answers for additional questions.

[0500] Server: Sends the generated answer to the device.

[0501] Terminal: Display the answer to the user.

[0502] 3. Discussion Consulting (2) Market and Company Analysis

[0503] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[0504] Terminal: Sends the request to the server.

[0505] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[0506] Server: Summarizes the collected data and generates company analysis reports.

[0507] Server: Sends the generated company analysis report to the terminal.

[0508] Terminal: Display company analysis reports to the user.

[0509] User: Review the analysis report and enter any additional questions.

[0510] Terminal: Sends a follow-up question to the server.

[0511] Server: Collects information again for additional questions and generates answers.

[0512] Server: Sends the generated answer to the device.

[0513] Terminal: Display the answer to the user.

[0514] 4. Investment simulation in a virtual environment

[0515] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0516] Terminal: Sends the request to the server.

[0517] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[0518] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[0519] Server: Sends the generated simulation results to the device.

[0520] Terminal: displays the simulation results to the user.

[0521] 5. Incorporating an Emotional Engine

[0522] User: Enters questions and commands into the terminal.

[0523] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[0524] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[0525] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[0526] Server: Sends tailored information and feedback to the device.

[0527] Device: Display tailored information and feedback to the user.

[0528] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[0529] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[0530] The processing flow will be explained below.

[0531] Support for understanding the basics of investing

[0532] Step 1:

[0533] User: Launches the application and enters a request: "I want to learn the basics of investing."

[0534] Step 2:

[0535] Terminal: Sends the user's request to the server.

[0536] Step 3:

[0537] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[0538] Step 4:

[0539] Server: Sends the generated basic information and quiz content to the device.

[0540] Step 5:

[0541] Terminal: Displays the submitted basic information and quiz content to the user.

[0542] Step 6:

[0543] User: Takes a quiz and enters the answer into the device.

[0544] Step 7:

[0545] Terminal: Sends the user's answer to the server.

[0546] Step 8:

[0547] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[0548] Step 9:

[0549] Server: Sends feedback to the device.

[0550] Step 10:

[0551] Terminal: Display feedback to the user.

[0552] Consulting (1) How to get started with investing

[0553] Step 1:

[0554] User: Enter a question about opening a brokerage account.

[0555] Step 2:

[0556] Terminal: Sends a question to the server.

[0557] Step 3:

[0558] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[0559] Step 4:

[0560] Server: Sends the aggregated information to the device.

[0561] Step 5:

[0562] Terminal: displays information to the user.

[0563] Step 6:

[0564] User: Review the information and re-enter any additional questions.

[0565] Step 7:

[0566] Terminal: Sends a follow-up question to the server.

[0567] Step 8:

[0568] Server: Re-aggregates information and generates answers for additional questions.

[0569] Step 9:

[0570] Server: Sends the generated answer to the device.

[0571] Step 10:

[0572] Terminal: Display the answer to the user.

[0573] Discussion Consulting (2) Market and Company Analysis

[0574] Step 1:

[0575] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[0576] Step 2:

[0577] Terminal: Sends the request to the server.

[0578] Step 3:

[0579] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[0580] Step 4:

[0581] Server: Summarizes the collected data and generates company analysis reports.

[0582] Step 5:

[0583] Server: Sends the generated company analysis report to the terminal.

[0584] Step 6:

[0585] Terminal: Display company analysis reports to the user.

[0586] Step 7:

[0587] User: Review the analysis report and enter any additional questions.

[0588] Step 8:

[0589] Terminal: Sends a follow-up question to the server.

[0590] Step 9:

[0591] Server: Collects information again for additional questions and generates answers.

[0592] Step 10:

[0593] Server: Sends the generated answer to the device.

[0594] Step 11:

[0595] Terminal: Display the answer to the user.

[0596] Investment simulation in a virtual environment

[0597] Step 1:

[0598] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0599] Step 2:

[0600] Terminal: Sends the request to the server.

[0601] Step 3:

[0602] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[0603] Step 4:

[0604] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[0605] Step 5:

[0606] Server: Sends the generated simulation results to the device.

[0607] Step 6:

[0608] Terminal: displays the simulation results to the user.

[0609] Incorporating an emotion engine

[0610] Step 1:

[0611] User: Enters questions and commands into the terminal.

[0612] Step 2:

[0613] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[0614] Step 3:

[0615] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[0616] Step 4:

[0617] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[0618] Step 5:

[0619] Server: Sends tailored information and feedback to the device.

[0620] Step 6:

[0621] Device: Display tailored information and feedback to the user.

[0622] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[0623] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[0624] Example 2

[0625] 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."

[0626] In systems that enable beginners to intermediate investors to efficiently learn about investment information and support their actual investment behavior, there is a lack of appropriate feedback that takes into account the user's emotional state, making it difficult to effectively learn while reducing stress and anxiety.In addition, there is a problem in that the information is not properly customized, making it difficult to provide personalized investment advice.

[0627] 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 a means for analyzing input data from a user and determining the emotional state, a means for adjusting information and feedback according to the emotional state and presenting it to the user, and a means for generating interactive learning content in the form of a quiz and displaying it to the user. This enables personalized learning support and investment advice that takes the user's emotional state into consideration.

[0628] A "user" is an individual or corporation that uses the system to learn investment information and receives support for actual investment actions.

[0629] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet, that communicates with a server and provides a user interface.

[0630] A "server" is a computer system that receives requests from users, performs the necessary processing, and returns information to the terminal.

[0631] "Quiz-style interactive learning content" refers to educational content in the form of questions and answers, intended to help users acquire knowledge about investments through their participation.

[0632] "Feedback" refers to the reaction or response provided by the system in response to the user's actions or input, and is supplementary information that deepens the user's understanding.

[0633] "Emotional state" refers to the psychological state that a user feels while using the system, and includes stress, anxiety, positive emotions, etc.

[0634] An "emotion engine" is a system that uses artificial intelligence to analyze user input data (text, facial expressions, tone of voice, etc.) and determine the user's emotional state.

[0635] "Basic information about investments" refers to information that includes the definition of investments and basic knowledge about stocks, bonds, etc.

[0636] "Information regarding opening a securities account" refers to information such as the documents required to open a securities account, procedural steps, and a list of recommended securities companies.

[0637] A "corporate analysis report" is an analytical document about a company's financial status and performance, generated based on the company's public information, stock price charts, and related news reports.

[0638] A "virtual investment environment" is an environment for simulating investments using virtual funds without using actual funds.

[0639] "Double-speed simulation" is a method of predicting future results by conducting an investment simulation at a speed faster than the normal rate of time progression.

[0640] "Natural language processing technology" is a technology for analyzing natural language such as text and speech, understanding its meaning, and processing it.

[0641] "Personalized" means providing information and services that are optimized for each individual user.

[0642] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[0643] In this invention, the terminal receives input from the user and sends it to the server. The server performs the necessary processing based on the received request and returns a response to the terminal. Specifically, the following hardware and software are used:

[0644] Hardware used

[0645] Device: Electronic devices such as computers, smartphones, and tablets.

[0646] Server: A high-performance computing system (e.g., cloud server, on-premise server).

[0647] Software used

[0648] Database: MySQL, PostgreSQL.

[0649] NLP (Natural Language Processing) technologies: Generative AI models such as GPT-3 and BERT.

[0650] Quiz generation algorithm: Python script.

[0651] Emotion engine: Text analysis, speech analysis, and facial expression analysis technologies (e.g., Azure Cognitive Services, Amazon Rekognition).

[0652] Specific processing content and operations

[0653] 1. Support for learning the basics of investing

[0654] A user launches the application and types, "I want to learn the basics of investing."

[0655] The terminal sends the user's request to the server, which retrieves basic information about the investment from a database.

[0656] The server generates interactive learning content in the form of a quiz and transmits it to the terminal.

[0657] The terminal displays the quiz content to the user, and the user inputs an answer.

[0658] The server analyzes the user's answers, generates feedback, and sends it to the terminal, which then displays the feedback to the user.

[0659] 2. Discussion Consulting (1) How to Start Investing

[0660] The user enters questions regarding opening a securities account.

[0661] The terminal sends a question to the server, which then gathers the necessary information from a database and generates an answer.

[0662] The terminal displays the information, and if the user enters a follow-up question, it sends it back to the server and receives a new answer.

[0663] 3. Discussion Consulting (2) Market and Company Analysis

[0664] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[0665] The terminal sends a request to the server, which collects public information, summarizes the data, and generates a business analysis report.

[0666] The terminal displays the report, and if the user enters additional questions, it sends them back to the server and receives new answers.

[0667] 4. Investment simulation in a virtual environment

[0668] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0669] The device sends a request to the server, which sets up a virtual environment and runs the simulation.

[0670] The terminal displays the simulation results to the user.

[0671] 5. Incorporating an Emotional Engine

[0672] When the user inputs a question or command, the device sends it to the server, which then requests the emotion engine to analyze the emotion.

[0673] The emotion engine determines the user's emotional state and sends the result to the server.

[0674] The server adjusts the information and feedback based on the emotion analysis results, sends it to the device, and displays it to the user.

[0675] Specific examples

[0676] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server can provide additional step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a positive emotion is detected when a user requests an investment simulation, the server can suggest advanced investment strategies, including risk.

[0677] Examples of prompts are:

[0678] What documents do I need to open a securities account?

[0679] "Tell me about Company X's recent performance."

[0680] "Please simulate what would happen if I invested 100,000 yen for three years."

[0681] This invention allows users to intuitively acquire investment knowledge and prepare for actual investment activities. Emotion analysis by the emotion engine and feedback from that analysis enable users to receive personalized support according to their psychological state.

[0682] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0683] Support for understanding the basics of investing

[0684] Step 1:

[0685] A user launches the application and types, "I want to learn the basics of investing."

[0686] Input: User text input

[0687] Specific actions: A user opens the mobile or web app, types "I want to learn the basics of investing" into the input form, and presses the submit button.

[0688] Output: User request data

[0689] Step 2:

[0690] The terminal sends the user's request to the server.

[0691] Input: User request data

[0692] Specific operation: The terminal sends the user's input data as an HTTP request.

[0693] Output: Request sent to the server

[0694] Step 3:

[0695] The server receives the request and retrieves basic information about the investment from a database.

[0696] Input: Request data

[0697] What it does: The server runs PHP and Python scripts to retrieve basic information for each category from a MySQL database.

[0698] Output: Investment basic information retrieved from the database

[0699] Step 4:

[0700] The server generates interactive learning content in the form of quizzes.

[0701] Input: Basic investment information

[0702] What it does: A Python script runs on the server to analyze the data and generate quiz-style content.

[0703] Output: Generated quiz content

[0704] Step 5:

[0705] The server transmits the generated content to the terminal.

[0706] Input: Generated quiz content

[0707] Specific operation: The quiz content generated by the server is formatted in JSON format and sent to the terminal as an HTTP response.

[0708] Output: Quiz content sent to device

[0709] Step 6:

[0710] The terminal displays the transmitted content to the user.

[0711] Input: Quiz content

[0712] Specific behavior: The device's browser or mobile app parses the JSON data and displays it in the user interface.

[0713] Output: Displayed quiz-style learning content

[0714] Step 7:

[0715] The user answers the quiz and enters the answers into the terminal.

[0716] Input: User's quiz answer

[0717] Specific actions: The user selects an option on the interface, confirms the answer, and presses the submit button.

[0718] Output: Quiz answer data entered on the device

[0719] Step 8:

[0720] The terminal sends the user's answer to the server.

[0721] Input: User response data

[0722] Specific operation: The terminal sends the response data to the server as an HTTP request.

[0723] Output: Response data sent to the server

[0724] Step 9:

[0725] The server analyzes the answers and generates feedback.

[0726] Input: Answer data

[0727] Specific operation: A script on the server analyzes the answer data and generates correct and incorrect answers and supplementary explanations.

[0728] Output: Generated feedback data

[0729] Step 10:

[0730] The server sends the feedback to the device.

[0731] Input: Feedback data

[0732] Specific operation: The server formats the feedback data into JSON format and sends it to the terminal as an HTTP response.

[0733] Output: Feedback data sent to the device

[0734] Step 11:

[0735] The device displays the feedback to the user.

[0736] Input: Feedback data

[0737] Specific operation: The device analyzes the data and displays a feedback message on the user interface.

[0738] Output: The feedback message displayed to the user

[0739] Consulting (1) How to get started with investing

[0740] Step 1:

[0741] The user enters questions regarding opening a securities account.

[0742] Input: User text input

[0743] Specific operation: The user types "What documents are required to open a securities account?" into the input form and presses the submit button.

[0744] Output: User question data

[0745] Step 2:

[0746] The terminal sends a question to the server.

[0747] Input: Question data

[0748] Specific operation: The terminal sends the question data as an HTTP request.

[0749] Output: The query data sent to the server

[0750] Step 3:

[0751] The server receives the question and gathers the necessary information from a database to generate an answer.

[0752] Input: Question data

[0753] What it does: The server runs an SQL query to retrieve the information needed to open a brokerage account from a database. The server then cross-parses this information and generates a clear answer.

[0754] Output: Generated response data

[0755] Step 4:

[0756] The server generates a response and sends it to the terminal.

[0757] Input: Answer data

[0758] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[0759] Output: Response data sent to the device

[0760] Step 5:

[0761] The terminal displays the answer to the user.

[0762] Input: Answer data

[0763] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[0764] Output: The answer displayed to the user

[0765] Step 6:

[0766] The user enters a follow-up question.

[0767] Input: User's additional question

[0768] Specific behavior: The user enters further questions into the input form and presses the submit button.

[0769] Output: Additional question data

[0770] Step 7:

[0771] The terminal sends a follow-up question to the server.

[0772] Input: Additional question data

[0773] Specific operation: The device sends additional question data as an HTTP request.

[0774] Output: Additional question data sent to the server

[0775] Step 8:

[0776] The server gathers new information and generates an answer.

[0777] Input: Additional question data

[0778] What happens: The server runs the SQL query, retrieves additional information from the database, parses it, and generates an answer.

[0779] Output: The newly generated answer

[0780] Step 9:

[0781] The server generates a response and sends it to the terminal.

[0782] Input: Newly generated answer

[0783] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[0784] Output: Answer sent to terminal

[0785] Step 10:

[0786] The terminal displays the answer to the user.

[0787] Input: Answer data

[0788] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[0789] Output: The new answer displayed to the user

[0790] Discussion Consulting (2) Market and Company Analysis

[0791] Step 1:

[0792] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[0793] Input: User text input

[0794] Specific operation: The user enters the company name and question in the input form and presses the submit button.

[0795] Output: User's analysis request data

[0796] Step 2:

[0797] The terminal sends a request to the server.

[0798] Input: Analysis request data

[0799] Specific operation: The terminal sends the analysis request data as an HTTP request.

[0800] Output: Analysis request data sent to the server

[0801] Step 3:

[0802] The server collects public information and summarizes the data to generate business analysis reports.

[0803] Input: Analysis request data

[0804] How it works: The server uses web scraping to collect publicly available financial reports, press releases, and stock price information, then uses NLP techniques to summarize and generate analytical reports.

[0805] Output: Generated company analysis report

[0806] Step 4:

[0807] The server sends the report to the device.

[0808] Input: Company Analysis Report

[0809] Specific operation: The report generated by the server is formatted into PDF or JSON format and sent to the terminal as an HTTP response.

[0810] Output: Company analysis report sent to terminal

[0811] Step 5:

[0812] The terminal displays the report to the user.

[0813] Input: Company Analysis Report

[0814] What happens: The device's browser or app will display the report using a PDF reader or other viewer.

[0815] Output: Company analysis report displayed to the user

[0816] Step 6:

[0817] The user enters a follow-up question.

[0818] Input: User's additional question

[0819] Specific behavior: The user enters further questions into the input form and presses the submit button.

[0820] Output: Additional question data

[0821] Step 7:

[0822] The terminal sends a follow-up question to the server.

[0823] Input: Additional question data

[0824] Specific operation: The device sends additional question data as an HTTP request.

[0825] Output: Additional question data sent to the server

[0826] Step 8:

[0827] The server again collects the data and generates an answer.

[0828] Input: Additional question data

[0829] What it does: The server uses SQL queries and NLP techniques to gather additional information, analyze it, and generate an answer.

[0830] Output: The newly generated answer

[0831] Step 9:

[0832] The server generates a response and sends it to the terminal.

[0833] Input: Newly generated answer

[0834] Specific operation: The server formats the generated response into PDF or JSON format and sends it to the terminal as an HTTP response.

[0835] Output: Answer sent to terminal

[0836] Step 10:

[0837] The terminal displays the answer to the user.

[0838] Input: Answer data

[0839] What happens: Your device's browser or app will display your answers using a PDF reader or other viewer.

[0840] Output: The new answer displayed to the user

[0841] Investment simulation in a virtual environment

[0842] Step 1:

[0843] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[0844] Input: User text input

[0845] Specific operation: The user types "What would happen if I invested 100,000 yen for three years?" into the input form and presses the submit button.

[0846] Output: User simulation request data

[0847] Step 2:

[0848] The device sends a request to the server.

[0849] Input: Simulation request data

[0850] Specific operation: The terminal sends the simulation request data as an HTTP request.

[0851] Output: Request data sent to the server

[0852] Step 3:

[0853] The server sets up a virtual investment environment based on the user's input data.

[0854] Input: Request data

[0855] Specific operation: The server sets up a virtual investment environment based on the input data (e.g., principal, investment period, predicted market environment, etc.).

[0856] Output: A virtual investment environment

[0857] Step 4:

[0858] The server runs the simulation in a virtual environment.

[0859] Input: A hypothetical investment environment

[0860] What it does: The server uses Monte Carlo simulations and other computational models to predict investment outcomes.

[0861] Output: Simulation results

[0862] Step 5:

[0863] The server generates the simulation results.

[0864] Input: Simulation results

[0865] Specific operation: The server analyzes the simulation result data and formats it as graphs and numerical data.

[0866] Output: Generated simulation result data

[0867] Step 6:

[0868] The server sends the results to the terminal.

[0869] Input: Generated simulation result data

[0870] Specific operation: The server formats the result data into JSON or graph format and sends it to the terminal as an HTTP response.

[0871] Output: Simulation results sent to the terminal

[0872] Step 7:

[0873] The terminal displays the simulation results to the user.

[0874] Input: Simulation results

[0875] Specific operation: The device's browser or app analyzes the results data and displays it as graphs or numerical data.

[0876] Output: Simulation results displayed to the user

[0877] Incorporating an emotion engine

[0878] Step 1:

[0879] The user enters a question or command.

[0880] Input: User text input

[0881] Specific operation: The user enters a question or command into the input form and presses the submit button.

[0882] Output: User input data

[0883] Step 2:

[0884] The device sends the input to the server and simultaneously requests the emotion engine to analyze the emotion.

[0885] Input: User-entered data

[0886] Specific operation: The device sends the user's input data as an HTTP request and requests emotion analysis from the emotion engine.

[0887] Output: Input data and sentiment analysis request sent to the server

[0888] Step 3:

[0889] The emotion engine analyzes the user's input data.

[0890] Input: User-entered data

[0891] How it works: The emotion engine performs text analysis, speech analysis, and facial expression analysis to determine the emotional state.

[0892] Output: Emotion analysis results

[0893] Step 4:

[0894] The emotion engine determines the emotional state and sends the result to the server.

[0895] Input: Sentiment analysis results

[0896] Specific operation: The emotion engine formats the analysis results into JSON format and sends them to the server.

[0897] Output: Sentiment analysis results sent to the server

[0898] Step 5:

[0899] The server receives the sentiment analysis results and adjusts the information and feedback it provides.

[0900] Input: Sentiment analysis results

[0901] Specific operation: The server generates appropriate feedback and information based on the analysis results and adjusts it according to the user's emotional state.

[0902] Output: Tailored feedback and information

[0903] Step 6:

[0904] The server sends the adjusted information and feedback to the device.

[0905] Input: Moderated feedback and information

[0906] Specific operation: The server formats the adjusted information into JSON format and sends it to the terminal as an HTTP response.

[0907] Output: Feedback and information sent to the device

[0908] Step 7:

[0909] The device displays information and feedback to the user.

[0910] Input: Feedback and Information

[0911] Specific behavior: The device analyzes the feedback and information and displays it in the user interface.

[0912] Output: Feedback or information displayed to the user

[0913] (Application example 2)

[0914] 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."

[0915] Many systems have been proposed to help beginners and intermediate investors efficiently learn reliable investment information and support their actual investment behavior. However, systems that provide support that takes into account the user's psychological state are still insufficient. In particular, they lack the functionality to provide real-time feedback on concerns or questions that arise during learning or investment simulations. Furthermore, content delivery that takes into account the user's emotional state has limited personalized support for individual users.

[0916] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic questions about investments from a user, means for generating basic information about investments appropriate to the questions and presenting it to the user, means for generating interactive learning content in the form of quizzes and displaying it to the user, means for receiving the user's answers to the quizzes and analyzing the answers to generate feedback, means for recognizing the user's emotional state, means for adjusting appropriate information and feedback based on the emotional state, and means for presenting the feedback to the user. This enables the user to intuitively acquire investment knowledge and prepare for investment behavior while receiving personalized support according to their emotional state.

[0917] "User" refers to an individual or corporation that uses the investment information learning system.

[0918] "Server" refers to the central control unit that receives requests from users and generates and presents appropriate information.

[0919] A "terminal" is a device that is directly operated by a user, and includes a smartphone, a computer, and the like.

[0920] "Basic information about investments" refers to information about the definition and basic concepts of investments, as well as types of stocks, bonds, etc.

[0921] "Quiz-style interactive learning content" refers to learning materials provided in the form of quizzes or questions and answers to assess a user's level of understanding.

[0922] "Feedback" refers to evaluations and instructional comments generated based on the user's quiz answers.

[0923] "Emotional state" refers to the psychological state exhibited by the user, and specifically includes stress, anxiety, positive emotions, and the like.

[0924] An "emotion engine" refers to a system that includes programs and algorithms for analyzing user input data and determining an emotional state.

[0925] "Personalized support" refers to individualized assistance tailored to the user's individual needs and emotional state.

[0926] "Investment learning content" refers to materials, videos, texts, etc. for learning investment knowledge and skills.

[0927] "Content distribution service" refers to an online service that provides users with necessary investment information and learning materials.

[0928] This invention is a system that enables beginners and intermediate investors to efficiently learn investment information and support their actual investment activities. In particular, by combining it with an emotion engine that recognizes the user's emotional state, it provides personalized support according to the user's psychological state.

[0929] Hardware and software used

[0930] Hardware

[0931] Device: smartphone or computer

[0932] Camera: Webcam, smartphone built-in camera

[0933] Server: Cloud or Dedicated Server

[0934] software

[0935] Emotion Engine: Emotion recognition program using OpenCV and Keras

[0936] Data analysis: Python, machine learning models (e.g., RandomForestClassifier)

[0937] Communication: REST API, Python requests library

[0938] Program processing

[0939] The server receives basic investment questions from users and generates appropriate basic information about investments. For example, it generates content such as the basics of stock investments and an overview of bonds. It provides interactive learning content in the form of quizzes, and when users answer, it analyzes their answers and generates feedback.

[0940] Furthermore, the system uses an emotion engine to recognize the user's emotional state and tailor appropriate information and feedback based on that state. For example, if the user is feeling anxious, the system will provide additional information or encouraging messages to alleviate their anxiety.

[0941] Specific examples

[0942] Example 1

[0943] A beginner investor is using the app to learn basic information about stock investment. If an anxious expression is detected during the learning process, the system displays an additional video about "How to reduce the risks of stock investment" and sends an encouraging message. It also displays prompts such as "Have you gained a deeper understanding?"

[0944] Example 2

[0945] The user asks how to open a brokerage account and the system provides the necessary information. If the system detects anxiety in the user's voice, it provides an additional step-by-step guide to the process. The prompt is "Are you ready to proceed?"

[0946] Prompt Sentence Examples

[0947] "What follow-up content would you provide if you detected anxiety in a user's facial expression while playing an investment learning video?"

[0948] "What quizzes or interactive elements will you add to check if users are understanding the video as they watch?"

[0949] "If you ask about opening a brokerage account and detect concerns, what guidance would you offer for moving forward?"

[0950] This system allows users to intuitively acquire investment knowledge and prepare for investment activities while receiving support tailored to their emotional state.

[0951] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0952] Step 1:

[0953] A user uses a smartphone or computer to launch an investment learning application and input basic investment questions. This input is sent to a terminal, which then sends the data to a server. The input data includes the user's question. The output is the question data sent to the server.

[0954] Step 2:

[0955] The server analyzes the query data received from the user and retrieves basic information about appropriate investments (e.g., the definition of stock investment and risk management methods) from the database. During this process, the server searches for relevant information in the database based on the query and selects the most appropriate information. The output is data containing appropriate investment information.

[0956] Step 3:

[0957] The server generates quiz-style interactive learning content based on the acquired basic information. This content is in the form of questions to verify the user's knowledge level. The generated content is sent from the server to the terminal. The input is the basic information, and the output is the generated quiz content.

[0958] Step 4:

[0959] The terminal displays the transmitted quiz content to the user. The user answers the displayed quiz and inputs the answer data into the terminal. The input is the user's quiz answer, and the output is the answer data input into the terminal.

[0960] Step 5:

[0961] The device sends the user's answer data to the server. The server analyzes the received answer data, determines whether the answer is correct or incorrect, and generates feedback. Data analysis includes the process of comparing it with the correct answer data to determine whether the user's choice is correct. The input is the user's answer data, and the output is feedback data.

[0962] Step 6:

[0963] The server sends the generated feedback data to the terminal, and the terminal displays the feedback to the user. The input is the generated feedback, and the output is the feedback displayed to the user.

[0964] Step 7:

[0965] When a user inputs a question or command, the device sends it to the server and simultaneously requests emotion recognition from the emotion engine. The input is the user's question or command, and the output is emotion recognition request data sent to the emotion engine.

[0966] Step 8:

[0967] The emotion engine analyzes the user's input data (text, facial expressions, tone of voice, etc.) and determines the user's emotional state. An emotion recognition model (e.g., a model using Keras) is used for data analysis. The input is the data sent to the emotion engine, and the output is the determined emotional state.

[0968] Step 9:

[0969] The server receives the emotion analysis results from the emotion engine and adjusts the information and feedback it provides based on those results. If anxiety is detected, adjustments are made, such as adding step-by-step guides or encouraging messages. The input is the emotion analysis results, and the output is the adjusted feedback data.

[0970] Step 10:

[0971] The server sends the adjusted information or feedback to the device, which then displays it to the user. The input is the adjusted data, and the output is the adjusted information or feedback displayed to the user.

[0972] 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.

[0973] 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.

[0974] 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.

[0975] [Second embodiment]

[0976] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0977] 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.

[0978] 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).

[0979] 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.

[0980] 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.

[0981] 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).

[0982] 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. 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.

[0983] 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.

[0984] 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.

[0985] 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.

[0986] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0987] 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."

[0988] This invention is a system that allows beginners to intermediate investors to efficiently learn about investment information and support their actual investment activities. This system is mainly comprised of users, servers, and terminals, and operates smoothly through the interaction of these elements.

[0989] A natural language description of the program's operation

[0990] 1. Support for understanding the basics of investing

[0991] User: Launches the application and enters a request: "I want to learn the basics of investing."

[0992] Terminal: Sends the user's request to the server.

[0993] Server: Generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.) and also creates interactive learning content in the form of quizzes.

[0994] Server: Sends the generated information and quiz content to the device.

[0995] Terminal: Displays the submitted information and quiz content to the user.

[0996] User: Answers the quiz and sends the answers to the device.

[0997] Server: Collects user answers, analyzes correct and incorrect answers, generates feedback, and sends it to the device.

[0998] Terminal: Display feedback to the user.

[0999] 2. Discussion Consulting (1) How to Start Investing

[1000] User: Enter a question about opening a brokerage account.

[1001] Terminal: Sends a question to the server.

[1002] Server: Searches for and aggregates the necessary information about opening a brokerage account (e.g., required documents, procedural steps, and a list of reputable brokerage firms) in a concise format.

[1003] Server: Sends the generated information to the terminal.

[1004] Terminal: displays information to the user.

[1005] User: Review the information and enter any additional questions.

[1006] Terminal: Sends a follow-up question to the server.

[1007] Server: Aggregates information from additional questions, generates answers, and sends them to the device.

[1008] Terminal: Display the answer to the user.

[1009] 3. Discussion Consulting (2) Market and Company Analysis

[1010] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[1011] Terminal: Sends the request to the server.

[1012] Server: Collects and summarizes company public information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[1013] Server: Generates a company analysis report based on the summarized information and sends it to the terminal.

[1014] Terminal: Display company analysis reports to the user.

[1015] User: Review the analysis report and enter any additional questions.

[1016] Terminal: Sends a follow-up question to the server.

[1017] Server: Collects information again for any additional questions, generates answers, and sends them to the device.

[1018] Terminal: Display the answer to the user.

[1019] 4. Investment simulation in a virtual environment

[1020] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1021] Terminal: Sends the request to the server.

[1022] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[1023] Server: Runs a double-speed simulation in the configured virtual environment and generates results (e.g., if held for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen).

[1024] Server: Sends the simulation results to the device.

[1025] Terminal: Displays the results to the user.

[1026] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, virtual investment simulations allow users to understand risks before actually starting an investment and deepen their knowledge for safe investments.

[1027] The processing flow will be explained below.

[1028] Support for understanding the basics of investing

[1029] Step 1:

[1030] User: Launches the application and enters a request: "I want to learn the basics of investing."

[1031] Step 2:

[1032] Terminal: Sends the user's request to the server.

[1033] Step 3:

[1034] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[1035] Step 4:

[1036] Server: Sends the generated basic information and quiz content to the device.

[1037] Step 5:

[1038] Terminal: Displays the submitted basic information and quiz content to the user.

[1039] Step 6:

[1040] User: Takes a quiz and enters the answer into the device.

[1041] Step 7:

[1042] Terminal: Sends the user's answer to the server.

[1043] Step 8:

[1044] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[1045] Step 9:

[1046] Server: Sends feedback to the device.

[1047] Step 10:

[1048] Terminal: Display feedback to the user.

[1049] Consulting (1) How to get started with investing

[1050] Step 1:

[1051] User: Enter a question about opening a brokerage account.

[1052] Step 2:

[1053] Terminal: Sends a question to the server.

[1054] Step 3:

[1055] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[1056] Step 4:

[1057] Server: Sends the aggregated information to the device.

[1058] Step 5:

[1059] Terminal: displays information to the user.

[1060] Step 6:

[1061] User: Review the information and re-enter any additional questions.

[1062] Step 7:

[1063] Terminal: Sends a follow-up question to the server.

[1064] Step 8:

[1065] Server: Re-aggregates information and generates answers for additional questions.

[1066] Step 9:

[1067] Server: Sends the generated answer to the device.

[1068] Step 10:

[1069] Terminal: Display the answer to the user.

[1070] Discussion Consulting (2) Market and Company Analysis

[1071] Step 1:

[1072] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[1073] Step 2:

[1074] Terminal: Sends the request to the server.

[1075] Step 3:

[1076] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[1077] Step 4:

[1078] Server: Summarizes the collected data and generates company analysis reports.

[1079] Step 5:

[1080] Server: Sends the generated company analysis report to the terminal.

[1081] Step 6:

[1082] Terminal: Display company analysis reports to the user.

[1083] Step 7:

[1084] User: Review the analysis report and enter any additional questions.

[1085] Step 8:

[1086] Terminal: Sends a follow-up question to the server.

[1087] Step 9:

[1088] Server: Collects information again for additional questions and generates answers.

[1089] Step 10:

[1090] Server: Sends the generated answer to the device.

[1091] Step 11:

[1092] Terminal: Display the answer to the user.

[1093] Investment simulation in a virtual environment

[1094] Step 1:

[1095] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1096] Step 2:

[1097] Terminal: Sends the request to the server.

[1098] Step 3:

[1099] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[1100] Step 4:

[1101] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[1102] Step 5:

[1103] Server: Sends the generated simulation results to the device.

[1104] Step 6:

[1105] Terminal: displays the simulation results to the user.

[1106] Through the above process steps, users can gradually learn the basics of investing and receive support for specific investment actions. Through virtual investment simulations, users can understand the risks before actually starting an investment and deepen their knowledge for safe investment.

[1107] Example 1

[1108] 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."

[1109] Conventional investment learning systems lack sufficient interactivity and feedback functions to enable beginners and intermediate users to efficiently learn investment information and support their actual investment behavior. As a result, users encounter many difficulties in the self-learning process and are at a high risk of making incorrect decisions. The present invention aims to solve these problems and provide a system that enables users to efficiently learn investment information and supports their actual investment behavior.

[1110] 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.

[1111] In this invention, the server includes means for receiving basic investment questions from a user, means for generating appropriate basic investment information in response to the questions and presenting it to the user, means for generating interactive learning content in the form of a quiz using a generative AI model and displaying it to the user, means for receiving answers to the quizzes from the user, analyzing the answers and generating feedback, and means for presenting the feedback to the user. This allows the user to intuitively acquire investment knowledge and prepare for actual investment behavior.

[1112] "User" refers to an individual or organization who uses the system to obtain investment information, learn, or ask questions.

[1113] A "server" is a dedicated computer system that receives requests from users, generates information about appropriate investments, and provides feedback and content.

[1114] A "terminal" is a device (e.g., smartphone, tablet, or PC) that a user uses to communicate with a server, obtain information, and perform operations.

[1115] "Basic information about investments" refers to information that includes the definition of investments, basic investment knowledge and terminology such as stocks and bonds.

[1116] A "generative AI model" is a model generated using artificial intelligence technology, and is a program that generates appropriate responses to user input.

[1117] "Quiz-style interactive learning content" refers to educational content designed to enable users to acquire knowledge about investments by answering quizzes.

[1118] "Feedback" is a response to a user's quiz answers, including whether they were correct or incorrect, as well as additional study information and advice.

[1119] "Basic questions" are questions that users ask the server about basic knowledge and procedures related to investment.

[1120] "Information on opening a securities account" refers to information on the documents and procedural steps required to open a securities account, as well as information on recommended securities companies.

[1121] A "corporate analysis report" is a document containing a summary and analysis results generated from public information, stock price charts, and related press reports of a specific company.

[1122] A "virtual investment environment" is a simulation environment in which users can make virtual investments and predict investment results using actual market data.

[1123] MODE FOR CARRYING OUT THE INVENTION

[1124] The present invention is a system that allows users to efficiently learn about investment information and supports actual investment behavior, and is operated through the interaction of users, a server, and terminals. Specifically, the system is implemented in the following manner.

[1125] Hardware and software used

[1126] Hardware: Server (general cloud-based server system), user device (smartphone, tablet, PC)

[1127] Software: Investment learning applications, generative AI models (e.g., GPT-3), database management systems (e.g., MySQL), data collection APIs (e.g., Google Finance API)

[1128] System operation explanation

[1129] 1. Support for understanding the basics of investing

[1130] The user starts the application and inputs a request to learn the basics of investing. For example, the user directly inputs "I want to learn the basics of investing."

[1131] The device sends the user's request to the server. The request data is sent in JSON format.

[1132] The server retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates quiz-style learning content using a generative AI model (e.g., GPT-3).

[1133] The server transmits the generated information and quiz content to the terminal.

[1134] The terminal visually displays the transmitted information and quiz content to the user.

[1135] The user answers the quiz and transmits the answers to the terminal.

[1136] The server analyzes the user's answers, generates feedback, and sends it to the terminal.

[1137] The terminal displays the feedback to the user.

[1138] Examples:

[1139] Prompt: "I want to learn the basics of investing."

[1140] Example feedback: "Your answer is correct! You understand the basics of investing."

[1141] 2. Discussion Consulting (1) How to Start Investing

[1142] The user inputs a question about opening a securities account, for example, "What documents do I need to open a securities account?"

[1143] The terminal sends a query to the server.

[1144] The server collects information regarding the opening of a securities account, compiles it into a concise form, and transmits it to the terminal.

[1145] The terminal displays the transmitted information to the user.

[1146] The user will review the information and re-enter any additional questions.

[1147] The terminal sends a follow-up question to the server.

[1148] The server aggregates the information for the additional questions, generates an answer, and sends it to the terminal.

[1149] The terminal displays the answer to the user.

[1150] Examples:

[1151] Prompt: "What documents do I need to open a brokerage account?"

[1152] Example feedback: "The documents required are identification (passport or driver's license), proof of current address (resident registration card), etc."

[1153] 3. Discussion Consulting (2) Market and Company Analysis

[1154] A user requests an analysis of a specific company, for example, "Tell me about the recent performance of Company X."

[1155] The terminal sends a request to the server.

[1156] The server collects public company information, stock charts, and related press reports, and generates company analysis reports.

[1157] The server transmits the generated company analysis report to the terminal.

[1158] The terminal displays the company analysis report to the user.

[1159] The user reviews the report and re-enters any additional questions.

[1160] The terminal sends a follow-up question to the server.

[1161] The server collects information for the additional questions, generates answers, and sends them to the terminal.

[1162] The terminal displays the answer to the user.

[1163] Examples:

[1164] Prompt: "Tell me about Company X's recent performance."

[1165] Example feedback: "Company X has seen a 10% increase in sales compared to the same month last year, and a 15% increase in profits."

[1166] 4. Investment simulation in a virtual environment

[1167] The user requests an investment simulation in a virtual environment, for example, by entering "What would happen if I invested 100,000 yen for three years?"

[1168] The terminal sends a request to the server.

[1169] The server sets up a virtual investment environment based on the user's input data (e.g., investment amount, investment period).

[1170] The server runs the simulation in the virtual environment and generates the results.

[1171] The server transmits the simulation results to the terminal.

[1172] The terminal displays the simulation results to the user.

[1173] Examples:

[1174] Prompt: "What would happen if you invested $1,000 for three years?"

[1175] Example feedback: "If you hold the investment for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen."

[1176] This allows users to understand the risks before they actually begin investing and deepen the knowledge they need to make appropriate decisions.

[1177] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1178] 1. Support for understanding the basics of investing

[1179] Step 1:

[1180] A user launches the application and types, "I want to learn the basics of investing."

[1181] Input: User request ("I want to learn the basics of investing")

[1182] What it does: Enter a request into a text input field within the app.

[1183] Output: Request data (text format)

[1184] Step 2:

[1185] The device sends a request to the server.

[1186] Input: User request data

[1187] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[1188] Output: Request data sent to the server

[1189] Step 3:

[1190] The server generates basic information about investments and creates learning content in the form of quizzes.

[1191] Input: Request data

[1192] How it works: It retrieves basic investment information from a database and uses a generative AI model (e.g., GPT-3) to generate interactive learning content in the form of quizzes.

[1193] Output: Basic information and quiz content (JSON format)

[1194] Step 4:

[1195] The server transmits the generated information and quiz content to the terminal.

[1196] Input: Basic information and quiz content

[1197] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[1198] Output: Data sent to the terminal

[1199] Step 5:

[1200] The terminal displays the transmitted information and quiz content to the user.

[1201] Input: Data from the server

[1202] Behavior: Parses the received JSON data and visually displays basic information and quiz content on the screen.

[1203] Output: The information displayed to the user and the quiz

[1204] Step 6:

[1205] The user answers the quiz and transmits the answers to the terminal.

[1206] Input: User's quiz answer

[1207] Action: Enter the quiz answer in the input field and press the submit button.

[1208] Output: Quiz answers sent to the device

[1209] Step 7:

[1210] The server collects the user's answers, analyzes whether they are correct or incorrect, and generates feedback.

[1211] Input: Quiz response data

[1212] How it works: Your answers are matched against existing ground truth data and feedback is generated using a generative AI model.

[1213] Output: Feedback data (JSON format)

[1214] Step 8:

[1215] The server sends the feedback to the device.

[1216] Input: Feedback data

[1217] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[1218] Output: Feedback data sent to the device

[1219] Step 9:

[1220] The device displays the feedback to the user.

[1221] Input: Feedback data

[1222] Behavior: Parses the received JSON data and displays feedback on the screen.

[1223] Output: Feedback displayed to the user

[1224] 2. Discussion Consulting (1) How to Start Investing

[1225] Step 1:

[1226] The user enters a question about opening a securities account.

[1227] Input: User question ("What documents do I need to open a brokerage account?")

[1228] What it does: Type a question into a text input field within the app.

[1229] Output: Question data (text format)

[1230] Step 2:

[1231] The terminal sends a question to the server.

[1232] Input: User question data

[1233] What it does: It converts question data into JSON format and sends it to the server via HTTP protocol.

[1234] Output: Question data sent to the server

[1235] Step 3:

[1236] The server collects and summarizes information about opening a securities account.

[1237] Input: User question data

[1238] What it does: Retrieves the necessary information from databases and external APIs, then aggregates and summarizes the information concisely.

[1239] Output: Aggregated information data (JSON format)

[1240] Step 4:

[1241] The server transmits the generated information to the terminal.

[1242] Input: Aggregated information data

[1243] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[1244] Output: Information data sent to the terminal

[1245] Step 5:

[1246] The terminal displays the information to the user.

[1247] Input: Information data from the server

[1248] What it does: Parses the received JSON data and displays the information visually on the screen.

[1249] Output: Information displayed to the user

[1250] Step 6:

[1251] The user enters a follow-up question.

[1252] Input: User's additional question

[1253] Action: Enter a follow-up question into the text entry field.

[1254] Output: Additional question data (text format)

[1255] Step 7:

[1256] The terminal sends a follow-up question to the server.

[1257] Input: User's additional question data

[1258] Behavior: The question data is converted to JSON format and sent to the server.

[1259] Output: Additional question data sent to the server

[1260] Step 8:

[1261] The server aggregates the information for the follow-up questions and generates an answer.

[1262] Input: Additional question data

[1263] What it does: Recollects information from databases and external APIs and generates answers.

[1264] Output: Generated response data (JSON format)

[1265] Step 9:

[1266] The server sends the response to the terminal.

[1267] Input: Generated response data

[1268] What it does: Composes data in JSON format and sends it to the device.

[1269] Output: Answer data sent to the device

[1270] Step 10:

[1271] The terminal displays the answer to the user.

[1272] Input: Response data from the server

[1273] Behavior: Parses the received JSON data and displays the answer on the screen.

[1274] Output: The answer displayed to the user

[1275] 3. Discussion Consulting (2) Market and Company Analysis

[1276] Step 1:

[1277] A user requests an analysis of a specific company.

[1278] Input: User's company analysis request ("Tell me about company X's recent performance")

[1279] What it does: Enter a request into a text input field within the app.

[1280] Output: Request data (text format)

[1281] Step 2:

[1282] The device sends a request to the server.

[1283] Input: User request data

[1284] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[1285] Output: Request data sent to the server

[1286] Step 3:

[1287] The server collects and summarizes company public information, stock charts, and related press coverage.

[1288] Input: User request data

[1289] What it does: Uses databases and external APIs to collect and summarize company public information, stock charts, and related press.

[1290] Output: Summarized company information data (JSON format)

[1291] Step 4:

[1292] The server generates a company analysis report and sends it to the terminal.

[1293] Input: Summarized company information data

[1294] What it does: Generates a company analysis report based on the summary data and sends it to the device in JSON format.

[1295] Output: Generated company analysis report data (JSON format)

[1296] Step 5:

[1297] The terminal displays the company analysis report to the user.

[1298] Input: Report data from the server

[1299] What it does: Parses the received JSON data and displays a report on the screen.

[1300] Output: Company analysis report displayed to the user

[1301] Step 6:

[1302] The user enters a follow-up question.

[1303] Input: User's additional question

[1304] Action: Enter a follow-up question into the text entry field.

[1305] Output: Additional question data (text format)

[1306] Step 7:

[1307] The terminal sends a follow-up question to the server.

[1308] Input: User's additional question data

[1309] Behavior: The question data is converted to JSON format and sent to the server.

[1310] Output: Additional question data sent to the server

[1311] Step 8:

[1312] The server recollects information for additional questions and generates answers.

[1313] Input: Additional question data

[1314] How it works: Generates an answer based on the recollected information and sends it to the device in JSON format.

[1315] Output: Generated response data (JSON format)

[1316] Step 9:

[1317] The server sends the response to the terminal.

[1318] Input: Generated response data

[1319] What it does: Composes data in JSON format and sends it to the device.

[1320] Output: Answer data sent to the device

[1321] Step 10:

[1322] The terminal displays the answer to the user.

[1323] Input: Response data from the server

[1324] Behavior: Parses the received JSON data and displays the answer on the screen.

[1325] Output: The answer displayed to the user

[1326] 4. Investment simulation in a virtual environment

[1327] Step 1:

[1328] A user requests an investment simulation.

[1329] Input: User simulation request ("What happens if I invest $1,000 for three years?")

[1330] What it does: Enter a request into a text input field within the app.

[1331] Output: Request data (text format)

[1332] Step 2:

[1333] The device sends a request to the server.

[1334] Input: User request data

[1335] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[1336] Output: Request data sent to the server

[1337] Step 3:

[1338] The server sets up a virtual investment environment based on the user's input data.

[1339] Input: Request data (investment amount, investment period, etc.)

[1340] How it works: Runs an algorithm to create a virtual investment environment based on input data.

[1341] Output: Set virtual investment environment data

[1342] Step 4:

[1343] The server runs the double-speed simulation in a configured virtual environment and generates the results.

[1344] Input: Hypothetical investment environment data

[1345] How it works: Runs simulations twice as fast in a virtual environment to calculate investment results.

[1346] Output: Simulation result data (e.g., 115,700 yen over 3 years at an annual interest rate of 5%)

[1347] Step 5:

[1348] The server transmits the simulation results to the terminal.

[1349] Input: Simulation result data

[1350] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[1351] Output: Simulation result data sent to the terminal

[1352] Step 6:

[1353] The terminal displays the simulation results to the user.

[1354] Input: Simulation result data

[1355] Operation: Parses the received JSON data and visually displays the simulation results on the screen.

[1356] Output: Simulation results displayed to the user

[1357] This allows users to intuitively acquire investment knowledge and prepare for actual investment actions. Virtual investment simulations also allow users to understand risks and deepen their knowledge for safe investments.

[1358] (Application example 1)

[1359] 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."

[1360] Existing systems that enable users from beginners to intermediate investors to efficiently learn investment information and support actual investment activities tend to be one-way, lacking interactivity. It was also difficult to provide a wide range of information and support necessary for investing, such as opening a securities account, company analysis, and virtual investment simulations, all in one system. Therefore, a system was needed that would allow users to intuitively learn about investment from the basics to advanced applications, while also allowing them to move smoothly and safely into actual investment activities.

[1361] 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.

[1362] In this invention, the server includes: means for receiving basic investment questions from a user; means for generating appropriate basic investment information in response to the questions and presenting it to the user; means for generating quiz-style interactive learning content and displaying it to the user; means for receiving user answers to the quizzes and analyzing the answers to generate feedback; means for presenting the feedback to the user; means for receiving user questions regarding company analysis; means for collecting and summarizing public company information, stock price charts, and related news reports in response to the questions; means for generating a company analysis report based on the summarized information; means for presenting the company analysis report to the user; means for re-collecting information in response to additional user questions and generating answers; means for presenting the answers to the user; means for receiving user requests for virtual investment simulations; means for designing a virtual investment environment based on the request; means for executing a virtual simulation and generating results; and means for presenting the simulation results to the user. This provides comprehensive support for users as they transition to actual investment behavior while consistently learning about investment from the basics to applications and practice, enabling beginners to intermediate investors to invest safely and efficiently.

[1363] "User" refers to a person who uses the electronic payment application to learn investment-related information and take actual investment actions.

[1364] "Server" refers to a computer system that generates investment information in response to a request from a user and provides it to the user.

[1365] "Basic information" refers to basic knowledge and definitions of investment, as well as information on basic investment vehicles such as stocks and bonds.

[1366] "Quiz" refers to an interactive set of questions that allows users to test their investing knowledge.

[1367] "Interactive learning content" refers to learning materials and activities that progress through two-way interaction between the user and the system.

[1368] "Feedback" refers to evaluations and advice information generated by the system through analysis of users' quiz answers and requests.

[1369] "Company analysis" refers to the process of evaluating the performance and market position of a particular company using public information, stock charts, and related press coverage.

[1370] "Public information" refers to information such as financial reports and press releases that companies make public.

[1371] "Virtual investment simulation" refers to a system that predicts investment results in a virtual investment environment based on the investment amount and period specified by the user.

[1372] "Virtual investment environment" refers to virtual market conditions and investment conditions for simulations set based on user input data.

[1373] "Results" refers to the predicted investment return and risk output based on a hypothetical investment simulation.

[1374] This invention is a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities. The system is mainly operated through the interaction between the server, terminals, and users. The implementation method for each main function is shown below.

[1375] First, the system has a means for receiving basic questions about investment from users. When a user inputs a question about the basics of investing from a terminal, the request is sent to the server. The server generates basic information about investment and presents it to the user. This basic information is provided as interactive learning content in the form of quizzes to make it easy for beginners to understand, such as the definitions of stocks and bonds. For example, in response to the question, "What is investment?", the system provides feedback in the form of a quiz, such as, "Investment is a means of increasing funds."

[1376] The server then receives questions from users about how to open a securities account and aggregates the appropriate information to present to the user. When a user requests "How do I open a securities account?" via a terminal, the server provides the necessary documents, procedural steps, a list of highly rated securities companies, and so on.

[1377] Furthermore, the system has a function to receive questions about company analysis from users. When a user types "Tell me about Company X's latest performance," the server collects and summarizes the company's public information, stock price charts, and related news reports. It then generates a company analysis report based on the summarized information and presents it to the user.

[1378] It also has a virtual investment simulation function. When a user inputs a request into the terminal, such as "What will be the results if I invest 100,000 yen for three years?", the request is sent to the server. The server designs a virtual investment environment based on the data entered by the user, runs a simulation, and generates the results. The simulation results are presented to the user via the terminal. For example, if you hold the investment for three years under the condition of an annual interest rate of 5%, the total amount will be approximately 115,700 yen.

[1379] This system is implemented using programming languages ​​such as Python, and frameworks and libraries (e.g., Flask and Django) for managing HTTP requests. The server runs on a RESTful API, and the database stores the latest investment information, company disclosures, and user learning history. It also uses machine learning models to analyze users' quiz answers and simulation results and generate personalized feedback and advice.

[1380] To illustrate this, here are some example prompts generated using a generative AI model:

[1381] Prompt Sentence Examples

[1382] "A user types in 'What is the recent performance of Company X?' The server processes it in the following steps:

[1383] 1. Search for public information about Company X.

[1384] 2. Collect financial reports, press releases, and related media coverage.

[1385] 3. Summarize the collected information and generate a company analysis report.

[1386] 4. Provide the generated report to the user.

[1387] In this way, the user is supported in making safe and efficient investment decisions while consistently learning everything from the basics to the practical aspects of investing.

[1388] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1389] Step 1:

[1390] The user enters basic investment questions.

[1391] In this step, the user launches the smartphone app and inputs a request such as "I want to learn the basics of investing." The input request is sent to the server via the device. The input data is natural language text data containing the user's question.

[1392] Step 2:

[1393] The server generates basic information about the investment and presents it to the user.

[1394] The server analyzes the received question data and generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.). The generated data is organized into interactive learning content in the form of a quiz. The generated information and quiz content are then sent back to the device. In this step, the server uses a generative AI model to generate this data.

[1395] Step 3:

[1396] The terminal displays the transmitted information and quiz content to the user.

[1397] The terminal receives the information from the server and displays it to the user, who then inputs answers to the displayed quiz questions.

[1398] Step 4:

[1399] The server receives the user's quiz answers, analyzes them and generates feedback.

[1400] The user's answer data is sent from the device to the server. The server analyzes this data and determines whether the user's answer is correct or incorrect. Feedback is generated based on the analysis results and sent to the device. Here too, a generative AI model is used to generate the feedback.

[1401] Step 5:

[1402] The terminal displays the feedback to the user.

[1403] The device displays the feedback received from the server to the user, including whether the answer was correct or incorrect and any additional advice.

[1404] Step 6:

[1405] A user requests an analysis of a specific company.

[1406] The user inputs a request such as "Tell me about the recent performance of Company X." The input data is sent to the server via the terminal.

[1407] Step 7:

[1408] The server collects and summarizes company public information, stock charts, and related press coverage.

[1409] Based on the received request, the server searches and collects public information, stock price charts, and related press reports related to Company X. The collected data is then summarized and organized into a company analysis report. This summarization process utilizes a generative AI model.

[1410] Step 8:

[1411] The terminal presents the company analysis report to the user.

[1412] The terminal displays the company analysis report received from the server to the user, who then checks the contents.

[1413] Step 9:

[1414] A user requests a virtual investment simulation.

[1415] The user inputs a request such as "What will be the result if I invest 100,000 yen for three years?" The input data is sent to the server via the terminal.

[1416] Step 10:

[1417] The server designs the virtual investment environment and runs the simulation.

[1418] The server designs a virtual investment environment based on user input data (investment amount, investment period, etc.), then runs a virtual simulation to generate investment results. The simulation is performed using a generative AI model and simulation algorithm.

[1419] Step 11:

[1420] The terminal presents the simulation results to the user.

[1421] The terminal receives simulation results from the server and displays them to the user, including estimated investment returns and risk information.

[1422] 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.

[1423] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[1424] A natural language description of the program's operation

[1425] 1. Support for understanding the basics of investing

[1426] User: Launches the application and enters a request: "I want to learn the basics of investing."

[1427] Terminal: Sends the user's request to the server.

[1428] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[1429] Server: Sends the generated basic information and quiz content to the device.

[1430] Terminal: Displays the submitted basic information and quiz content to the user.

[1431] User: Takes a quiz and enters the answer into the device.

[1432] Terminal: Sends the user's answer to the server.

[1433] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[1434] Server: Sends feedback to the device.

[1435] Terminal: Display feedback to the user.

[1436] 2. Discussion Consulting (1) How to Start Investing

[1437] User: Enter a question about opening a brokerage account.

[1438] Terminal: Sends a question to the server.

[1439] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[1440] Server: Sends the aggregated information to the device.

[1441] Terminal: displays information to the user.

[1442] User: Review the information and re-enter any additional questions.

[1443] Terminal: Sends a follow-up question to the server.

[1444] Server: Re-aggregates information and generates answers for additional questions.

[1445] Server: Sends the generated answer to the device.

[1446] Terminal: Display the answer to the user.

[1447] 3. Discussion Consulting (2) Market and Company Analysis

[1448] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[1449] Terminal: Sends the request to the server.

[1450] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[1451] Server: Summarizes the collected data and generates company analysis reports.

[1452] Server: Sends the generated company analysis report to the terminal.

[1453] Terminal: Display company analysis reports to the user.

[1454] User: Review the analysis report and enter any additional questions.

[1455] Terminal: Sends a follow-up question to the server.

[1456] Server: Collects information again for additional questions and generates answers.

[1457] Server: Sends the generated answer to the device.

[1458] Terminal: Display the answer to the user.

[1459] 4. Investment simulation in a virtual environment

[1460] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1461] Terminal: Sends the request to the server.

[1462] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[1463] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[1464] Server: Sends the generated simulation results to the device.

[1465] Terminal: displays the simulation results to the user.

[1466] 5. Incorporating an Emotional Engine

[1467] User: Enters questions and commands into the terminal.

[1468] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[1469] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[1470] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[1471] Server: Sends tailored information and feedback to the device.

[1472] Device: Display tailored information and feedback to the user.

[1473] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[1474] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[1475] The processing flow will be explained below.

[1476] Support for understanding the basics of investing

[1477] Step 1:

[1478] User: Launches the application and enters a request: "I want to learn the basics of investing."

[1479] Step 2:

[1480] Terminal: Sends the user's request to the server.

[1481] Step 3:

[1482] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[1483] Step 4:

[1484] Server: Sends the generated basic information and quiz content to the device.

[1485] Step 5:

[1486] Terminal: Displays the submitted basic information and quiz content to the user.

[1487] Step 6:

[1488] User: Takes a quiz and enters the answer into the device.

[1489] Step 7:

[1490] Terminal: Sends the user's answer to the server.

[1491] Step 8:

[1492] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[1493] Step 9:

[1494] Server: Sends feedback to the device.

[1495] Step 10:

[1496] Terminal: Display feedback to the user.

[1497] Consulting (1) How to get started with investing

[1498] Step 1:

[1499] User: Enter a question about opening a brokerage account.

[1500] Step 2:

[1501] Terminal: Sends a question to the server.

[1502] Step 3:

[1503] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[1504] Step 4:

[1505] Server: Sends the aggregated information to the device.

[1506] Step 5:

[1507] Terminal: displays information to the user.

[1508] Step 6:

[1509] User: Review the information and re-enter any additional questions.

[1510] Step 7:

[1511] Terminal: Sends a follow-up question to the server.

[1512] Step 8:

[1513] Server: Re-aggregates information and generates answers for additional questions.

[1514] Step 9:

[1515] Server: Sends the generated answer to the device.

[1516] Step 10:

[1517] Terminal: Display the answer to the user.

[1518] Discussion Consulting (2) Market and Company Analysis

[1519] Step 1:

[1520] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[1521] Step 2:

[1522] Terminal: Sends the request to the server.

[1523] Step 3:

[1524] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[1525] Step 4:

[1526] Server: Summarizes the collected data and generates company analysis reports.

[1527] Step 5:

[1528] Server: Sends the generated company analysis report to the terminal.

[1529] Step 6:

[1530] Terminal: Display company analysis reports to the user.

[1531] Step 7:

[1532] User: Review the analysis report and enter any additional questions.

[1533] Step 8:

[1534] Terminal: Sends a follow-up question to the server.

[1535] Step 9:

[1536] Server: Collects information again for additional questions and generates answers.

[1537] Step 10:

[1538] Server: Sends the generated answer to the device.

[1539] Step 11:

[1540] Terminal: Display the answer to the user.

[1541] Investment simulation in a virtual environment

[1542] Step 1:

[1543] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1544] Step 2:

[1545] Terminal: Sends the request to the server.

[1546] Step 3:

[1547] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[1548] Step 4:

[1549] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[1550] Step 5:

[1551] Server: Sends the generated simulation results to the device.

[1552] Step 6:

[1553] Terminal: displays the simulation results to the user.

[1554] Incorporating an emotion engine

[1555] Step 1:

[1556] User: Enters questions and commands into the terminal.

[1557] Step 2:

[1558] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[1559] Step 3:

[1560] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[1561] Step 4:

[1562] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[1563] Step 5:

[1564] Server: Sends tailored information and feedback to the device.

[1565] Step 6:

[1566] Device: Display tailored information and feedback to the user.

[1567] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[1568] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[1569] Example 2

[1570] 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."

[1571] In systems that enable beginners to intermediate investors to efficiently learn about investment information and support their actual investment behavior, there is a lack of appropriate feedback that takes into account the user's emotional state, making it difficult to effectively learn while reducing stress and anxiety.In addition, there is a problem in that the information is not properly customized, making it difficult to provide personalized investment advice.

[1572] 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 a means for analyzing input data from a user and determining the emotional state, a means for adjusting information and feedback according to the emotional state and presenting it to the user, and a means for generating interactive learning content in the form of a quiz and displaying it to the user. This enables personalized learning support and investment advice that takes the user's emotional state into consideration.

[1573] A "user" is an individual or corporation that uses the system to learn investment information and receives support for actual investment actions.

[1574] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet, that communicates with a server and provides a user interface.

[1575] A "server" is a computer system that receives requests from users, performs the necessary processing, and returns information to the terminal.

[1576] "Quiz-style interactive learning content" refers to educational content in the form of questions and answers, intended to help users acquire knowledge about investments through their participation.

[1577] "Feedback" refers to the reaction or response provided by the system in response to the user's actions or input, and is supplementary information that deepens the user's understanding.

[1578] "Emotional state" refers to the psychological state that a user feels while using the system, and includes stress, anxiety, positive emotions, etc.

[1579] An "emotion engine" is a system that uses artificial intelligence to analyze user input data (text, facial expressions, tone of voice, etc.) and determine the user's emotional state.

[1580] "Basic information about investments" refers to information that includes the definition of investments and basic knowledge about stocks, bonds, etc.

[1581] "Information regarding opening a securities account" refers to information such as the documents required to open a securities account, procedural steps, and a list of recommended securities companies.

[1582] A "corporate analysis report" is an analytical document about a company's financial status and performance, generated based on the company's public information, stock price charts, and related news reports.

[1583] A "virtual investment environment" is an environment for simulating investments using virtual funds without using actual funds.

[1584] "Double-speed simulation" is a method of predicting future results by conducting an investment simulation at a speed faster than the normal rate of time.

[1585] "Natural language processing technology" is a technology for analyzing natural language such as text and speech, understanding its meaning, and processing it.

[1586] "Personalized" means providing information and services that are optimized for each individual user.

[1587] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[1588] In this invention, the terminal receives input from the user and sends it to the server. The server performs the necessary processing based on the received request and returns a response to the terminal. Specifically, the following hardware and software are used:

[1589] Hardware used

[1590] Device: Electronic devices such as computers, smartphones, and tablets.

[1591] Server: A high-performance computing system (e.g., cloud server, on-premise server).

[1592] Software used

[1593] Database: MySQL, PostgreSQL.

[1594] NLP (Natural Language Processing) technologies: Generative AI models such as GPT-3 and BERT.

[1595] Quiz generation algorithm: Python script.

[1596] Emotion engine: Text analysis, speech analysis, and facial expression analysis technologies (e.g., Azure Cognitive Services, Amazon Rekognition).

[1597] Specific processing content and operations

[1598] 1. Support for learning the basics of investing

[1599] A user launches the application and types, "I want to learn the basics of investing."

[1600] The terminal sends the user's request to the server, which retrieves basic information about the investment from a database.

[1601] The server generates interactive learning content in the form of a quiz and transmits it to the terminal.

[1602] The terminal displays the quiz content to the user, and the user inputs an answer.

[1603] The server analyzes the user's answers, generates feedback, and sends it to the terminal, which then displays the feedback to the user.

[1604] 2. Discussion Consulting (1) How to Start Investing

[1605] The user enters questions regarding opening a securities account.

[1606] The terminal sends a question to the server, which then gathers the necessary information from a database and generates an answer.

[1607] The terminal displays the information, and if the user enters a follow-up question, it sends it back to the server and receives a new answer.

[1608] 3. Discussion Consulting (2) Market and Company Analysis

[1609] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[1610] The terminal sends a request to the server, which collects public information, summarizes the data, and generates a business analysis report.

[1611] The terminal displays the report, and if the user enters additional questions, it sends them back to the server and receives new answers.

[1612] 4. Investment simulation in a virtual environment

[1613] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1614] The device sends a request to the server, which sets up a virtual environment and runs the simulation.

[1615] The terminal displays the simulation results to the user.

[1616] 5. Incorporating an Emotional Engine

[1617] When the user inputs a question or command, the device sends it to the server, which then requests the emotion engine to analyze the emotion.

[1618] The emotion engine determines the user's emotional state and sends the result to the server.

[1619] The server adjusts the information and feedback based on the emotion analysis results, sends it to the device, and displays it to the user.

[1620] Specific examples

[1621] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server can provide additional step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a positive emotion is detected when a user requests an investment simulation, the server can suggest advanced investment strategies, including risk.

[1622] Examples of prompts are:

[1623] What documents do I need to open a securities account?

[1624] "Tell me about Company X's recent performance."

[1625] "Please simulate what would happen if I invested 100,000 yen for three years."

[1626] This invention allows users to intuitively acquire investment knowledge and prepare for actual investment activities. Emotion analysis by the emotion engine and feedback from that analysis enable users to receive personalized support according to their psychological state.

[1627] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1628] Support for understanding the basics of investing

[1629] Step 1:

[1630] A user launches the application and types, "I want to learn the basics of investing."

[1631] Input: User text input

[1632] Specific actions: A user opens the mobile or web app, types "I want to learn the basics of investing" into the input form, and presses the submit button.

[1633] Output: User request data

[1634] Step 2:

[1635] The terminal sends the user's request to the server.

[1636] Input: User request data

[1637] Specific operation: The terminal sends the user's input data as an HTTP request.

[1638] Output: Request sent to the server

[1639] Step 3:

[1640] The server receives the request and retrieves basic information about the investment from a database.

[1641] Input: Request data

[1642] What it does: The server runs PHP and Python scripts to retrieve basic information for each category from a MySQL database.

[1643] Output: Investment basic information retrieved from the database

[1644] Step 4:

[1645] The server generates interactive learning content in the form of quizzes.

[1646] Input: Basic investment information

[1647] What it does: A Python script runs on the server to analyze the data and generate quiz-style content.

[1648] Output: Generated quiz content

[1649] Step 5:

[1650] The server transmits the generated content to the terminal.

[1651] Input: Generated quiz content

[1652] Specific operation: The quiz content generated by the server is formatted in JSON format and sent to the terminal as an HTTP response.

[1653] Output: Quiz content sent to device

[1654] Step 6:

[1655] The terminal displays the transmitted content to the user.

[1656] Input: Quiz content

[1657] Specific behavior: The device's browser or mobile app parses the JSON data and displays it in the user interface.

[1658] Output: Displayed quiz-style learning content

[1659] Step 7:

[1660] The user answers the quiz and enters the answers into the terminal.

[1661] Input: User's quiz answer

[1662] Specific actions: The user selects an option on the interface, confirms the answer, and presses the submit button.

[1663] Output: Quiz answer data entered on the device

[1664] Step 8:

[1665] The terminal sends the user's answer to the server.

[1666] Input: User response data

[1667] Specific operation: The terminal sends the response data to the server as an HTTP request.

[1668] Output: Response data sent to the server

[1669] Step 9:

[1670] The server analyzes the answers and generates feedback.

[1671] Input: Answer data

[1672] Specific operation: A script on the server analyzes the answer data and generates correct and incorrect answers and supplementary explanations.

[1673] Output: Generated feedback data

[1674] Step 10:

[1675] The server sends the feedback to the device.

[1676] Input: Feedback data

[1677] Specific operation: The server formats the feedback data into JSON format and sends it to the terminal as an HTTP response.

[1678] Output: Feedback data sent to the device

[1679] Step 11:

[1680] The device displays the feedback to the user.

[1681] Input: Feedback data

[1682] Specific operation: The device analyzes the data and displays a feedback message on the user interface.

[1683] Output: The feedback message displayed to the user

[1684] Consulting (1) How to get started with investing

[1685] Step 1:

[1686] The user enters questions regarding opening a securities account.

[1687] Input: User text input

[1688] Specific operation: The user types "What documents are required to open a securities account?" into the input form and presses the submit button.

[1689] Output: User question data

[1690] Step 2:

[1691] The terminal sends a question to the server.

[1692] Input: Question data

[1693] Specific operation: The terminal sends the question data as an HTTP request.

[1694] Output: The query data sent to the server

[1695] Step 3:

[1696] The server receives the question and gathers the necessary information from a database to generate an answer.

[1697] Input: Question data

[1698] What it does: The server runs an SQL query to retrieve the information needed to open a brokerage account from a database. The server then cross-parses this information and generates a clear answer.

[1699] Output: Generated response data

[1700] Step 4:

[1701] The server generates a response and sends it to the terminal.

[1702] Input: Answer data

[1703] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[1704] Output: Response data sent to the device

[1705] Step 5:

[1706] The terminal displays the answer to the user.

[1707] Input: Answer data

[1708] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[1709] Output: The answer displayed to the user

[1710] Step 6:

[1711] The user enters a follow-up question.

[1712] Input: User's additional question

[1713] Specific behavior: The user enters further questions into the input form and presses the submit button.

[1714] Output: Additional question data

[1715] Step 7:

[1716] The terminal sends a follow-up question to the server.

[1717] Input: Additional question data

[1718] Specific operation: The device sends additional question data as an HTTP request.

[1719] Output: Additional question data sent to the server

[1720] Step 8:

[1721] The server gathers new information and generates an answer.

[1722] Input: Additional question data

[1723] What happens: The server runs the SQL query, retrieves additional information from the database, parses it, and generates an answer.

[1724] Output: The newly generated answer

[1725] Step 9:

[1726] The server generates a response and sends it to the terminal.

[1727] Input: Newly generated answer

[1728] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[1729] Output: Answer sent to terminal

[1730] Step 10:

[1731] The terminal displays the answer to the user.

[1732] Input: Answer data

[1733] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[1734] Output: The new answer displayed to the user

[1735] Discussion Consulting (2) Market and Company Analysis

[1736] Step 1:

[1737] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[1738] Input: User text input

[1739] Specific operation: The user enters the company name and question in the input form and presses the submit button.

[1740] Output: User's analysis request data

[1741] Step 2:

[1742] The terminal sends a request to the server.

[1743] Input: Analysis request data

[1744] Specific operation: The terminal sends the analysis request data as an HTTP request.

[1745] Output: Analysis request data sent to the server

[1746] Step 3:

[1747] The server collects public information and summarizes the data to generate business analysis reports.

[1748] Input: Analysis request data

[1749] How it works: The server uses web scraping to collect publicly available financial reports, press releases, and stock price information, then uses NLP techniques to summarize and generate analytical reports.

[1750] Output: Generated company analysis report

[1751] Step 4:

[1752] The server sends the report to the device.

[1753] Input: Company Analysis Report

[1754] Specific operation: The report generated by the server is formatted into PDF or JSON format and sent to the terminal as an HTTP response.

[1755] Output: Company analysis report sent to terminal

[1756] Step 5:

[1757] The terminal displays the report to the user.

[1758] Input: Company Analysis Report

[1759] What happens: The device's browser or app will display the report using a PDF reader or other viewer.

[1760] Output: Company analysis report displayed to the user

[1761] Step 6:

[1762] The user enters a follow-up question.

[1763] Input: User's additional question

[1764] Specific behavior: The user enters further questions into the input form and presses the submit button.

[1765] Output: Additional question data

[1766] Step 7:

[1767] The terminal sends a follow-up question to the server.

[1768] Input: Additional question data

[1769] Specific operation: The device sends additional question data as an HTTP request.

[1770] Output: Additional question data sent to the server

[1771] Step 8:

[1772] The server again collects the data and generates an answer.

[1773] Input: Additional question data

[1774] What it does: The server uses SQL queries and NLP techniques to gather additional information, analyze it, and generate an answer.

[1775] Output: The newly generated answer

[1776] Step 9:

[1777] The server generates a response and sends it to the terminal.

[1778] Input: Newly generated answer

[1779] Specific operation: The server formats the generated response into PDF or JSON format and sends it to the terminal as an HTTP response.

[1780] Output: Answer sent to terminal

[1781] Step 10:

[1782] The terminal displays the answer to the user.

[1783] Input: Answer data

[1784] What happens: Your device's browser or app will display your answers using a PDF reader or other viewer.

[1785] Output: The new answer displayed to the user

[1786] Investment simulation in a virtual environment

[1787] Step 1:

[1788] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1789] Input: User text input

[1790] Specific operation: The user types "What would happen if I invested 100,000 yen for three years?" into the input form and presses the submit button.

[1791] Output: User simulation request data

[1792] Step 2:

[1793] The device sends a request to the server.

[1794] Input: Simulation request data

[1795] Specific operation: The terminal sends the simulation request data as an HTTP request.

[1796] Output: Request data sent to the server

[1797] Step 3:

[1798] The server sets up a virtual investment environment based on the user's input data.

[1799] Input: Request data

[1800] Specific operation: The server sets up a virtual investment environment based on the input data (e.g., principal, investment period, predicted market environment, etc.).

[1801] Output: A virtual investment environment

[1802] Step 4:

[1803] The server runs the simulation in a virtual environment.

[1804] Input: A hypothetical investment environment

[1805] What it does: The server uses Monte Carlo simulations and other computational models to predict investment outcomes.

[1806] Output: Simulation results

[1807] Step 5:

[1808] The server generates the simulation results.

[1809] Input: Simulation results

[1810] Specific operation: The server analyzes the simulation result data and formats it as graphs and numerical data.

[1811] Output: Generated simulation result data

[1812] Step 6:

[1813] The server sends the results to the terminal.

[1814] Input: Generated simulation result data

[1815] Specific operation: The server formats the result data into JSON or graph format and sends it to the terminal as an HTTP response.

[1816] Output: Simulation results sent to the terminal

[1817] Step 7:

[1818] The terminal displays the simulation results to the user.

[1819] Input: Simulation results

[1820] Specific operation: The device's browser or app analyzes the results data and displays it as graphs or numerical data.

[1821] Output: Simulation results displayed to the user

[1822] Incorporating an emotion engine

[1823] Step 1:

[1824] The user enters a question or command.

[1825] Input: User text input

[1826] Specific operation: The user enters a question or command into the input form and presses the submit button.

[1827] Output: User input data

[1828] Step 2:

[1829] The device sends the input to the server and simultaneously requests the emotion engine to analyze the emotion.

[1830] Input: User-entered data

[1831] Specific operation: The device sends the user's input data as an HTTP request and requests emotion analysis from the emotion engine.

[1832] Output: Input data and sentiment analysis request sent to the server

[1833] Step 3:

[1834] The emotion engine analyzes the user's input data.

[1835] Input: User-entered data

[1836] How it works: The emotion engine performs text analysis, speech analysis, and facial expression analysis to determine the emotional state.

[1837] Output: Emotion analysis results

[1838] Step 4:

[1839] The emotion engine determines the emotional state and sends the result to the server.

[1840] Input: Sentiment analysis results

[1841] Specific operation: The emotion engine formats the analysis results into JSON format and sends them to the server.

[1842] Output: Sentiment analysis results sent to the server

[1843] Step 5:

[1844] The server receives the sentiment analysis results and adjusts the information and feedback it provides.

[1845] Input: Sentiment analysis results

[1846] Specific operation: The server generates appropriate feedback and information based on the analysis results and adjusts it according to the user's emotional state.

[1847] Output: Tailored feedback and information

[1848] Step 6:

[1849] The server sends the adjusted information and feedback to the device.

[1850] Input: Moderated feedback and information

[1851] Specific operation: The server formats the adjusted information into JSON format and sends it to the terminal as an HTTP response.

[1852] Output: Feedback and information sent to the device

[1853] Step 7:

[1854] The device displays information and feedback to the user.

[1855] Input: Feedback and Information

[1856] Specific behavior: The device analyzes the feedback and information and displays it in the user interface.

[1857] Output: Feedback or information displayed to the user

[1858] (Application example 2)

[1859] 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."

[1860] Many systems have been proposed to help beginners and intermediate investors efficiently learn reliable investment information and support their actual investment behavior. However, systems that provide support that takes into account the user's psychological state are still insufficient. In particular, they lack the functionality to provide real-time feedback on concerns or questions that arise during learning or investment simulations. Furthermore, content delivery that takes into account the user's emotional state has limited personalized support for individual users.

[1861] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic questions about investments from a user, means for generating basic information about investments appropriate to the questions and presenting it to the user, means for generating interactive learning content in the form of quizzes and displaying it to the user, means for receiving the user's answers to the quizzes and analyzing the answers to generate feedback, means for recognizing the user's emotional state, means for adjusting appropriate information and feedback based on the emotional state, and means for presenting the feedback to the user. This enables the user to intuitively acquire investment knowledge and prepare for investment behavior while receiving personalized support according to their emotional state.

[1862] "User" refers to an individual or corporation that uses the investment information learning system.

[1863] "Server" refers to the central control unit that receives requests from users and generates and presents appropriate information.

[1864] A "terminal" is a device that is directly operated by a user, and includes a smartphone, a computer, and the like.

[1865] "Basic information about investments" refers to information about the definition and basic concepts of investments, as well as types of stocks, bonds, etc.

[1866] "Quiz-style interactive learning content" refers to learning materials provided in the form of quizzes or questions and answers to assess a user's level of understanding.

[1867] "Feedback" refers to evaluations and instructional comments generated based on the user's quiz answers.

[1868] "Emotional state" refers to the psychological state exhibited by the user, and specifically includes stress, anxiety, positive emotions, and the like.

[1869] An "emotion engine" refers to a system that includes programs and algorithms for analyzing user input data and determining an emotional state.

[1870] "Personalized support" refers to individualized assistance tailored to the user's individual needs and emotional state.

[1871] "Investment learning content" refers to materials, videos, texts, etc. for learning investment knowledge and skills.

[1872] "Content distribution service" refers to an online service that provides users with necessary investment information and learning materials.

[1873] This invention is a system that enables beginners and intermediate investors to efficiently learn investment information and support their actual investment activities. In particular, by combining it with an emotion engine that recognizes the user's emotional state, it provides personalized support according to the user's psychological state.

[1874] Hardware and software used

[1875] Hardware

[1876] Device: smartphone or computer

[1877] Camera: Webcam, smartphone built-in camera

[1878] Server: Cloud or Dedicated Server

[1879] software

[1880] Emotion Engine: Emotion recognition program using OpenCV and Keras

[1881] Data analysis: Python, machine learning models (e.g., RandomForestClassifier)

[1882] Communication: REST API, Python requests library

[1883] Program processing

[1884] The server receives basic investment questions from users and generates appropriate basic information about investments. For example, it generates content such as the basics of stock investments and an overview of bonds. It provides interactive learning content in the form of quizzes, and when users answer, it analyzes their answers and generates feedback.

[1885] Furthermore, the system uses an emotion engine to recognize the user's emotional state and tailor appropriate information and feedback based on that state. For example, if the user is feeling anxious, the system will provide additional information or encouraging messages to alleviate their anxiety.

[1886] Specific examples

[1887] Example 1

[1888] A beginner investor is using the app to learn basic information about stock investment. If an anxious expression is detected during the learning process, the system displays an additional video about "How to reduce the risks of stock investment" and sends an encouraging message. It also displays prompts such as "Have you gained a deeper understanding?"

[1889] Example 2

[1890] The user asks how to open a brokerage account and the system provides the necessary information. If the system detects anxiety in the user's voice, it provides an additional step-by-step guide to the process. The prompt is "Are you ready to proceed?"

[1891] Prompt Sentence Examples

[1892] "What follow-up content would you provide if you detected anxiety in a user's facial expression while playing an investment learning video?"

[1893] "What quizzes or interactive elements will you add to check if users are understanding the video as they watch?"

[1894] "If you ask about opening a brokerage account and detect concerns, what guidance would you offer for moving forward?"

[1895] This system allows users to intuitively acquire investment knowledge and prepare for investment activities while receiving support tailored to their emotional state.

[1896] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1897] Step 1:

[1898] A user uses a smartphone or computer to launch an investment learning application and input basic investment questions. This input is sent to a terminal, which then sends the data to a server. The input data includes the user's question. The output is the question data sent to the server.

[1899] Step 2:

[1900] The server analyzes the query data received from the user and retrieves basic information about appropriate investments (e.g., the definition of stock investment and risk management methods) from the database. During this process, the server searches for relevant information in the database based on the query and selects the most appropriate information. The output is data containing appropriate investment information.

[1901] Step 3:

[1902] The server generates quiz-style interactive learning content based on the acquired basic information. This content is in the form of questions to verify the user's knowledge level. The generated content is sent from the server to the terminal. The input is the basic information, and the output is the generated quiz content.

[1903] Step 4:

[1904] The terminal displays the transmitted quiz content to the user. The user answers the displayed quiz and inputs the answer data into the terminal. The input is the user's quiz answer, and the output is the answer data input into the terminal.

[1905] Step 5:

[1906] The device sends the user's answer data to the server. The server analyzes the received answer data, determines whether the answer is correct or incorrect, and generates feedback. Data analysis includes the process of comparing it with the correct answer data to determine whether the user's choice is correct. The input is the user's answer data, and the output is feedback data.

[1907] Step 6:

[1908] The server sends the generated feedback data to the terminal, and the terminal displays the feedback to the user. The input is the generated feedback, and the output is the feedback displayed to the user.

[1909] Step 7:

[1910] When a user inputs a question or command, the device sends it to the server and simultaneously requests emotion recognition from the emotion engine. The input is the user's question or command, and the output is emotion recognition request data sent to the emotion engine.

[1911] Step 8:

[1912] The emotion engine analyzes the user's input data (text, facial expressions, tone of voice, etc.) and determines the user's emotional state. An emotion recognition model (e.g., a model using Keras) is used for data analysis. The input is the data sent to the emotion engine, and the output is the determined emotional state.

[1913] Step 9:

[1914] The server receives the emotion analysis results from the emotion engine and adjusts the information and feedback it provides based on those results. If anxiety is detected, adjustments are made, such as adding step-by-step guides or encouraging messages. The input is the emotion analysis results, and the output is the adjusted feedback data.

[1915] Step 10:

[1916] The server sends the adjusted information or feedback to the device, which then displays it to the user. The input is the adjusted data, and the output is the adjusted information or feedback displayed to the user.

[1917] 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.

[1918] 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.

[1919] 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.

[1920] [Third embodiment]

[1921] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1922] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1923] 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).

[1924] 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.

[1925] 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.

[1926] 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).

[1927] 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.

[1928] 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.

[1929] 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.

[1930] 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.

[1931] 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.

[1932] 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."

[1933] This invention is a system that allows beginners to intermediate investors to efficiently learn about investment information and support their actual investment activities. This system is mainly comprised of users, servers, and terminals, and operates smoothly through the interaction of these elements.

[1934] A natural language description of the program's operation

[1935] 1. Support for understanding the basics of investing

[1936] User: Launches the application and enters a request: "I want to learn the basics of investing."

[1937] Terminal: Sends the user's request to the server.

[1938] Server: Generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.) and also creates interactive learning content in the form of quizzes.

[1939] Server: Sends the generated information and quiz content to the device.

[1940] Terminal: Displays the submitted information and quiz content to the user.

[1941] User: Answers the quiz and sends the answers to the device.

[1942] Server: Collects user answers, analyzes correct and incorrect answers, generates feedback, and sends it to the device.

[1943] Terminal: Display feedback to the user.

[1944] 2. Discussion Consulting (1) How to Start Investing

[1945] User: Enter a question about opening a brokerage account.

[1946] Terminal: Sends a question to the server.

[1947] Server: Searches for and aggregates the necessary information about opening a brokerage account (e.g., required documents, procedural steps, and a list of reputable brokerage firms) in a concise format.

[1948] Server: Sends the generated information to the terminal.

[1949] Terminal: displays information to the user.

[1950] User: Review the information and enter any additional questions.

[1951] Terminal: Sends a follow-up question to the server.

[1952] Server: Aggregates information from additional questions, generates answers, and sends them to the device.

[1953] Terminal: Display the answer to the user.

[1954] 3. Discussion Consulting (2) Market and Company Analysis

[1955] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[1956] Terminal: Sends the request to the server.

[1957] Server: Collects and summarizes company public information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[1958] Server: Generates a company analysis report based on the summarized information and sends it to the terminal.

[1959] Terminal: Display company analysis reports to the user.

[1960] User: Review the analysis report and enter any additional questions.

[1961] Terminal: Sends a follow-up question to the server.

[1962] Server: Collects information again for any additional questions, generates answers, and sends them to the device.

[1963] Terminal: Display the answer to the user.

[1964] 4. Investment simulation in a virtual environment

[1965] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[1966] Terminal: Sends the request to the server.

[1967] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[1968] Server: Runs a double-speed simulation in the configured virtual environment and generates results (e.g., if held for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen).

[1969] Server: Sends the simulation results to the device.

[1970] Terminal: Displays the results to the user.

[1971] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, virtual investment simulations allow users to understand risks before actually starting an investment and deepen their knowledge for safe investments.

[1972] The processing flow will be explained below.

[1973] Support for understanding the basics of investing

[1974] Step 1:

[1975] User: Launches the application and enters a request: "I want to learn the basics of investing."

[1976] Step 2:

[1977] Terminal: Sends the user's request to the server.

[1978] Step 3:

[1979] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[1980] Step 4:

[1981] Server: Sends the generated basic information and quiz content to the device.

[1982] Step 5:

[1983] Terminal: Displays the submitted basic information and quiz content to the user.

[1984] Step 6:

[1985] User: Takes a quiz and enters the answer into the device.

[1986] Step 7:

[1987] Terminal: Sends the user's answer to the server.

[1988] Step 8:

[1989] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[1990] Step 9:

[1991] Server: Sends feedback to the device.

[1992] Step 10:

[1993] Terminal: Display feedback to the user.

[1994] Consulting (1) How to get started with investing

[1995] Step 1:

[1996] User: Enter a question about opening a brokerage account.

[1997] Step 2:

[1998] Terminal: Sends a question to the server.

[1999] Step 3:

[2000] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[2001] Step 4:

[2002] Server: Sends the aggregated information to the device.

[2003] Step 5:

[2004] Terminal: displays information to the user.

[2005] Step 6:

[2006] User: Review the information and re-enter any additional questions.

[2007] Step 7:

[2008] Terminal: Sends a follow-up question to the server.

[2009] Step 8:

[2010] Server: Re-aggregates information and generates answers for additional questions.

[2011] Step 9:

[2012] Server: Sends the generated answer to the device.

[2013] Step 10:

[2014] Terminal: Display the answer to the user.

[2015] Discussion Consulting (2) Market and Company Analysis

[2016] Step 1:

[2017] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[2018] Step 2:

[2019] Terminal: Sends the request to the server.

[2020] Step 3:

[2021] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[2022] Step 4:

[2023] Server: Summarizes the collected data and generates company analysis reports.

[2024] Step 5:

[2025] Server: Sends the generated company analysis report to the terminal.

[2026] Step 6:

[2027] Terminal: Display company analysis reports to the user.

[2028] Step 7:

[2029] User: Review the analysis report and enter any additional questions.

[2030] Step 8:

[2031] Terminal: Sends a follow-up question to the server.

[2032] Step 9:

[2033] Server: Collects information again for additional questions and generates answers.

[2034] Step 10:

[2035] Server: Sends the generated answer to the device.

[2036] Step 11:

[2037] Terminal: Display the answer to the user.

[2038] Investment simulation in a virtual environment

[2039] Step 1:

[2040] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2041] Step 2:

[2042] Terminal: Sends the request to the server.

[2043] Step 3:

[2044] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[2045] Step 4:

[2046] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[2047] Step 5:

[2048] Server: Sends the generated simulation results to the device.

[2049] Step 6:

[2050] Terminal: displays the simulation results to the user.

[2051] Through the above process steps, users can gradually learn the basics of investing and receive support for specific investment actions. Through virtual investment simulations, users can understand the risks before actually starting an investment and deepen their knowledge for safe investment.

[2052] Example 1

[2053] 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."

[2054] Conventional investment learning systems lack sufficient interactivity and feedback functions to enable beginners and intermediate users to efficiently learn investment information and support their actual investment behavior. As a result, users encounter many difficulties in the self-learning process and are at a high risk of making incorrect decisions. The present invention aims to solve these problems and provide a system that enables users to efficiently learn investment information and supports their actual investment behavior.

[2055] 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.

[2056] In this invention, the server includes means for receiving basic investment questions from a user, means for generating appropriate basic investment information in response to the questions and presenting it to the user, means for generating interactive learning content in the form of a quiz using a generative AI model and displaying it to the user, means for receiving answers to the quizzes from the user, analyzing the answers and generating feedback, and means for presenting the feedback to the user. This allows the user to intuitively acquire investment knowledge and prepare for actual investment behavior.

[2057] "User" refers to an individual or organization who uses the system to obtain investment information, learn, or ask questions.

[2058] A "server" is a dedicated computer system that receives requests from users, generates information about appropriate investments, and provides feedback and content.

[2059] A "terminal" is a device (e.g., smartphone, tablet, or PC) that a user uses to communicate with a server, obtain information, and perform operations.

[2060] "Basic information about investments" refers to information that includes the definition of investments, basic investment knowledge and terminology such as stocks and bonds.

[2061] A "generative AI model" is a model generated using artificial intelligence technology, and is a program that generates appropriate responses to user input.

[2062] "Quiz-style interactive learning content" refers to educational content designed to enable users to acquire knowledge about investments by answering quizzes.

[2063] "Feedback" is a response to a user's quiz answers, including whether they were correct or incorrect, as well as additional study information and advice.

[2064] "Basic questions" are questions that users ask the server about basic knowledge and procedures related to investment.

[2065] "Information on opening a securities account" refers to information on the documents and procedural steps required to open a securities account, as well as information on recommended securities companies.

[2066] A "corporate analysis report" is a document containing a summary and analysis results generated from public information, stock price charts, and related press reports of a specific company.

[2067] A "virtual investment environment" is a simulation environment in which users can make virtual investments and predict investment results using actual market data.

[2068] MODE FOR CARRYING OUT THE INVENTION

[2069] The present invention is a system that allows users to efficiently learn about investment information and supports actual investment behavior, and is operated through the interaction of users, a server, and terminals. Specifically, the system is implemented in the following manner.

[2070] Hardware and software used

[2071] Hardware: Server (general cloud-based server system), user device (smartphone, tablet, PC)

[2072] Software: Investment learning applications, generative AI models (e.g., GPT-3), database management systems (e.g., MySQL), data collection APIs (e.g., Google Finance API)

[2073] System operation explanation

[2074] 1. Support for understanding the basics of investing

[2075] The user starts the application and inputs a request to learn the basics of investing. For example, the user directly inputs "I want to learn the basics of investing."

[2076] The device sends the user's request to the server. The request data is sent in JSON format.

[2077] The server retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates quiz-style learning content using a generative AI model (e.g., GPT-3).

[2078] The server transmits the generated information and quiz content to the terminal.

[2079] The terminal visually displays the transmitted information and quiz content to the user.

[2080] The user answers the quiz and transmits the answers to the terminal.

[2081] The server analyzes the user's answers, generates feedback, and sends it to the terminal.

[2082] The terminal displays the feedback to the user.

[2083] Examples:

[2084] Prompt: "I want to learn the basics of investing."

[2085] Example feedback: "Your answer is correct! You understand the basics of investing."

[2086] 2. Discussion Consulting (1) How to Start Investing

[2087] The user inputs a question about opening a securities account, for example, "What documents do I need to open a securities account?"

[2088] The terminal sends a query to the server.

[2089] The server collects information regarding the opening of a securities account, compiles it into a concise form, and transmits it to the terminal.

[2090] The terminal displays the transmitted information to the user.

[2091] The user will review the information and re-enter any additional questions.

[2092] The terminal sends a follow-up question to the server.

[2093] The server aggregates the information for the additional questions, generates an answer, and sends it to the terminal.

[2094] The terminal displays the answer to the user.

[2095] Examples:

[2096] Prompt: "What documents do I need to open a brokerage account?"

[2097] Example feedback: "The documents required are identification (passport or driver's license), proof of current address (resident registration card), etc."

[2098] 3. Discussion Consulting (2) Market and Company Analysis

[2099] A user requests an analysis of a specific company, for example, "Tell me about the recent performance of Company X."

[2100] The terminal sends a request to the server.

[2101] The server collects public company information, stock charts, and related press reports, and generates company analysis reports.

[2102] The server transmits the generated company analysis report to the terminal.

[2103] The terminal displays the company analysis report to the user.

[2104] The user reviews the report and re-enters any additional questions.

[2105] The terminal sends a follow-up question to the server.

[2106] The server collects information for the additional questions, generates answers, and sends them to the terminal.

[2107] The terminal displays the answer to the user.

[2108] Examples:

[2109] Prompt: "Tell me about Company X's recent performance."

[2110] Example feedback: "Company X has seen a 10% increase in sales compared to the same month last year, and a 15% increase in profits."

[2111] 4. Investment simulation in a virtual environment

[2112] The user requests an investment simulation in a virtual environment, for example, by entering "What would happen if I invested 100,000 yen for three years?"

[2113] The terminal sends a request to the server.

[2114] The server sets up a virtual investment environment based on the user's input data (e.g., investment amount, investment period).

[2115] The server runs the simulation in the virtual environment and generates the results.

[2116] The server transmits the simulation results to the terminal.

[2117] The terminal displays the simulation results to the user.

[2118] Examples:

[2119] Prompt: "What would happen if you invested $1,000 for three years?"

[2120] Example feedback: "If you hold the investment for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen."

[2121] This allows users to understand the risks before they actually begin investing and deepen the knowledge they need to make appropriate decisions.

[2122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2123] 1. Support for understanding the basics of investing

[2124] Step 1:

[2125] A user launches the application and types, "I want to learn the basics of investing."

[2126] Input: User request ("I want to learn the basics of investing")

[2127] What it does: Enter a request into a text input field within the app.

[2128] Output: Request data (text format)

[2129] Step 2:

[2130] The device sends a request to the server.

[2131] Input: User request data

[2132] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[2133] Output: Request data sent to the server

[2134] Step 3:

[2135] The server generates basic information about investments and creates learning content in the form of quizzes.

[2136] Input: Request data

[2137] How it works: It retrieves basic investment information from a database and uses a generative AI model (e.g., GPT-3) to generate interactive learning content in the form of quizzes.

[2138] Output: Basic information and quiz content (JSON format)

[2139] Step 4:

[2140] The server transmits the generated information and quiz content to the terminal.

[2141] Input: Basic information and quiz content

[2142] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[2143] Output: Data sent to the terminal

[2144] Step 5:

[2145] The terminal displays the transmitted information and quiz content to the user.

[2146] Input: Data from the server

[2147] Behavior: Parses the received JSON data and visually displays basic information and quiz content on the screen.

[2148] Output: The information displayed to the user and the quiz

[2149] Step 6:

[2150] The user answers the quiz and transmits the answers to the terminal.

[2151] Input: User's quiz answer

[2152] Action: Enter the quiz answer in the input field and press the submit button.

[2153] Output: Quiz answers sent to the device

[2154] Step 7:

[2155] The server collects the user's answers, analyzes whether they are correct or incorrect, and generates feedback.

[2156] Input: Quiz response data

[2157] How it works: Your answers are matched against existing ground truth data and feedback is generated using a generative AI model.

[2158] Output: Feedback data (JSON format)

[2159] Step 8:

[2160] The server sends the feedback to the device.

[2161] Input: Feedback data

[2162] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[2163] Output: Feedback data sent to the device

[2164] Step 9:

[2165] The device displays the feedback to the user.

[2166] Input: Feedback data

[2167] Behavior: Parses the received JSON data and displays feedback on the screen.

[2168] Output: Feedback displayed to the user

[2169] 2. Discussion Consulting (1) How to Start Investing

[2170] Step 1:

[2171] The user enters a question about opening a securities account.

[2172] Input: User question ("What documents do I need to open a brokerage account?")

[2173] What it does: Type a question into a text input field within the app.

[2174] Output: Question data (text format)

[2175] Step 2:

[2176] The terminal sends a question to the server.

[2177] Input: User question data

[2178] What it does: It converts question data into JSON format and sends it to the server via HTTP protocol.

[2179] Output: Question data sent to the server

[2180] Step 3:

[2181] The server collects and summarizes information about opening a securities account.

[2182] Input: User question data

[2183] What it does: Retrieves the necessary information from databases and external APIs, aggregates the information, and summarizes it succinctly.

[2184] Output: Aggregated information data (JSON format)

[2185] Step 4:

[2186] The server transmits the generated information to the terminal.

[2187] Input: Aggregated information data

[2188] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[2189] Output: Information data sent to the terminal

[2190] Step 5:

[2191] The terminal displays the information to the user.

[2192] Input: Information data from the server

[2193] What it does: Parses the received JSON data and displays the information visually on the screen.

[2194] Output: Information displayed to the user

[2195] Step 6:

[2196] The user enters a follow-up question.

[2197] Input: User's additional question

[2198] Action: Enter a follow-up question into the text entry field.

[2199] Output: Additional question data (text format)

[2200] Step 7:

[2201] The terminal sends a follow-up question to the server.

[2202] Input: User's additional question data

[2203] Behavior: The question data is converted to JSON format and sent to the server.

[2204] Output: Additional question data sent to the server

[2205] Step 8:

[2206] The server aggregates the information for the follow-up questions and generates an answer.

[2207] Input: Additional question data

[2208] What it does: Recollects information from databases and external APIs and generates answers.

[2209] Output: Generated response data (JSON format)

[2210] Step 9:

[2211] The server sends the response to the terminal.

[2212] Input: Generated response data

[2213] What it does: Composes data in JSON format and sends it to the device.

[2214] Output: Answer data sent to the device

[2215] Step 10:

[2216] The terminal displays the answer to the user.

[2217] Input: Response data from the server

[2218] Behavior: Parses the received JSON data and displays the answer on the screen.

[2219] Output: The answer displayed to the user

[2220] 3. Discussion Consulting (2) Market and Company Analysis

[2221] Step 1:

[2222] A user requests an analysis of a specific company.

[2223] Input: User's company analysis request ("Tell me about company X's recent performance")

[2224] What it does: Enter a request into a text input field within the app.

[2225] Output: Request data (text format)

[2226] Step 2:

[2227] The device sends a request to the server.

[2228] Input: User request data

[2229] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[2230] Output: Request data sent to the server

[2231] Step 3:

[2232] The server collects and summarizes company public information, stock charts, and related press coverage.

[2233] Input: User request data

[2234] What it does: Uses databases and external APIs to collect and summarize company public information, stock charts, and related press.

[2235] Output: Summarized company information data (JSON format)

[2236] Step 4:

[2237] The server generates a company analysis report and sends it to the terminal.

[2238] Input: Summarized company information data

[2239] What it does: Generates a company analysis report based on the summary data and sends it to the device in JSON format.

[2240] Output: Generated company analysis report data (JSON format)

[2241] Step 5:

[2242] The terminal displays the company analysis report to the user.

[2243] Input: Report data from the server

[2244] What it does: Parses the received JSON data and displays a report on the screen.

[2245] Output: Company analysis report displayed to the user

[2246] Step 6:

[2247] The user enters a follow-up question.

[2248] Input: User's additional question

[2249] Action: Enter a follow-up question into the text entry field.

[2250] Output: Additional question data (text format)

[2251] Step 7:

[2252] The terminal sends a follow-up question to the server.

[2253] Input: User's additional question data

[2254] Behavior: The question data is converted to JSON format and sent to the server.

[2255] Output: Additional question data sent to the server

[2256] Step 8:

[2257] The server recollects information for additional questions and generates answers.

[2258] Input: Additional question data

[2259] How it works: Generates an answer based on the recollected information and sends it to the device in JSON format.

[2260] Output: Generated response data (JSON format)

[2261] Step 9:

[2262] The server sends the response to the terminal.

[2263] Input: Generated response data

[2264] What it does: Composes data in JSON format and sends it to the device.

[2265] Output: Answer data sent to the device

[2266] Step 10:

[2267] The terminal displays the answer to the user.

[2268] Input: Response data from the server

[2269] Behavior: Parses the received JSON data and displays the answer on the screen.

[2270] Output: The answer displayed to the user

[2271] 4. Investment simulation in a virtual environment

[2272] Step 1:

[2273] A user requests an investment simulation.

[2274] Input: User simulation request ("What happens if I invest $1,000 for three years?")

[2275] What it does: Enter a request into a text input field within the app.

[2276] Output: Request data (text format)

[2277] Step 2:

[2278] The device sends a request to the server.

[2279] Input: User request data

[2280] What it does: Converts the request data into JSON format and sends it to the server via HTTP.

[2281] Output: Request data sent to the server

[2282] Step 3:

[2283] The server sets up a virtual investment environment based on the user's input data.

[2284] Input: Request data (investment amount, investment period, etc.)

[2285] How it works: Runs an algorithm to create a virtual investment environment based on input data.

[2286] Output: Set virtual investment environment data

[2287] Step 4:

[2288] The server runs the double-speed simulation in a configured virtual environment and generates the results.

[2289] Input: Hypothetical investment environment data

[2290] How it works: Runs simulations twice as fast in a virtual environment to calculate investment results.

[2291] Output: Simulation result data (e.g., 115,700 yen over 3 years at an annual interest rate of 5%)

[2292] Step 5:

[2293] The server transmits the simulation results to the terminal.

[2294] Input: Simulation result data

[2295] Behavior: Composes data in JSON format and sends it to the device as an HTTP response.

[2296] Output: Simulation result data sent to the terminal

[2297] Step 6:

[2298] The terminal displays the simulation results to the user.

[2299] Input: Simulation result data

[2300] Operation: Parses the received JSON data and visually displays the simulation results on the screen.

[2301] Output: Simulation results displayed to the user

[2302] This allows users to intuitively acquire investment knowledge and prepare for actual investment actions. Virtual investment simulations also allow users to understand risks and deepen their knowledge for safe investments.

[2303] (Application example 1)

[2304] 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."

[2305] Existing systems that enable users from beginners to intermediate investors to efficiently learn investment information and support actual investment activities tend to be one-way, lacking interactivity. It was also difficult to provide a wide range of information and support necessary for investing, such as opening a securities account, company analysis, and virtual investment simulations, all in one system. Therefore, a system was needed that would allow users to intuitively learn about investment from the basics to advanced applications, while also allowing them to move smoothly and safely into actual investment activities.

[2306] 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.

[2307] In this invention, the server includes: means for receiving basic investment questions from a user; means for generating appropriate basic investment information in response to the questions and presenting it to the user; means for generating quiz-style interactive learning content and displaying it to the user; means for receiving user answers to the quizzes and analyzing the answers to generate feedback; means for presenting the feedback to the user; means for receiving user questions regarding company analysis; means for collecting and summarizing public company information, stock price charts, and related news reports in response to the questions; means for generating a company analysis report based on the summarized information; means for presenting the company analysis report to the user; means for re-collecting information in response to additional user questions and generating answers; means for presenting the answers to the user; means for receiving user requests for virtual investment simulations; means for designing a virtual investment environment based on the request; means for executing a virtual simulation and generating results; and means for presenting the simulation results to the user. This provides comprehensive support for users as they transition to actual investment behavior while consistently learning about investment from the basics to applications and practice, enabling beginners to intermediate investors to invest safely and efficiently.

[2308] "User" refers to a person who uses the electronic payment application to learn investment-related information and take actual investment actions.

[2309] "Server" refers to a computer system that generates investment information in response to a request from a user and provides it to the user.

[2310] "Basic information" refers to basic knowledge and definitions of investment, as well as information on basic investment vehicles such as stocks and bonds.

[2311] "Quiz" refers to an interactive set of questions that allows users to test their investing knowledge.

[2312] "Interactive learning content" refers to learning materials and activities that progress through two-way interaction between the user and the system.

[2313] "Feedback" refers to evaluations and advice information generated by the system through analysis of users' quiz answers and requests.

[2314] "Company analysis" refers to the process of evaluating the performance and market position of a particular company using public information, stock charts, and related press coverage.

[2315] "Public information" refers to information such as financial reports and press releases that companies make public.

[2316] "Virtual investment simulation" refers to a system that predicts investment results in a virtual investment environment based on the investment amount and period specified by the user.

[2317] "Virtual investment environment" refers to virtual market conditions and investment conditions for simulations set based on user input data.

[2318] "Results" refers to the predicted investment return and risk output based on a hypothetical investment simulation.

[2319] This invention is a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities. The system is mainly operated through the interaction between the server, terminals, and users. The implementation method for each main function is shown below.

[2320] First, the system has a means for receiving basic questions about investment from users. When a user inputs a question about the basics of investing from a terminal, the request is sent to the server. The server generates basic information about investment and presents it to the user. This basic information is provided as interactive learning content in the form of quizzes to make it easy for beginners to understand, such as the definitions of stocks and bonds. For example, in response to the question, "What is investment?", the system provides feedback in the form of a quiz, such as, "Investment is a means of increasing funds."

[2321] The server then receives questions from users about how to open a securities account and aggregates the appropriate information to present to the user. When a user requests "How do I open a securities account?" via a terminal, the server provides the necessary documents, procedural steps, a list of highly rated securities companies, and so on.

[2322] Furthermore, the system has a function to receive questions about company analysis from users. When a user types "Tell me about Company X's latest performance," the server collects and summarizes the company's public information, stock price charts, and related news reports. It then generates a company analysis report based on the summarized information and presents it to the user.

[2323] It also has a virtual investment simulation function. When a user inputs a request into the terminal, such as "What will be the results if I invest 100,000 yen for three years?", the request is sent to the server. The server designs a virtual investment environment based on the data entered by the user, runs a simulation, and generates the results. The simulation results are presented to the user via the terminal. For example, if you hold the investment for three years under the condition of an annual interest rate of 5%, the total amount will be approximately 115,700 yen.

[2324] This system is implemented using programming languages ​​such as Python, and frameworks and libraries (e.g., Flask and Django) for managing HTTP requests. The server runs on a RESTful API, and the database stores the latest investment information, company disclosures, and user learning history. It also uses machine learning models to analyze users' quiz answers and simulation results and generate personalized feedback and advice.

[2325] To illustrate this, here are some example prompts generated using a generative AI model:

[2326] Prompt Sentence Examples

[2327] "A user types in 'What is the recent performance of Company X?' The server processes it in the following steps:

[2328] 1. Search for public information about Company X.

[2329] 2. Collect financial reports, press releases, and related media coverage.

[2330] 3. Summarize the collected information and generate a company analysis report.

[2331] 4. Provide the generated report to the user.

[2332] In this way, the user is supported in making safe and efficient investment decisions while consistently learning everything from the basics to the practical aspects of investing.

[2333] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2334] Step 1:

[2335] The user enters basic investment questions.

[2336] In this step, the user launches the smartphone app and inputs a request such as "I want to learn the basics of investing." The input request is sent to the server via the device. The input data is natural language text data containing the user's question.

[2337] Step 2:

[2338] The server generates basic information about the investment and presents it to the user.

[2339] The server analyzes the received question data and generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.). The generated data is organized into interactive learning content in the form of a quiz. The generated information and quiz content are then sent back to the device. In this step, the server uses a generative AI model to generate this data.

[2340] Step 3:

[2341] The terminal displays the transmitted information and quiz content to the user.

[2342] The terminal receives the information from the server and displays it to the user, who then inputs answers to the displayed quiz questions.

[2343] Step 4:

[2344] The server receives the user's quiz answers, analyzes them and generates feedback.

[2345] The user's answer data is sent from the device to the server. The server analyzes this data and determines whether the user's answer is correct or incorrect. Feedback is generated based on the analysis results and sent to the device. Here too, a generative AI model is used to generate the feedback.

[2346] Step 5:

[2347] The terminal displays the feedback to the user.

[2348] The device displays the feedback received from the server to the user, including whether the answer was correct or incorrect and any additional advice.

[2349] Step 6:

[2350] A user requests an analysis of a specific company.

[2351] The user inputs a request such as "Tell me about the recent performance of Company X." The input data is sent to the server via the terminal.

[2352] Step 7:

[2353] The server collects and summarizes company public information, stock charts, and related press coverage.

[2354] Based on the received request, the server searches and collects public information, stock price charts, and related press reports related to Company X. The collected data is then summarized and organized into a company analysis report. This summarization process utilizes a generative AI model.

[2355] Step 8:

[2356] The terminal presents the company analysis report to the user.

[2357] The terminal displays the company analysis report received from the server to the user, who then checks the contents.

[2358] Step 9:

[2359] A user requests a virtual investment simulation.

[2360] The user inputs a request such as "What will be the result if I invest 100,000 yen for three years?" The input data is sent to the server via the terminal.

[2361] Step 10:

[2362] The server designs the virtual investment environment and runs the simulation.

[2363] The server designs a virtual investment environment based on user input data (investment amount, investment period, etc.), then runs a virtual simulation to generate investment results. The simulation is performed using a generative AI model and simulation algorithm.

[2364] Step 11:

[2365] The terminal presents the simulation results to the user.

[2366] The terminal receives simulation results from the server and displays them to the user, including estimated investment returns and risk information.

[2367] 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.

[2368] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[2369] A natural language description of the program's operation

[2370] 1. Support for understanding the basics of investing

[2371] User: Launches the application and enters a request: "I want to learn the basics of investing."

[2372] Terminal: Sends the user's request to the server.

[2373] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[2374] Server: Sends the generated basic information and quiz content to the device.

[2375] Terminal: Displays the submitted basic information and quiz content to the user.

[2376] User: Takes a quiz and enters the answer into the device.

[2377] Terminal: Sends the user's answer to the server.

[2378] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[2379] Server: Sends feedback to the device.

[2380] Terminal: Display feedback to the user.

[2381] 2. Discussion Consulting (1) How to Start Investing

[2382] User: Enter a question about opening a brokerage account.

[2383] Terminal: Sends a question to the server.

[2384] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[2385] Server: Sends the aggregated information to the device.

[2386] Terminal: displays information to the user.

[2387] User: Review the information and re-enter any additional questions.

[2388] Terminal: Sends a follow-up question to the server.

[2389] Server: Re-aggregates information and generates answers for additional questions.

[2390] Server: Sends the generated answer to the device.

[2391] Terminal: Display the answer to the user.

[2392] 3. Discussion Consulting (2) Market and Company Analysis

[2393] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[2394] Terminal: Sends the request to the server.

[2395] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[2396] Server: Summarizes the collected data and generates company analysis reports.

[2397] Server: Sends the generated company analysis report to the terminal.

[2398] Terminal: Display company analysis reports to the user.

[2399] User: Review the analysis report and enter any additional questions.

[2400] Terminal: Sends a follow-up question to the server.

[2401] Server: Collects information again for additional questions and generates answers.

[2402] Server: Sends the generated answer to the device.

[2403] Terminal: Display the answer to the user.

[2404] 4. Investment simulation in a virtual environment

[2405] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2406] Terminal: Sends the request to the server.

[2407] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[2408] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[2409] Server: Sends the generated simulation results to the device.

[2410] Terminal: displays the simulation results to the user.

[2411] 5. Incorporating an Emotional Engine

[2412] User: Enters questions and commands into the terminal.

[2413] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[2414] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[2415] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[2416] Server: Sends tailored information and feedback to the device.

[2417] Device: Display tailored information and feedback to the user.

[2418] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[2419] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[2420] The processing flow will be explained below.

[2421] Support for understanding the basics of investing

[2422] Step 1:

[2423] User: Launches the application and enters a request: "I want to learn the basics of investing."

[2424] Step 2:

[2425] Terminal: Sends the user's request to the server.

[2426] Step 3:

[2427] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[2428] Step 4:

[2429] Server: Sends the generated basic information and quiz content to the device.

[2430] Step 5:

[2431] Terminal: Displays the submitted basic information and quiz content to the user.

[2432] Step 6:

[2433] User: Takes a quiz and enters the answer into the device.

[2434] Step 7:

[2435] Terminal: Sends the user's answer to the server.

[2436] Step 8:

[2437] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[2438] Step 9:

[2439] Server: Sends feedback to the device.

[2440] Step 10:

[2441] Terminal: Display feedback to the user.

[2442] Consulting (1) How to get started with investing

[2443] Step 1:

[2444] User: Enter a question about opening a brokerage account.

[2445] Step 2:

[2446] Terminal: Sends a question to the server.

[2447] Step 3:

[2448] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[2449] Step 4:

[2450] Server: Sends the aggregated information to the device.

[2451] Step 5:

[2452] Terminal: displays information to the user.

[2453] Step 6:

[2454] User: Review the information and re-enter any additional questions.

[2455] Step 7:

[2456] Terminal: Sends a follow-up question to the server.

[2457] Step 8:

[2458] Server: Re-aggregates information and generates answers for additional questions.

[2459] Step 9:

[2460] Server: Sends the generated answer to the device.

[2461] Step 10:

[2462] Terminal: Display the answer to the user.

[2463] Discussion Consulting (2) Market and Company Analysis

[2464] Step 1:

[2465] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[2466] Step 2:

[2467] Terminal: Sends the request to the server.

[2468] Step 3:

[2469] Server: Collects public company information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[2470] Step 4:

[2471] Server: Summarizes the collected data and generates company analysis reports.

[2472] Step 5:

[2473] Server: Sends the generated company analysis report to the terminal.

[2474] Step 6:

[2475] Terminal: Display company analysis reports to the user.

[2476] Step 7:

[2477] User: Review the analysis report and enter any additional questions.

[2478] Step 8:

[2479] Terminal: Sends a follow-up question to the server.

[2480] Step 9:

[2481] Server: Collects information again for additional questions and generates answers.

[2482] Step 10:

[2483] Server: Sends the generated answer to the device.

[2484] Step 11:

[2485] Terminal: Display the answer to the user.

[2486] Investment simulation in a virtual environment

[2487] Step 1:

[2488] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2489] Step 2:

[2490] Terminal: Sends the request to the server.

[2491] Step 3:

[2492] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[2493] Step 4:

[2494] Server: Runs the double-speed simulation in the configured virtual environment and generates the simulation results.

[2495] Step 5:

[2496] Server: Sends the generated simulation results to the device.

[2497] Step 6:

[2498] Terminal: displays the simulation results to the user.

[2499] Incorporating an emotion engine

[2500] Step 1:

[2501] User: Enters questions and commands into the terminal.

[2502] Step 2:

[2503] Terminal: Sends user input to the server and simultaneously requests emotion recognition from the emotion engine.

[2504] Step 3:

[2505] Emotion engine: Analyzes user input data (text, facial expressions, tone of voice, etc.) to determine the user's emotional state (e.g., stress, anxiety, positive emotion).

[2506] Step 4:

[2507] Server: Receives the emotion analysis results from the emotion engine and adjusts the information and feedback provided based on the results.

[2508] Step 5:

[2509] Server: Sends tailored information and feedback to the device.

[2510] Step 6:

[2511] Device: Display tailored information and feedback to the user.

[2512] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server will provide step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a user requests an investment simulation and positive emotions are detected, the server will suggest advanced investment strategies, including risk.

[2513] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, through emotion analysis and feedback using an emotion engine, users can receive personalized support according to their psychological state.

[2514] Example 2

[2515] 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."

[2516] In systems that enable beginners to intermediate investors to efficiently learn about investment information and support their actual investment behavior, there is a lack of appropriate feedback that takes into account the user's emotional state, making it difficult to effectively learn while reducing stress and anxiety.In addition, there is a problem in that the information is not properly customized, making it difficult to provide personalized investment advice.

[2517] 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 a means for analyzing input data from a user and determining the emotional state, a means for adjusting information and feedback according to the emotional state and presenting it to the user, and a means for generating interactive learning content in the form of a quiz and displaying it to the user. This enables personalized learning support and investment advice that takes the user's emotional state into consideration.

[2518] A "user" is an individual or corporation that uses the system to learn investment information and receives support for actual investment actions.

[2519] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet, that communicates with a server and provides a user interface.

[2520] A "server" is a computer system that receives requests from users, performs the necessary processing, and returns information to the terminal.

[2521] "Quiz-style interactive learning content" refers to educational content in the form of questions and answers, intended to help users acquire knowledge about investments through their participation.

[2522] "Feedback" refers to the reaction or response provided by the system in response to the user's actions or input, and is supplementary information that deepens the user's understanding.

[2523] "Emotional state" refers to the psychological state that a user feels while using the system, and includes stress, anxiety, positive emotions, etc.

[2524] An "emotion engine" is a system that uses artificial intelligence to analyze user input data (text, facial expressions, tone of voice, etc.) and determine the user's emotional state.

[2525] "Basic information about investments" refers to information that includes the definition of investments and basic knowledge about stocks, bonds, etc.

[2526] "Information regarding opening a securities account" refers to information such as the documents required to open a securities account, procedural steps, and a list of recommended securities companies.

[2527] A "corporate analysis report" is an analytical document about a company's financial status and performance, generated based on the company's public information, stock price charts, and related news reports.

[2528] A "virtual investment environment" is an environment for simulating investments using virtual funds without using actual funds.

[2529] "Double-speed simulation" is a method of predicting future results by conducting an investment simulation at a speed faster than the normal rate of time.

[2530] "Natural language processing technology" is a technology for analyzing natural language such as text and speech, understanding its meaning, and processing it.

[2531] "Personalized" means providing information and services that are optimized for each individual user.

[2532] This invention is a system that provides even more advanced support by combining a system that allows beginners to intermediate investors to efficiently learn investment information and support their actual investment activities with an emotion engine that recognizes the user's emotional state. This system operates smoothly through the interaction between the user, server, terminal, and emotion engine.

[2533] In this invention, the terminal receives input from the user and sends it to the server. The server performs the necessary processing based on the received request and returns a response to the terminal. Specifically, the following hardware and software are used:

[2534] Hardware used

[2535] Device: Electronic devices such as computers, smartphones, and tablets.

[2536] Server: A high-performance computing system (e.g., cloud server, on-premise server).

[2537] Software used

[2538] Database: MySQL, PostgreSQL.

[2539] NLP (Natural Language Processing) technologies: Generative AI models such as GPT-3 and BERT.

[2540] Quiz generation algorithm: Python script.

[2541] Emotion engine: Text analysis, speech analysis, and facial expression analysis technologies (e.g., Azure Cognitive Services, Amazon Rekognition).

[2542] Specific processing content and operations

[2543] 1. Support for learning the basics of investing

[2544] A user launches the application and types, "I want to learn the basics of investing."

[2545] The terminal sends the user's request to the server, which retrieves basic information about the investment from a database.

[2546] The server generates interactive learning content in the form of a quiz and transmits it to the terminal.

[2547] The terminal displays the quiz content to the user, and the user inputs an answer.

[2548] The server analyzes the user's answers, generates feedback, and sends it to the terminal, which then displays the feedback to the user.

[2549] 2. Discussion Consulting (1) How to Start Investing

[2550] The user enters questions regarding opening a securities account.

[2551] The terminal sends a question to the server, which then gathers the necessary information from a database and generates an answer.

[2552] The terminal displays the information, and if the user enters a follow-up question, it sends it back to the server and receives a new answer.

[2553] 3. Discussion Consulting (2) Market and Company Analysis

[2554] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[2555] The terminal sends a request to the server, which collects public information, summarizes the data, and generates a business analysis report.

[2556] The terminal displays the report, and if the user enters additional questions, it sends them back to the server and receives new answers.

[2557] 4. Investment simulation in a virtual environment

[2558] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2559] The device sends a request to the server, which sets up a virtual environment and runs the simulation.

[2560] The terminal displays the simulation results to the user.

[2561] 5. Incorporating an Emotional Engine

[2562] When the user inputs a question or command, the device sends it to the server, which then requests the emotion engine to analyze the emotion.

[2563] The emotion engine determines the user's emotional state and sends the result to the server.

[2564] The server adjusts the information and feedback based on the emotion analysis results, sends it to the device, and displays it to the user.

[2565] Specific examples

[2566] For example, if a user inquires about opening a securities account and the emotion engine determines that the user is feeling anxious, the server can provide additional step-by-step guidance and encouraging messages to alleviate the anxiety. Similarly, if a positive emotion is detected when a user requests an investment simulation, the server can suggest advanced investment strategies, including risk.

[2567] Examples of prompts are:

[2568] What documents do I need to open a securities account?

[2569] "Tell me about Company X's recent performance."

[2570] "Please simulate what would happen if I invested 100,000 yen for three years."

[2571] This invention allows users to intuitively acquire investment knowledge and prepare for actual investment activities. Emotion analysis by the emotion engine and feedback from that analysis enable users to receive personalized support according to their psychological state.

[2572] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2573] Support for understanding the basics of investing

[2574] Step 1:

[2575] A user launches the application and types, "I want to learn the basics of investing."

[2576] Input: User text input

[2577] Specific actions: A user opens the mobile or web app, types "I want to learn the basics of investing" into the input form, and presses the submit button.

[2578] Output: User request data

[2579] Step 2:

[2580] The terminal sends the user's request to the server.

[2581] Input: User request data

[2582] Specific operation: The terminal sends the user's input data as an HTTP request.

[2583] Output: Request sent to the server

[2584] Step 3:

[2585] The server receives the request and retrieves basic information about the investment from a database.

[2586] Input: Request data

[2587] What it does: The server runs PHP and Python scripts to retrieve basic information for each category from a MySQL database.

[2588] Output: Investment basic information retrieved from the database

[2589] Step 4:

[2590] The server generates interactive learning content in the form of quizzes.

[2591] Input: Basic investment information

[2592] What it does: A Python script runs on the server to analyze the data and generate quiz-style content.

[2593] Output: Generated quiz content

[2594] Step 5:

[2595] The server transmits the generated content to the terminal.

[2596] Input: Generated quiz content

[2597] Specific operation: The quiz content generated by the server is formatted in JSON format and sent to the terminal as an HTTP response.

[2598] Output: Quiz content sent to device

[2599] Step 6:

[2600] The terminal displays the transmitted content to the user.

[2601] Input: Quiz content

[2602] Specific behavior: The device's browser or mobile app parses the JSON data and displays it in the user interface.

[2603] Output: Displayed quiz-style learning content

[2604] Step 7:

[2605] The user answers the quiz and enters the answers into the terminal.

[2606] Input: User's quiz answer

[2607] Specific actions: The user selects an option on the interface, confirms the answer, and presses the submit button.

[2608] Output: Quiz answer data entered on the device

[2609] Step 8:

[2610] The terminal sends the user's answer to the server.

[2611] Input: User response data

[2612] Specific operation: The terminal sends the response data to the server as an HTTP request.

[2613] Output: Response data sent to the server

[2614] Step 9:

[2615] The server analyzes the answers and generates feedback.

[2616] Input: Answer data

[2617] Specific operation: A script on the server analyzes the answer data and generates correct and incorrect answers and supplementary explanations.

[2618] Output: Generated feedback data

[2619] Step 10:

[2620] The server sends the feedback to the device.

[2621] Input: Feedback data

[2622] Specific operation: The server formats the feedback data into JSON format and sends it to the terminal as an HTTP response.

[2623] Output: Feedback data sent to the device

[2624] Step 11:

[2625] The device displays the feedback to the user.

[2626] Input: Feedback data

[2627] Specific operation: The device analyzes the data and displays a feedback message on the user interface.

[2628] Output: The feedback message displayed to the user

[2629] Consulting (1) How to get started with investing

[2630] Step 1:

[2631] The user enters questions regarding opening a securities account.

[2632] Input: User text input

[2633] Specific operation: The user types "What documents are required to open a securities account?" into the input form and presses the submit button.

[2634] Output: User question data

[2635] Step 2:

[2636] The terminal sends a question to the server.

[2637] Input: Question data

[2638] Specific operation: The terminal sends the question data as an HTTP request.

[2639] Output: The query data sent to the server

[2640] Step 3:

[2641] The server receives the question and gathers the necessary information from a database to generate an answer.

[2642] Input: Question data

[2643] What it does: The server runs an SQL query to retrieve the information needed to open a brokerage account from a database. The server then cross-parses this information and generates a clear answer.

[2644] Output: Generated response data

[2645] Step 4:

[2646] The server generates a response and sends it to the terminal.

[2647] Input: Answer data

[2648] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[2649] Output: Response data sent to the device

[2650] Step 5:

[2651] The terminal displays the answer to the user.

[2652] Input: Answer data

[2653] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[2654] Output: The answer displayed to the user

[2655] Step 6:

[2656] The user enters a follow-up question.

[2657] Input: User's additional question

[2658] Specific behavior: The user enters further questions into the input form and presses the submit button.

[2659] Output: Additional question data

[2660] Step 7:

[2661] The terminal sends a follow-up question to the server.

[2662] Input: Additional question data

[2663] Specific operation: The device sends additional question data as an HTTP request.

[2664] Output: Additional question data sent to the server

[2665] Step 8:

[2666] The server gathers new information and generates an answer.

[2667] Input: Additional question data

[2668] What happens: The server runs the SQL query, retrieves additional information from the database, parses it, and generates an answer.

[2669] Output: The newly generated answer

[2670] Step 9:

[2671] The server generates a response and sends it to the terminal.

[2672] Input: Newly generated answer

[2673] Specific operation: The response generated by the server is formatted in JSON and sent to the terminal as an HTTP response.

[2674] Output: Answer sent to terminal

[2675] Step 10:

[2676] The terminal displays the answer to the user.

[2677] Input: Answer data

[2678] Specific behavior: The device's browser or app parses the JSON data and displays it in the user interface.

[2679] Output: The new answer displayed to the user

[2680] Discussion Consulting (2) Market and Company Analysis

[2681] Step 1:

[2682] A user requests an analysis of a specific company (e.g., "Tell me about company X's recent performance").

[2683] Input: User text input

[2684] Specific operation: The user enters the company name and question in the input form and presses the submit button.

[2685] Output: User's analysis request data

[2686] Step 2:

[2687] The terminal sends a request to the server.

[2688] Input: Analysis request data

[2689] Specific operation: The terminal sends the analysis request data as an HTTP request.

[2690] Output: Analysis request data sent to the server

[2691] Step 3:

[2692] The server collects public information and summarizes the data to generate business analysis reports.

[2693] Input: Analysis request data

[2694] How it works: The server uses web scraping to collect publicly available financial reports, press releases, and stock price information, then uses NLP techniques to summarize and generate analytical reports.

[2695] Output: Generated company analysis report

[2696] Step 4:

[2697] The server sends the report to the device.

[2698] Input: Company Analysis Report

[2699] Specific operation: The report generated by the server is formatted into PDF or JSON format and sent to the terminal as an HTTP response.

[2700] Output: Company analysis report sent to terminal

[2701] Step 5:

[2702] The terminal displays the report to the user.

[2703] Input: Company Analysis Report

[2704] What happens: The device's browser or app will display the report using a PDF reader or other viewer.

[2705] Output: Company analysis report displayed to the user

[2706] Step 6:

[2707] The user enters a follow-up question.

[2708] Input: User's additional question

[2709] Specific behavior: The user enters further questions into the input form and presses the submit button.

[2710] Output: Additional question data

[2711] Step 7:

[2712] The terminal sends a follow-up question to the server.

[2713] Input: Additional question data

[2714] Specific operation: The device sends additional question data as an HTTP request.

[2715] Output: Additional question data sent to the server

[2716] Step 8:

[2717] The server again collects the data and generates an answer.

[2718] Input: Additional question data

[2719] What it does: The server uses SQL queries and NLP techniques to gather additional information, analyze it, and generate an answer.

[2720] Output: The newly generated answer

[2721] Step 9:

[2722] The server generates a response and sends it to the terminal.

[2723] Input: Newly generated answer

[2724] Specific operation: The server formats the generated response into PDF or JSON format and sends it to the terminal as an HTTP response.

[2725] Output: Answer sent to terminal

[2726] Step 10:

[2727] The terminal displays the answer to the user.

[2728] Input: Answer data

[2729] What happens: Your device's browser or app will display your answers using a PDF reader or other viewer.

[2730] Output: The new answer displayed to the user

[2731] Investment simulation in a virtual environment

[2732] Step 1:

[2733] A user requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2734] Input: User text input

[2735] Specific operation: The user types "What would happen if I invested 100,000 yen for three years?" into the input form and presses the submit button.

[2736] Output: User simulation request data

[2737] Step 2:

[2738] The device sends a request to the server.

[2739] Input: Simulation request data

[2740] Specific operation: The terminal sends the simulation request data as an HTTP request.

[2741] Output: Request data sent to the server

[2742] Step 3:

[2743] The server sets up a virtual investment environment based on the user's input data.

[2744] Input: Request data

[2745] Specific operation: The server sets up a virtual investment environment based on the input data (e.g., principal, investment period, predicted market environment, etc.).

[2746] Output: A virtual investment environment

[2747] Step 4:

[2748] The server runs the simulation in a virtual environment.

[2749] Input: A hypothetical investment environment

[2750] What it does: The server uses Monte Carlo simulations and other computational models to predict investment outcomes.

[2751] Output: Simulation results

[2752] Step 5:

[2753] The server generates the simulation results.

[2754] Input: Simulation results

[2755] Specific operation: The server analyzes the simulation result data and formats it as graphs and numerical data.

[2756] Output: Generated simulation result data

[2757] Step 6:

[2758] The server sends the results to the terminal.

[2759] Input: Generated simulation result data

[2760] Specific operation: The server formats the result data into JSON or graph format and sends it to the terminal as an HTTP response.

[2761] Output: Simulation results sent to the terminal

[2762] Step 7:

[2763] The terminal displays the simulation results to the user.

[2764] Input: Simulation results

[2765] Specific operation: The device's browser or app analyzes the results data and displays it as graphs or numerical data.

[2766] Output: Simulation results displayed to the user

[2767] Incorporating an emotion engine

[2768] Step 1:

[2769] The user enters a question or command.

[2770] Input: User text input

[2771] Specific operation: The user enters a question or command into the input form and presses the submit button.

[2772] Output: User input data

[2773] Step 2:

[2774] The device sends the input to the server and simultaneously requests the emotion engine to analyze the emotion.

[2775] Input: User-entered data

[2776] Specific operation: The device sends the user's input data as an HTTP request and requests emotion analysis from the emotion engine.

[2777] Output: Input data and sentiment analysis request sent to the server

[2778] Step 3:

[2779] The emotion engine analyzes the user's input data.

[2780] Input: User-entered data

[2781] How it works: The emotion engine performs text analysis, speech analysis, and facial expression analysis to determine the emotional state.

[2782] Output: Emotion analysis results

[2783] Step 4:

[2784] The emotion engine determines the emotional state and sends the result to the server.

[2785] Input: Sentiment analysis results

[2786] Specific operation: The emotion engine formats the analysis results into JSON format and sends them to the server.

[2787] Output: Sentiment analysis results sent to the server

[2788] Step 5:

[2789] The server receives the sentiment analysis results and adjusts the information and feedback it provides.

[2790] Input: Sentiment analysis results

[2791] Specific operation: The server generates appropriate feedback and information based on the analysis results and adjusts it according to the user's emotional state.

[2792] Output: Tailored feedback and information

[2793] Step 6:

[2794] The server sends the adjusted information and feedback to the device.

[2795] Input: Moderated feedback and information

[2796] Specific operation: The server formats the adjusted information into JSON format and sends it to the terminal as an HTTP response.

[2797] Output: Feedback and information sent to the device

[2798] Step 7:

[2799] The device displays information and feedback to the user.

[2800] Input: Feedback and Information

[2801] Specific behavior: The device analyzes the feedback and information and displays it in the user interface.

[2802] Output: Feedback or information displayed to the user

[2803] (Application example 2)

[2804] 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."

[2805] Many systems have been proposed to help beginners and intermediate investors efficiently learn reliable investment information and support their actual investment behavior. However, systems that provide support that takes into account the user's psychological state are still insufficient. In particular, they lack the functionality to provide real-time feedback on concerns or questions that arise during learning or investment simulations. Furthermore, content delivery that takes into account the user's emotional state has limited personalized support for individual users.

[2806] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic questions about investments from a user, means for generating basic information about investments appropriate to the questions and presenting it to the user, means for generating interactive learning content in the form of quizzes and displaying it to the user, means for receiving the user's answers to the quizzes and analyzing the answers to generate feedback, means for recognizing the user's emotional state, means for adjusting appropriate information and feedback based on the emotional state, and means for presenting the feedback to the user. This enables the user to intuitively acquire investment knowledge and prepare for investment behavior while receiving personalized support according to their emotional state.

[2807] "User" refers to an individual or corporation that uses the investment information learning system.

[2808] "Server" refers to the central control unit that receives requests from users and generates and presents appropriate information.

[2809] A "terminal" is a device that is directly operated by a user, and includes a smartphone, a computer, and the like.

[2810] "Basic information about investments" refers to information about the definition and basic concepts of investments, as well as types of stocks, bonds, etc.

[2811] "Quiz-style interactive learning content" refers to learning materials provided in the form of quizzes or questions and answers to assess a user's level of understanding.

[2812] "Feedback" refers to evaluations and instructional comments generated based on the user's quiz answers.

[2813] "Emotional state" refers to the psychological state exhibited by the user, and specifically includes stress, anxiety, positive emotions, and the like.

[2814] An "emotion engine" refers to a system that includes programs and algorithms for analyzing user input data and determining an emotional state.

[2815] "Personalized support" refers to individualized assistance tailored to the user's individual needs and emotional state.

[2816] "Investment learning content" refers to materials, videos, texts, etc. for learning investment knowledge and skills.

[2817] "Content distribution service" refers to an online service that provides users with necessary investment information and learning materials.

[2818] This invention is a system that enables beginners and intermediate investors to efficiently learn investment information and support their actual investment activities. In particular, by combining it with an emotion engine that recognizes the user's emotional state, it provides personalized support according to the user's psychological state.

[2819] Hardware and software used

[2820] Hardware

[2821] Device: smartphone or computer

[2822] Camera: Webcam, smartphone built-in camera

[2823] Server: Cloud or Dedicated Server

[2824] software

[2825] Emotion Engine: Emotion recognition program using OpenCV and Keras

[2826] Data analysis: Python, machine learning models (e.g., RandomForestClassifier)

[2827] Communication: REST API, Python requests library

[2828] Program processing

[2829] The server receives basic investment questions from users and generates appropriate basic information about investments. For example, it generates content such as the basics of stock investments and an overview of bonds. It provides interactive learning content in the form of quizzes, and when users answer, it analyzes their answers and generates feedback.

[2830] Furthermore, the system uses an emotion engine to recognize the user's emotional state and tailor appropriate information and feedback based on that state. For example, if the user is feeling anxious, the system will provide additional information or encouraging messages to alleviate their anxiety.

[2831] Specific examples

[2832] Example 1

[2833] A beginner investor is using the app to learn basic information about stock investment. If an anxious expression is detected during the learning process, the system displays an additional video about "How to reduce the risks of stock investment" and sends an encouraging message. It also displays prompts such as "Have you gained a deeper understanding?"

[2834] Example 2

[2835] The user asks how to open a brokerage account and the system provides the necessary information. If the system detects anxiety in the user's voice, it provides an additional step-by-step guide to the process. The prompt is "Are you ready to proceed?"

[2836] Prompt Sentence Examples

[2837] "What follow-up content would you provide if you detected anxiety in a user's facial expression while playing an investment learning video?"

[2838] "What quizzes or interactive elements will you add to check if users are understanding the video as they watch?"

[2839] "If you ask about opening a brokerage account and detect concerns, what guidance would you offer for moving forward?"

[2840] This system allows users to intuitively acquire investment knowledge and prepare for investment activities while receiving support tailored to their emotional state.

[2841] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2842] Step 1:

[2843] A user uses a smartphone or computer to launch an investment learning application and input basic investment questions. This input is sent to a terminal, which then sends the data to a server. The input data includes the user's question. The output is the question data sent to the server.

[2844] Step 2:

[2845] The server analyzes the query data received from the user and retrieves basic information about appropriate investments (e.g., the definition of stock investment and risk management methods) from the database. During this process, the server searches for relevant information in the database based on the query and selects the most appropriate information. The output is data containing appropriate investment information.

[2846] Step 3:

[2847] The server generates quiz-style interactive learning content based on the acquired basic information. This content is in the form of questions to verify the user's knowledge level. The generated content is sent from the server to the terminal. The input is the basic information, and the output is the generated quiz content.

[2848] Step 4:

[2849] The terminal displays the transmitted quiz content to the user. The user answers the displayed quiz and inputs the answer data into the terminal. The input is the user's quiz answer, and the output is the answer data input into the terminal.

[2850] Step 5:

[2851] The device sends the user's answer data to the server. The server analyzes the received answer data, determines whether the answer is correct or incorrect, and generates feedback. Data analysis includes the process of comparing it with the correct answer data to determine whether the user's choice is correct. The input is the user's answer data, and the output is feedback data.

[2852] Step 6:

[2853] The server sends the generated feedback data to the terminal, and the terminal displays the feedback to the user. The input is the generated feedback, and the output is the feedback displayed to the user.

[2854] Step 7:

[2855] When a user inputs a question or command, the device sends it to the server and simultaneously requests emotion recognition from the emotion engine. The input is the user's question or command, and the output is emotion recognition request data sent to the emotion engine.

[2856] Step 8:

[2857] The emotion engine analyzes the user's input data (text, facial expressions, tone of voice, etc.) and determines the user's emotional state. An emotion recognition model (e.g., a model using Keras) is used for data analysis. The input is the data sent to the emotion engine, and the output is the determined emotional state.

[2858] Step 9:

[2859] The server receives the emotion analysis results from the emotion engine and adjusts the information and feedback it provides based on those results. If anxiety is detected, adjustments are made, such as adding step-by-step guides or encouraging messages. The input is the emotion analysis results, and the output is the adjusted feedback data.

[2860] Step 10:

[2861] The server sends the adjusted information or feedback to the device, which then displays it to the user. The input is the adjusted data, and the output is the adjusted information or feedback displayed to the user.

[2862] 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.

[2863] 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.

[2864] 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.

[2865] [Fourth embodiment]

[2866] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2867] 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.

[2868] 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).

[2869] 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.

[2870] 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.

[2871] 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).

[2872] 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. 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.

[2873] 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.

[2874] 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.

[2875] 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.

[2876] 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.

[2877] 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.

[2878] 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."

[2879] This invention is a system that allows beginners to intermediate investors to efficiently learn about investment information and support their actual investment activities. This system is mainly comprised of users, servers, and terminals, and operates smoothly through the interaction of these elements.

[2880] A natural language description of the program's operation

[2881] 1. Support for understanding the basics of investing

[2882] User: Launches the application and enters a request: "I want to learn the basics of investing."

[2883] Terminal: Sends the user's request to the server.

[2884] Server: Generates basic information about investments (e.g., definition of investment, stocks, bonds, etc.) and also creates interactive learning content in the form of quizzes.

[2885] Server: Sends the generated information and quiz content to the device.

[2886] Terminal: Displays the submitted information and quiz content to the user.

[2887] User: Answers the quiz and sends the answers to the device.

[2888] Server: Collects user answers, analyzes correct and incorrect answers, generates feedback, and sends it to the device.

[2889] Terminal: Display feedback to the user.

[2890] 2. Discussion Consulting (1) How to Start Investing

[2891] User: Enter a question about opening a brokerage account.

[2892] Terminal: Sends a question to the server.

[2893] Server: Searches for and aggregates the necessary information about opening a brokerage account (e.g., required documents, procedural steps, and a list of reputable brokerage firms) in a concise format.

[2894] Server: Sends the generated information to the terminal.

[2895] Terminal: displays information to the user.

[2896] User: Review the information and enter any additional questions.

[2897] Terminal: Sends a follow-up question to the server.

[2898] Server: Aggregates information from additional questions, generates answers, and sends them to the device.

[2899] Terminal: Display the answer to the user.

[2900] 3. Discussion Consulting (2) Market and Company Analysis

[2901] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[2902] Terminal: Sends the request to the server.

[2903] Server: Collects and summarizes company public information (e.g., earnings reports, press releases), stock charts, and related press coverage.

[2904] Server: Generates a company analysis report based on the summarized information and sends it to the terminal.

[2905] Terminal: Display company analysis reports to the user.

[2906] User: Review the analysis report and enter any additional questions.

[2907] Terminal: Sends a follow-up question to the server.

[2908] Server: Collects information again for any additional questions, generates answers, and sends them to the device.

[2909] Terminal: Display the answer to the user.

[2910] 4. Investment simulation in a virtual environment

[2911] User: Requests an investment simulation (e.g., "What would happen if I invested $1,000 for three years?").

[2912] Terminal: Sends the request to the server.

[2913] Server: Sets up a virtual investment environment based on user input data (investment amount, investment period, etc.).

[2914] Server: Runs a double-speed simulation in the configured virtual environment and generates results (e.g., if held for three years at an annual interest rate of 5%, the total amount will be approximately 115,700 yen).

[2915] Server: Sends the simulation results to the device.

[2916] Terminal: Displays the results to the user.

[2917] This system automatically generates and manages the information provided at each phase, allowing users to intuitively acquire investment knowledge and prepare for actual investment actions. Furthermore, virtual investment simulations allow users to understand risks before actually starting an investment and deepen their knowledge for safe investments.

[2918] The processing flow will be explained below.

[2919] Support for understanding the basics of investing

[2920] Step 1:

[2921] User: Launches the application and enters a request: "I want to learn the basics of investing."

[2922] Step 2:

[2923] Terminal: Sends the user's request to the server.

[2924] Step 3:

[2925] Server: Retrieves basic investment information (e.g., definition of investment, stocks, bonds, etc.) from a database and generates interactive learning content in the form of quizzes.

[2926] Step 4:

[2927] Server: Sends the generated basic information and quiz content to the device.

[2928] Step 5:

[2929] Terminal: Displays the submitted basic information and quiz content to the user.

[2930] Step 6:

[2931] User: Takes a quiz and enters the answer into the device.

[2932] Step 7:

[2933] Terminal: Sends the user's answer to the server.

[2934] Step 8:

[2935] Server: Analyzes the user's quiz answers, determines whether they are correct or incorrect, and generates feedback.

[2936] Step 9:

[2937] Server: Sends feedback to the device.

[2938] Step 10:

[2939] Terminal: Display feedback to the user.

[2940] Consulting (1) How to get started with investing

[2941] Step 1:

[2942] User: Enter a question about opening a brokerage account.

[2943] Step 2:

[2944] Terminal: Sends a question to the server.

[2945] Step 3:

[2946] Server: Searches and aggregates necessary information for opening a securities account (e.g., required documents, procedural steps, list of recommended securities firms).

[2947] Step 4:

[2948] Server: Sends the aggregated information to the device.

[2949] Step 5:

[2950] Terminal: displays information to the user.

[2951] Step 6:

[2952] User: Review the information and re-enter any additional questions.

[2953] Step 7:

[2954] Terminal: Sends a follow-up question to the server.

[2955] Step 8:

[2956] Server: Re-aggregates information and generates answers for additional questions.

[2957] Step 9:

[2958] Server: Sends the generated answer to the device.

[2959] Step 10:

[2960] Terminal: Display the answer to the user.

[2961] Discussion Consulting (2) Market and Company Analysis

[2962] Step 1:

[2963] User: Requests an analysis of a specific company (e.g., "Tell me how company X has performed recently").

[2964] Step 2:

[2965] Terminal: Sends the request to the server.

[2966] Step 3:

[2967] Server: Collects public company information (e.g., ear...

Claims

1. means for receiving basic investment questions from users; means for generating basic information on appropriate investments in response to the question and presenting the information to the user; means for generating and displaying interactive learning content in the form of quizzes to users; means for receiving the user's responses to the quiz and analyzing the responses to generate feedback; means for presenting said feedback to a user; A system including:

2. means for receiving inquiries from users regarding how to open a securities account; a means for aggregating information on opening an appropriate securities account in response to the question and presenting the information to the user; a means for re-aggregating information and generating answers to additional questions from the user; means for presenting the answer to a user; The system of claim 1 , comprising:

3. means for receiving a question from a user regarding company analysis; A means for collecting and summarizing public company information, stock price charts, and related press reports in response to said queries; means for generating a company analysis report based on the summarized information; means for presenting the company analysis report to a user; a means for collecting information again and generating answers to additional questions from the user; means for presenting the answer to a user; The system of claim 1 , comprising:

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