system

Abstract

We provide the system. [Solution] Information provision means using knowledge graph technology, A query mechanism for generating queries in a knowledge graph based on user questions and retrieving corresponding information from the knowledge graph, A means of providing acquired information to the user via a chat interface, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, one of the problems faced by novice entrepreneurs is the difficulty of obtaining rapid and accurate information. At present, due to the lack of expertise and the inability to obtain appropriate advice, the success rate of business often decreases. In addition, knowledge sharing among users is not sufficiently carried out, and useful advice from experienced entrepreneurs is not utilized. In order to solve such problems, there is a need for a system that promotes efficient information provision and knowledge sharing among users using knowledge graph technology.

Means for Solving the Problems

[0005] The present invention provides a system comprising: an information provision means using knowledge graph technology; an inquiry means for generating queries in the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; and a presentation means for providing the obtained information to the user via a chat interface. Furthermore, the above-mentioned problems can be solved by further providing: a storage means for saving answers to questions from other users in a database and adding the answers to the knowledge graph; an advertisement presentation means for selecting highly relevant advertisements based on the user's profile information and the context of the question and displaying the advertisements in the chat interface; an authentication means for saving user authentication information in a database, generating an initial authentication token and sending it to the user; and a sharing means for presenting answers to questions from other users for knowledge sharing among users.

[0006] "Knowledge graph technology" is a technique that graphically represents the relationships between data, enabling efficient information retrieval and inference.

[0007] "Information provision means" refers to methods and devices for providing users with necessary information.

[0008] A "user question" is the content of an inquiry entered by the user, and it serves as a trigger for providing information.

[0009] "Generating queries" means creating search commands for databases and knowledge graphs based on user questions.

[0010] A "query tool" is a method or device for generating appropriate queries in response to a user's question and executing those queries against a knowledge graph.

[0011] A "chat interface" is a screen or application that allows users and systems to exchange information in a conversational format.

[0012] "Presentation means" refers to methods or devices for displaying acquired information to the user.

[0013] "Saving responses to a database" means storing user-entered responses in a storage device so they can be used later.

[0014] "Storage means" refers to methods or devices for storing data in a database.

[0015] "Advertising display means" refers to methods or devices for displaying advertisements selected based on the user's profile information and the content of their questions.

[0016] "Authentication means" refers to methods or devices used to verify a user's authentication information and confirm that the user is a legitimate user.

[0017] "Sharing methods" refer to methods or devices for sharing information and knowledge among users. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Further, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] Patent Specification

[0040] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[0041] User registration and authentication system

[0042] 1. User registration:

[0043] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0044] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0045] Question submission and knowledge graph reference

[0046] 1. Enter and submit your question:

[0047] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0048] Server: Receives a question and generates a query against the knowledge graph. Executes the generated query against the knowledge graph and sends the information obtained from the knowledge graph to the terminal in JSON format.

[0049] Terminal: Displays received information within the chat interface and provides responses to the user.

[0050] Knowledge sharing among users

[0051] 1. Question and answer exchange:

[0052] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[0053] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[0054] Ad display processing

[0055] 1. Selection and display of relevant advertisements:

[0056] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0057] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[0058] Specific example:

[0059] 1. Example 1: User registration and authentication:

[0060] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[0061] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0062] 2. Example 2: Posting and answering questions:

[0063] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[0064] Terminal: Sends the question to the server.

[0065] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[0066] Terminal: Displays received responses within the chat interface.

[0067] User knowledge sharing and ad display

[0068] 1. Example 3: Answering another user's question:

[0069] User A: Asks in the chat window, "Which marketing tool do you recommend?"

[0070] Terminal: Sends the question to the server and displays it to other users.

[0071] User B: Based on their own experience, they recommend HubSpot.

[0072] Terminal: Submit your answer and display it to other users.

[0073] Server: Saves the answer to the database and adds it to the knowledge graph.

[0074] 2. Example 4: Displaying related ads:

[0075] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[0076] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0077] User: Views the displayed advertisement.

[0078] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[0079] The following describes the processing flow.

[0080] User registration and authentication system

[0081] Step 1:

[0082] Terminal: Displays a form for the user to enter their name, email address, and password.

[0083] Step 2:

[0084] User: Enter your name, email address, and password, then click the "Register" button.

[0085] Step 3:

[0086] Terminal: Sends the entered data to the server.

[0087] Step 4:

[0088] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[0089] Step 5:

[0090] User: Your account will be activated by receiving an email and clicking the verification link.

[0091] Question submission and knowledge graph reference

[0092] Step 1:

[0093] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[0094] Step 2:

[0095] User: Enter your question and click the "Submit" button.

[0096] Step 3:

[0097] Terminal: Sends the question to the server.

[0098] Step 4:

[0099] Server: Analyzes question data and generates queries for the knowledge graph.

[0100] Step 5:

[0101] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[0102] Step 6:

[0103] Server: Sends the retrieved information to the terminal in JSON format.

[0104] Step 7:

[0105] Terminal: Displays received information within the chat interface.

[0106] Step 8:

[0107] User: Check the answer in the chat interface.

[0108] Knowledge sharing among users

[0109] Step 1:

[0110] Terminal: Displays questions from other users in the chat interface.

[0111] Step 2:

[0112] User: View other users' questions and enter answers based on your own knowledge.

[0113] Step 3:

[0114] User: Enter your answer and click the "Submit" button.

[0115] Step 4:

[0116] Terminal: Sends the entered response to the server.

[0117] Step 5:

[0118] Server: Saves received responses to the database and adds them to the knowledge graph.

[0119] Step 6:

[0120] Server: Sends saved answers to the terminal so that other users can also see them.

[0121] Step 7:

[0122] Terminal: Displays new replies in other users' chat interfaces.

[0123] Ad display processing

[0124] Step 1:

[0125] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0126] Step 2:

[0127] Server: Sends selected advertising data to the terminal in JSON format.

[0128] Step 3:

[0129] Device: Displays received advertisements in a specific location within the chat interface.

[0130] Step 4:

[0131] User: Views advertisements in a chat interface.

[0132] (Example 1)

[0133] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0134] There is a need to provide a platform where novice entrepreneurs can efficiently acquire information and share knowledge among users, as well as to appropriately display advertisements tailored to users' interests. However, it has been difficult to effectively achieve this using conventional methods.

[0135] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0136] In this invention, the server includes: an information provision means using knowledge graph technology; an inquiry means for generating queries to the knowledge graph based on user questions and retrieving corresponding information from the knowledge graph; a presentation means for providing the retrieved information to the user via a chat interface; a storage means for saving user-inputted information to a database; and an authentication means for generating an initial authentication token for the user and sending it via email. This enables novice entrepreneurs to easily and quickly obtain necessary information and facilitates the sharing of specific and useful knowledge among users. Furthermore, the effectiveness of advertisements can be maximized by displaying advertisements tailored to the user's interests.

[0137] "Knowledge graph technology" is a technique that semantically links and represents large amounts of data, enabling users to understand the relationships between those data points.

[0138] "Information provision means" refers to devices or systems that provide users with the information they seek.

[0139] A "query" is a command that attempts to inquire about information from a data repository, such as a database or knowledge graph.

[0140] A "query tool" is a device or system that generates queries based on user questions and retrieves information from databases or knowledge graphs.

[0141] A "chat interface" is a user interface that allows users to communicate in a text-based, conversational format.

[0142] "Presentation means" refers to a device or system for displaying acquired information to the user.

[0143] "Storage means" refers to devices or systems that store data entered by users or information acquired by the system.

[0144] "Authentication means" refers to devices or systems used to verify the identity of a user during registration.

[0145] An "initial authentication token" is a unique identifier used when a user logs in for the first time, and is generated to assist in the authentication process.

[0146] "Profile information" refers to a collection of personal data, such as a user's basic information, interests, and preferences.

[0147] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[0148] User registration and authentication system

[0149] User registration:

[0150] Terminal: Displays a form for the user to enter their name, email address, and password. This form is built using HTML and JavaScript. When the user clicks the "Register" button, the terminal sends that information to the server in JSON format.

[0151] Server: Uses a Java-based Spring Boot framework to receive user information. After validating the received information, it saves it to a MySQL database. If the save is successful, it generates a JWT (JSON Web Token) and sends it to the user's email address via an SMTP server.

[0152] Specific example:

[0153] Terminal: The user enters the name "Sato Ichiro", email address "ichiro@example.com", and password "password123", then clicks the "Register" button.

[0154] Server: Receives input data and saves it to the database. It also generates an initial authentication token and sends it to "ichiro@example.com".

[0155] Question submission and knowledge graph reference

[0156] Enter and submit your question:

[0157] Terminal: Provides a chat interface built using React, allowing users to type questions. When a user types a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0158] Server: Uses the Spring Boot framework to parse received questions and generates queries against the knowledge graph using SPARQL or Cypher. Executes the generated queries and sends the retrieved information to the terminal in JSON format.

[0159] Specific example:

[0160] User: Type "Please teach me how to create a business model" into the chat window and click the "Send" button.

[0161] Terminal: Sends the question to the server.

[0162] Server: Queries the knowledge graph to retrieve information about "how to create a business model" and responds to the user.

[0163] Terminal: Displays received responses within the chat interface.

[0164] Knowledge sharing among users

[0165] Question and answer exchange:

[0166] Terminal: Displays questions from other users in the chat interface. For example, it can display questions in real time using Polling or WebSocket.

[0167] User: Look at other users' questions, enter an answer based on your own experience, and click the "Submit" button.

[0168] Server: Received answers are saved to a MySQL database and then added to the knowledge graph.

[0169] Specific example:

[0170] User A: Asks in the chat window, "What are some recommended marketing tools?"

[0171] Terminal: Sends the question to the server and displays it to other users.

[0172] User B: Based on their own experience, they answer, "SEO tools are useful."

[0173] Terminal: Submit your answer and display it to other users.

[0174] Server: Saves the answer to the database and adds it to the knowledge graph.

[0175] Ad display processing

[0176] Selecting and displaying relevant advertisements:

[0177] Server: Analyzes user profile information and question content to select highly relevant advertisements. For example, it uses natural language processing (NLP) techniques to analyze question content.

[0178] Device: The selected advertisement is displayed in a specific location within the chat interface. The device performs rendering to display the advertisement data.

[0179] Specific example:

[0180] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[0181] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0182] User: Views the displayed advertisement.

[0183] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[0184] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0185] Step 1:

[0186] The user enters their name, email address, and password into an input form. For example, the user enters information into a form built with HTML and JavaScript on their device. The input is converted into JSON in the following format.

[0187] input:{

[0188] "Name": "Ichiro Sato",

[0189] "Email address": "ichiro@example.com",

[0190] "Password": "password123"

[0191] }

[0192] Output: User information in JSON format

[0193] Step 2:

[0194] When the device clicks the "Register" button, it sends this JSON-formatted user information to the server. Specifically, it uses JavaScript to send this data to the server via the HTTPS protocol.

[0195] Input: User information in JSON format

[0196] Output: HTTP request to the server

[0197] Step 3:

[0198] The server receives user information using the Spring Boot framework and performs validation. For example, it checks the validity of the email address and the strength of the password.

[0199] Input: Received user information

[0200] Output: Validation result (success or error)

[0201] Step 4:

[0202] After successful validation, the server saves the user information to the MySQL database. Transactions are managed during this process to verify the success or failure of the save operation.

[0203] Input: User information that passed validation

[0204] Output: Result of saving to the database (success or error)

[0205] Step 5:

[0206] If saving is successful, the server generates a JWT (JSON Web Token) for initial authentication. This token is associated with the user's email address.

[0207] Input: Confirmation of successful save operation

[0208] Output: Generated JWT

[0209] Step 6:

[0210] A confirmation email containing the generated JWT is sent to the user's email address. The email is sent using an SMTP server, and the success or failure of the transmission is recorded.

[0211] Input: JWT and user's email address

[0212] Output: Confirmation of sent emails

[0213] Step 7:

[0214] The user enters a question in the system's chat interface. The interface, built using React, allows the user to enter a question and click the "Send" button.

[0215] Input: User's question (e.g., "How do I create a business model?")

[0216] Output: Question data in JSON format

[0217] Step 8:

[0218] The device sends this JSON-formatted question data to the server. It sends the data via the HTTPS protocol using JavaScript.

[0219] Input: Question data in JSON format

[0220] Output: HTTP request to the server

[0221] Step 9:

[0222] The server analyzes the received question data and generates SPARQL or Cypher queries. These generated queries are then executed against the knowledge graph.

[0223] Input: Received question data

[0224] Output: The generated query and its execution result

[0225] Step 10:

[0226] The retrieved information is sent back to the terminal in JSON format. The server formats the retrieved information and sends it as an HTTP response.

[0227] Input: Execution results from Knowledge Graph

[0228] Output: Response data in JSON format

[0229] Step 11:

[0230] The device receives response data in JSON format and displays it within the chat interface. The React component parses the received data and displays it in a user-friendly format.

[0231] Input: Response data in JSON format

[0232] Output: Answer displayed on the interface

[0233] Step 12:

[0234] This feature allows users to submit answers to questions from other users. The chat interface displays other users' questions, and users can enter their answers and click the "Submit" button.

[0235] Input: Questions and answers from other users

[0236] Output: Response data in JSON format

[0237] Step 13:

[0238] The server stores the received response data in a database and then adds it to the knowledge graph. This response data can be reused in the future as information for other users' questions.

[0239] Input: Received response data

[0240] Output: Results saved to the database and knowledge graph

[0241] Step 14:

[0242] The system selects highly relevant advertisements based on the user's profile information and the content of their questions. Natural language processing (NLP) techniques are used to analyze the questions.

[0243] Input: User profile information and questions

[0244] Output: Selected ad data

[0245] Step 15:

[0246] Selected advertising data is displayed in a specific location within the chat interface. The device receives the advertising data and displays it in a location where the user can view it.

[0247] Input: Selected ad data

[0248] Output: Advertisements displayed on the interface

[0249] The above outlines the specific processing steps of the system. This system allows novice entrepreneurs to efficiently acquire information, promotes knowledge sharing among users, and displays advertisements tailored to their interests.

[0250] (Application Example 1)

[0251] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0252] Traditional information systems suffer from problems such as delayed support and inaccurate information provided when users submit questions. Furthermore, knowledge sharing among users is inefficient, often resulting in biased or incomplete information. Additionally, there are limitations to the means of delivering optimal advertisements to users. There is a need to develop a system that solves these problems, providing rapid and accurate information and knowledge sharing to novice entrepreneurs, and presenting appropriate advertisements.

[0253] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0254] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; advertisement presentation means for selecting highly relevant advertisements based on the content of the question and displaying the advertisements on the chat interface; storage means for saving the user's questions and answers, adding them to the knowledge graph, and displaying them to other users; and execution means as an application that operates on smartphones, smart glasses, and head-mounted displays. As a result, users can not only receive information quickly and accurately, but also efficiently share knowledge with other users and view highly relevant advertisements in a timely manner.

[0255] "Knowledge graph technology" is a technique that visualizes information entities and their interrelationships, and presents relevant information in response to user questions.

[0256] "Information provision means" refers to a function that uses a knowledge graph to provide users with the necessary information.

[0257] A "querying method" is a function that executes queries against the knowledge graph based on the user's question and retrieves the results.

[0258] "Presentation method" refers to a function that provides acquired information in a format that users can view, specifically by displaying it through a chat interface.

[0259] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's question and displays them in the chat interface.

[0260] The "storage method" refers to a function that saves user questions and answers to a database, adds them to a knowledge graph, and displays them to other users.

[0261] "Execution means" refers to the function that allows the system to run on a device such as a smartphone, smart glasses, or head-mounted display.

[0262] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. This system is implemented with the following configuration.

[0263] User registration and authentication system

[0264] User Registration

[0265] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0266] Server: Receives user information and saves it to a database (such as MongoDB). If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0267] Specific example

[0268] Enter the following information: Username "Yamada Taro", email address "taro@example.com", and password "password123", then click the "Register" button.

[0269] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0270] Question submission and knowledge graph reference

[0271] Enter and submit your question

[0272] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0273] Server: Receives a question, generates and executes a query for the knowledge graph (e.g., Google Knowledge Graph API). Sends the information retrieved from the knowledge graph to the terminal in JSON format.

[0274] Terminal: Displays received information within the chat interface and provides responses to the user.

[0275] Specific example

[0276] User: Type "Please teach me how to write a business plan" into the chat interface and click the "Send" button.

[0277] Server: Queries the knowledge graph to retrieve information about "how to write a business plan" and responds to the user.

[0278] Terminal: Displays received responses within the chat interface.

[0279] Knowledge sharing among users

[0280] Question and Answer Interaction

[0281] Terminal: Display questions from other users on the chat interface. Users can view the questions from other users and input and send answers based on their own experiences and knowledge.

[0282] Server: Save the received answers to the database and add them to the knowledge graph. Make the saved answers visible to other users as well.

[0283] Specific Example

[0284] User A: Ask the question "Which marketing tool is recommended?" on the chat interface.

[0285] Terminal: Send the question to the server and display it to other users.

[0286] User B: Answer "HubSpot is recommended" based on their own experience.

[0287] Terminal: Send the answer and display it to other users.

[0288] Server: Save the answer to the database and add it to the knowledge graph.

[0289] Advertisement Display Processing

[0290] Selection and Display of Relevant Advertisements

[0291] Server: Analyze the user's profile information and question content to select highly relevant advertisements.

[0292] Terminal: Display the selected advertisements at a specific position in the chat interface. Users can view the advertisements in the chat interface.

[0293] Specific Example

[0294] Server: Based on the user's questions regarding "marketing tools", select relevant advertisements.

[0295] Terminal: Display the selected advertisement at a specific position in the chat interface.

[0296] User: View the displayed advertisement.

[0297] Examples of prompt sentences

[0298] "Methods of raising funds when starting a business"

[0299] "Common methods of raising funds available when starting a business include the following: 1. Funding provided by angel investors; 2. Crowdfunding; 3. Venture capital, etc."

[0300] Through the above system, users can receive quick and accurate information, efficiently share knowledge with other users, and view relevant advertisements in a timely manner.

[0301] The flow of specific processing in Application Example 1 will be described using Figure 12. <s

[0302] Step 1:

[0303] The user enters their name, email address, and password on the terminal and clicks the "Register" button.

[0304] Input: Name, email address, password

[0305] Output: User information is sent to the server

[0306] Action: The user enters information in the form and clicks the button

[0307] Step 2:

[0308] The server stores the received user information in a database, generates an initial authentication token, and sends it to the user via email.

[0309] Input: User information (name, email address, password)

[0310] Output: User information stored in the database, generated authentication token

[0311] Operation: The server saves data to a database and generates a token, then uses an email server to send the token.

[0312] Step 3:

[0313] The user enters a question in the chat interface and clicks the "Send" button.

[0314] Input: Question content

[0315] Output: The question content is sent to the server.

[0316] Operation: The user enters a question into the chat interface and clicks a button.

[0317] Step 4:

[0318] The server generates and executes queries in the knowledge graph based on the questions it receives.

[0319] Input: Question content

[0320] Output: Answer data from the knowledge graph

[0321] Operation: The server processes the question, queries the Knowledge Graph API, and retrieves the answer.

[0322] Step 5:

[0323] The device displays the answers received from the knowledge graph in the chat interface.

[0324] Input: Response data from Knowledge Graph

[0325] Output: Answer displayed on the user screen

[0326] Operation: The device displays the received response on the chat interface.

[0327] Step 6:

[0328] A user enters an answer to another user's question and clicks the "Submit" button.

[0329] Input: Answer content

[0330] Output: The response content is sent to the server.

[0331] Operation: Users view other users' questions, enter answers based on their own knowledge and experience, and click the submit button.

[0332] Step 7:

[0333] The server saves the received responses to the database and adds them to the knowledge graph.

[0334] Input: Answer content

[0335] Output: Answers stored in the database, information added to the knowledge graph.

[0336] Operation: The server saves the answers to the database and adds the information to the knowledge graph.

[0337] Step 8:

[0338] The server analyzes the user's profile information and questions to select highly relevant advertisements.

[0339] Input: Profile information, Question content

[0340] Output: Selected ad data

[0341] Operation: The server analyzes user information and questions, and selects the most suitable advertisement from the advertising database.

[0342] Step 9:

[0343] The system displays selected advertisements in the chat interface.

[0344] Input: Selected ad data

[0345] Output: Advertisements displayed in the chat interface

[0346] Operation: Displays the advertising data received by the device on the chat interface, making it viewable by the user.

[0347] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0348] Patent Specification

[0349] The system of this invention provides information using knowledge graph technology and promotes knowledge sharing among users. Furthermore, by combining it with an emotion engine that recognizes user emotions, it achieves more personalized information delivery and an improved user experience. The specific processing of the program of this system is described below in natural language.

[0350] User registration and authentication system

[0351] 1. User registration:

[0352] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0353] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0354] Question submission and knowledge graph reference

[0355] 1. Enter and submit your question:

[0356] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[0357] User: Enter your question and click the "Submit" button.

[0358] Terminal: Sends the question to the server.

[0359] 1. Generating queries to the knowledge graph:

[0360] Server: Analyzes question data and generates queries for the knowledge graph. Executes the generated queries on the knowledge graph and retrieves appropriate information from it.

[0361] Server: Sends the retrieved information to the terminal in JSON format.

[0362] Terminal: Displays received information within the chat interface and provides responses to the user.

[0363] Knowledge sharing among users

[0364] 1. Question and answer exchange:

[0365] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[0366] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[0367] Ad display processing

[0368] 1. Selection and display of relevant advertisements:

[0369] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0370] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0371] User: Advertisements can be viewed through the chat interface.

[0372] Implementation of an emotion engine

[0373] 1. Emotion recognition and information provision:

[0374] Emotion Engine: Analyzes the text of questions and messages entered by the user to recognize the user's emotions (e.g., joy, sadness, anger, etc.).

[0375] Server: Adjusts the tone and content of information based on the perceived emotions of the user. For example, if the server perceives that the user is in distress, it provides additional support.

[0376] 1. Adjusting responses based on emotions:

[0377] Server: Uses templates and guidelines to adjust the tone and content of responses according to the user's emotions. Based on the user's emotions recognized by the emotion engine, it generates responses in an appropriate tone.

[0378] Terminal: Displays the adjusted response within the chat interface.

[0379] 1. Display of emotion indicators:

[0380] Terminal: Visualizes the user's emotions as recognized by the emotion engine and displays them as emotion indicators on the chat interface. This allows users to see how their emotions are being perceived.

[0381] Specific example:

[0382] 1. Example 1: User registration and authentication:

[0383] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[0384] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0385] 2. Example 2: Posting and answering questions:

[0386] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[0387] Terminal: Sends the question to the server.

[0388] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[0389] Terminal: Displays received responses within the chat interface.

[0390] 3. Example 3: Recognizing user emotions:

[0391] User: Looking confused, types, "This process is too difficult; I don't understand it."

[0392] Emotion Engine: Recognizes the user's "confusion" from the message.

[0393] Server: Generates answers with additional support information and a friendly tone.

[0394] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[0395] As described above, the system of the present invention combines knowledge graph technology and an emotion engine to provide users with rapid and accurate information, as well as personalized services to improve the user experience.

[0396] The following describes the processing flow.

[0397] User registration and authentication system

[0398] Step 1:

[0399] Terminal: Displays a form for the user to enter their name, email address, and password.

[0400] Step 2:

[0401] User: Enter your name, email address, and password, then click the "Register" button.

[0402] Step 3:

[0403] Terminal: Sends the entered data to the server.

[0404] Step 4:

[0405] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[0406] Step 5:

[0407] User: Your account will be activated by receiving an email and clicking the verification link.

[0408] Question submission and knowledge graph reference

[0409] Step 1:

[0410] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[0411] Step 2:

[0412] User: Enter your question and click the "Submit" button.

[0413] Step 3:

[0414] Terminal: Sends the question to the server.

[0415] Step 4:

[0416] Server: Analyzes question data and generates queries for the knowledge graph.

[0417] Step 5:

[0418] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[0419] Step 6:

[0420] Server: Sends the retrieved information to the terminal in JSON format.

[0421] Step 7:

[0422] Terminal: Displays received information within the chat interface.

[0423] Step 8:

[0424] User: Check the answer in the chat interface.

[0425] Knowledge sharing among users

[0426] Step 1:

[0427] Terminal: Displays questions from other users in the chat interface.

[0428] Step 2:

[0429] User: View other users' questions and enter answers based on your own knowledge.

[0430] Step 3:

[0431] User: Enter your answer and click the "Submit" button.

[0432] Step 4:

[0433] Terminal: Sends the entered response to the server.

[0434] Step 5:

[0435] Server: Saves received responses to the database and adds them to the knowledge graph.

[0436] Step 6:

[0437] Server: Sends saved answers to the terminal so that other users can also see them.

[0438] Step 7:

[0439] Terminal: Displays new replies in other users' chat interfaces.

[0440] Ad display processing

[0441] Step 1:

[0442] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0443] Step 2:

[0444] Server: Sends selected advertising data to the terminal in JSON format.

[0445] Step 3:

[0446] Device: Displays received advertisements in a specific location within the chat interface.

[0447] Step 4:

[0448] User: Views advertisements in a chat interface.

[0449] Implementation of an emotion engine

[0450] Step 1:

[0451] Terminal: Sends the message entered by the user to the emotion engine.

[0452] Step 2:

[0453] Emotion Engine: Analyzes user input messages and recognizes emotions (e.g., joy, confusion, anger).

[0454] Step 3:

[0455] Server: Based on emotional information received from the emotion engine, adjusts the tone of the information and responses provided.

[0456] Step 4:

[0457] Terminal: Displays the adjusted response within the chat interface.

[0458] Step 5:

[0459] Terminal: Visualizes the emotions of recognized users and displays them as emotion indicators on the chat interface.

[0460] Step 6:

[0461] User: Check the displayed emotion indicator to see how your emotions are being perceived.

[0462] (Example 2)

[0463] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0464] Information provision systems using knowledge graph technology are required not only to provide answers to questions, but also to provide personalized information based on the user's emotions. However, conventional systems lack the functionality to recognize and respond to user emotions, resulting in a lack of improvement in the user experience. Furthermore, there is a need for a means to efficiently display highly relevant advertisements while promoting knowledge sharing among users. This invention aims to solve these problems.

[0465] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0466] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for analyzing text entered by the user and recognizing emotions; and emotion adaptation means for adjusting responses based on recognized emotions and providing personalized information. This enables not only quick and accurate answers to user questions but also personalized information provision that takes user emotions into consideration. Furthermore, it facilitates knowledge sharing among users and enables the efficient display of highly relevant advertisements.

[0467] A "knowledge graph" is a structured graph of knowledge that shows the relationships between data, and it is a technology that systematically organizes information and allows for quick retrieval of information through queries.

[0468] "Information provision means" refers to a part of a system that uses knowledge graph technology to provide users with necessary information.

[0469] A "querying method" is a function that generates queries to the knowledge graph based on the user's question and retrieves corresponding information from the knowledge graph.

[0470] A "presentation means" is a function that provides an interface for displaying acquired information to the user.

[0471] An "emotion recognition tool" is a function that analyzes text entered by the user to recognize the user's emotions.

[0472] "Emotional adaptation mechanisms" are functions that adjust responses based on recognized emotions and provide personalized information to users.

[0473] "Storage method" refers to a function that saves answers to questions from other users to a database and adds them to the knowledge graph.

[0474] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[0475] This system combines knowledge graph technology and an emotion engine to provide users with personalized information, promote knowledge sharing among users, and display highly relevant advertisements. The following describes a specific implementation of this system.

[0476] User registration and authentication system

[0477] The terminal displays a form for the user to enter their name, email address, and password. Once the user submits the information, the server receives it and stores it in a database. For example, MySQL or PostgreSQL can be used for the database. Upon successful saving, the server generates an initial authentication token and sends it to the user's email address. This process allows the user to obtain an authentication link and complete the registration.

[0478] Question submission and knowledge graph reference

[0479] The terminal displays a chat interface, allowing the user to enter a question. Once the user enters and submits a question, the terminal sends it to the server. The server parses the question and generates a query against a knowledge graph. Examples of knowledge graphs that can be used include Neo4j and Amazon Neptune. The generated query is executed to retrieve the appropriate information. The retrieved information is sent to the terminal in JSON format, and the terminal displays the information within the chat interface.

[0480] Knowledge sharing among users

[0481] The terminal displays questions from other users, and users can enter and submit their answers. The server saves the received answers to a database and adds them to the knowledge graph. This allows other users to share this information.

[0482] Ad display processing

[0483] The server analyzes the user's profile information and questions to select highly relevant advertisements. These selected advertisements are sent to the user's device and displayed in specific locations within the chat interface. This allows the user to view relevant advertisements.

[0484] Implementation of an emotion engine

[0485] The emotion engine analyzes the text entered by the user and recognizes the user's emotions using natural language processing techniques (such as BERT or GPT-3). Based on the recognized emotions, the server adjusts the tone and content of the information. For example, if the server recognizes that the user is in distress, it provides additional support information and a more helpful tone in its response. The terminal displays the adjusted response and emotion indicator, allowing the user to see how their emotions are being perceived.

[0486] Specific example

[0487] 1. User registration and authentication:

[0488] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[0489] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0490] 2. Posting and answering questions:

[0491] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[0492] Terminal: Sends the question to the server.

[0493] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[0494] Terminal: Displays received responses within the chat interface.

[0495] 3. Recognizing user emotions:

[0496] User: Looking confused, types, "This process is too difficult; I don't understand it."

[0497] Emotion Engine: Recognizes the user's "confusion" from the message.

[0498] Server: Generates answers with additional support information and a friendly tone.

[0499] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[0500] Through the above specific examples, this system can combine knowledge graph technology and an emotion engine to provide users with fast and accurate information, thereby improving the user experience.

[0501] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0502] Step 1:

[0503] Displaying user registration

[0504] The terminal displays an input form for the user to enter their name, email address, and password. The input form includes a "Register" button, which the user clicks to submit the entered data. Input and Output: The input is the name, email address, and password entered by the user, and the output is the transmission of this data to the server.

[0505] Step 2:

[0506] Send user information

[0507] When the user clicks the "Register" button, the terminal sends the entered information (name, email address, password) to the server. Input and Output: Input is the data entered by the user, and output is the data sent to the server.

[0508] Step 3:

[0509] User information storage

[0510] The server receives the submitted user information and stores it in a database. Specifically, it uses MySQL or PostgreSQL as the database. If the storage is successful, the server generates an initial authentication token and sends it to the user's email address. Input and Output: The input is the user's registration information, and the output is the entry stored in the database and the generated authentication token.

[0511] Step 4:

[0512] Sending an authentication token

[0513] The server sends an email containing the generated initial authentication token to the user's email address. This gives the user a link to complete the authentication process. Input and Output: The input is the generated authentication token and the user's email address, and the output is the authentication email sent to the user.

[0514] Step 5:

[0515] Display of the question input screen

[0516] The device displays a chat interface, allowing the user to enter questions using a text box. A "Send" button is also provided. Input and Output: Input is the question entered by the user, and output is the display of the chat interface on the device.

[0517] Step 6:

[0518] Submit a question

[0519] The user enters a question in the text box and clicks the "Submit" button. The terminal sends this to the server. Input and Output: The input is the question entered by the user, and the output is the question data sent to the server.

[0520] Step 7:

[0521] Query generation

[0522] The server parses the submitted question and generates a query for the knowledge graph. Specifically, if the question is "How do I write a business plan?", it will search for data related to "how to write a business plan". Input and Output: The input is the question entered by the user, and the output is the query generated for the knowledge graph.

[0523] Step 8:

[0524] Executing queries on the knowledge graph

[0525] The server executes the generated queries against the knowledge graph and retrieves relevant information. Neo4j and Amazon Neptune are commonly used as the knowledge graph. The retrieved information is structured within the server in JSON format. Input and Output: The input is the generated query, and the output is the information retrieved from the knowledge graph.

[0526] Step 9:

[0527] Submit and display of responses

[0528] The server sends structured information to the terminal in JSON format. The terminal displays the received information within the chat interface and provides answers to the user. Input and Output: The input is information obtained from the knowledge graph, and the output is the answers displayed in the chat interface.

[0529] Step 10:

[0530] Displaying questions from other users

[0531] The terminal displays questions from other users in a chat interface. Users can then type and submit their answers. Input and Output: Input is the question from another user, and output is the displayed question.

[0532] Step 11:

[0533] Enter and submit your response.

[0534] The user enters an answer to another user's question and clicks the "Submit" button. The terminal sends the entered answer to the server. Input and Output: The input is the answer entered by the user, and the output is the answer data sent to the server.

[0535] Step 12:

[0536] Save and share your answers

[0537] The server saves the received responses to the database and adds them to the knowledge graph. This allows other users to access this information. Input and Output: The input is the user's response, and the output is the entries saved in the database and updates to the knowledge graph.

[0538] Step 13:

[0539] Ad selection

[0540] The server analyzes the user's profile information and questions to select highly relevant advertisements. For example, if the question includes "business plan," it will select advertisements for business books. Input and Output: The input is the user's profile information and questions, and the output is the selected advertisement information.

[0541] Step 14:

[0542] Displaying ads

[0543] The device displays selected advertisements in specific locations within the chat interface. This allows users to view relevant advertisements. Input and Output: The input is the selected advertisement information, and the output is the advertisement displayed in the chat interface.

[0544] Step 15:

[0545] Recognition of emotions

[0546] The emotion engine analyzes text entered by the user and recognizes the user's emotions using natural language processing techniques (e.g., BERT and GPT-3). For example, it recognizes confusion from keywords such as "troubled" and "difficult." Input and Output: The input is the user's text, and the output is the recognized emotion information.

[0547] Step 16:

[0548] Coordination of information provision

[0549] The server adjusts the tone and content of information based on the recognized user's emotions. For example, it provides additional support information and a gentler tone of message to a user who is in distress. Input and Output: The input is the recognized emotion information, and the output is the adjusted response.

[0550] Step 17:

[0551] Display of emotion indicator

[0552] The device visualizes the user's emotions, as recognized by the emotion engine, and displays them as emotion indicators on the chat interface. This allows the user to see how their emotions are being perceived. Input and Output: The input is the recognized emotion information, and the output is the displayed emotion indicator.

[0553] (Application Example 2)

[0554] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0555] Traditional information provision systems merely provided information in response to user questions, failing to consider user emotions. This could lead to decreased user satisfaction and trust. Furthermore, the system did not effectively facilitate knowledge sharing among users or present relevant advertisements, limiting the quality of information provided and the effectiveness of advertising.

[0556] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0557] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for recognizing the user's emotions using an emotion engine and adjusting the tone and content of the information based on those emotions; and emotion indicator means for visualizing the results of emotion recognition to the user. This enables personalized information provision, increasing not only user satisfaction but also trust. Furthermore, by saving answers to questions from other users in a database and adding them to the knowledge graph, knowledge sharing among users is promoted. The effectiveness of advertisements can also be enhanced by selecting and displaying highly relevant advertisements based on profile information and the context of the questions.

[0558] "Knowledge graph technology" is a technique that represents data in a graph structure and organizes and displays information using nodes (individual elements of data) and edges (relationships between nodes).

[0559] "Information provision means" refers to systems and functions that provide users with the information they need.

[0560] "Query means" refers to a system or function that generates queries in a knowledge graph based on user questions and retrieves information from that knowledge graph.

[0561] "Presentation means" refers to a system or function for displaying acquired information to the user.

[0562] An "emotion engine" refers to a system or algorithm that analyzes and recognizes a user's emotions from text and audio data.

[0563] "Emotion recognition means" refers to a system or function that uses an emotion engine to recognize a user's emotions and adjusts information based on the results.

[0564] "Emotion indicator means" refers to systems or functions that visualize recognized emotions for the user.

[0565] "Storage method" refers to a system or function for saving answers to questions from other users to a database and adding them to a knowledge graph.

[0566] "Advertising display method" refers to a system or function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[0567] This invention aims to realize a system that provides personalized information to users by utilizing knowledge graph technology and an emotion engine. The necessary hardware and software configuration and each processing step for this purpose will be described.

[0568] Hardware configuration

[0569] Servers: Database server (e.g., MySQL), Application server (e.g., Node.js)

[0570] Client device: Smartphone (iOS / Android)

[0571] Software Configuration

[0572] Data analysis: Python, Knowledge graph (e.g., Neo4j)

[0573] Emotion recognition: Natural language processing libraries (NLP) and AI models (e.g., TensorFlow, Hugging Face)

[0574] Explanation of processing details

[0575] 1. User registration and authentication:

[0576] The user registers by entering their name, email address, and password. The entered data is sent to the server and stored in the database (MySQL). An authentication token is generated and sent to the user via email.

[0577] 2. Question posting and knowledge graph referencing:

[0578] The user submits a question through the chat interface. The server analyzes the question and generates a query for the knowledge graph (Neo4j). Based on the generated query, information is retrieved from the knowledge graph. The retrieved information is sent in JSON format and displayed on the smartphone.

[0579] 3. Knowledge sharing among users:

[0580] Other users' questions and answers are displayed in the chat interface. Users can type and submit their answers. The answers are stored in a database by the server and added to the knowledge graph.

[0581] 4. Emotion recognition and information provision:

[0582] The user's message is sent to an emotion engine (TensorFlow, Hugging Face) and analyzed. The emotion engine recognizes the user's emotions from the sent message, and based on the result, the server generates a response in an appropriate tone. The generated response is then provided to the user.

[0583] 5. Display of emotion indicators:

[0584] Recognized emotions are displayed as emotion indicators in the smartphone's chat interface. This allows users to see how their emotions are being perceived.

[0585] 6. Advertisement display:

[0586] The server analyzes the user's profile information and the context of the question to select the most relevant advertisements. The selected advertisements are then displayed in the chat interface.

[0587] Examples of specific cases and prompt statements

[0588] Specific example:

[0589] 1. Question posted: "Please tell me the latest movie reviews."

[0590] 2. Emotion Recognition: Recognizing the emotion "I was disappointed because the movie reviews were terrible."

[0591] Example of a prompt:

[0592] "The user has asked about the latest movie reviews and expressed disappointment. How should the system respond considering the user's emotional state?"

[0593] Based on these configurations, a system combining a knowledge graph and an emotion engine will provide users with fast and appropriate information and personalized support, resulting in a better user experience.

[0594] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0595] Step 1:

[0596] User registration and authentication

[0597] The user enters their name, email address, and password in the smartphone app and clicks the registration button.

[0598] The terminal sends the entered data to the server.

[0599] The server saves the received data to a database (MySQL) and generates an authentication token. This token is then sent to the user via email.

[0600] Input: Name, email address, password

[0601] Output: Authentication token

[0602] Step 2:

[0603] Question submission and knowledge graph reference

[0604] The user enters their question in the chat interface and clicks the send button.

[0605] The terminal sends the question data to the server.

[0606] The server analyzes the received question and generates a query against the knowledge graph (Neo4j). It executes the generated query and retrieves the necessary information from the knowledge graph. The retrieved information is sent to the terminal in JSON format. The terminal displays the retrieved information in the chat interface.

[0607] Input: User's question text

[0608] Output: Information obtained from the knowledge graph

[0609] Step 3:

[0610] Knowledge sharing among users

[0611] The device displays questions and answers from other users in a chat interface.

[0612] Users enter their answers based on their knowledge and experience and click the submit button.

[0613] The device sends the response data to the server.

[0614] The server saves the received answers to a database and adds them to the knowledge graph. The saved answers are also visible to other users, facilitating knowledge sharing.

[0615] Input: User's response text

[0616] Output: Answers stored in the database, information added to the knowledge graph.

[0617] Step 4:

[0618] Emotion recognition and information provision

[0619] The user types a message in the chat interface and clicks the send button.

[0620] The terminal sends message data to the server.

[0621] The server sends the received messages to the emotion engine (TensorFlow, Hugging Face) for analysis.

[0622] The emotion engine analyzes the user's emotions from the message and returns the results to the server.

[0623] Based on the emotion recognition results, the server generates a response in an appropriate tone, sends it to the terminal, and displays it.

[0624] Input: User's message text

[0625] Output: Emotion recognition results from the emotion engine, adjusted response

[0626] Step 5:

[0627] Display of emotion indicator

[0628] The device displays emotion indicators recognized by the emotion engine on the chat interface. This allows users to see how their emotions are being perceived.

[0629] Input: Sentiment recognition result

[0630] Output: Visual display of emotion indicators

[0631] Step 6:

[0632] Advertisement

[0633] The server analyzes the user's profile information and question data to select highly relevant advertisements.

[0634] Selected advertisements are displayed in the chat interface. Users can view relevant advertisements.

[0635] Input: User profile information, question data

[0636] Output: Advertisements displayed in the chat interface

[0637] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0638] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0639] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0640] [Second Embodiment]

[0641] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0642] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0643] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0644] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0645] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0646] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0647] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0648] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0649] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0650] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0651] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0652] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0653] Patent Specification

[0654] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[0655] User registration and authentication system

[0656] 1. User registration:

[0657] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0658] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0659] Question submission and knowledge graph reference

[0660] 1. Enter and submit your question:

[0661] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0662] Server: Receives a question and generates a query against the knowledge graph. Executes the generated query against the knowledge graph and sends the information obtained from the knowledge graph to the terminal in JSON format.

[0663] Terminal: Displays received information within the chat interface and provides responses to the user.

[0664] Knowledge sharing among users

[0665] 1. Question and answer exchange:

[0666] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[0667] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[0668] Ad display processing

[0669] 1. Selection and display of relevant advertisements:

[0670] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0671] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[0672] Specific example:

[0673] 1. Example 1: User registration and authentication:

[0674] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[0675] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0676] 2. Example 2: Posting and answering questions:

[0677] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[0678] Terminal: Sends the question to the server.

[0679] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[0680] Terminal: Displays received responses within the chat interface.

[0681] User knowledge sharing and ad display

[0682] 1. Example 3: Answering another user's question:

[0683] User A: Asks in the chat window, "Which marketing tool do you recommend?"

[0684] Terminal: Sends the question to the server and displays it to other users.

[0685] User B: Based on their own experience, they recommend HubSpot.

[0686] Terminal: Submit your answer and display it to other users.

[0687] Server: Saves the answer to the database and adds it to the knowledge graph.

[0688] 2. Example 4: Displaying related ads:

[0689] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[0690] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0691] User: Views the displayed advertisement.

[0692] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[0693] The following describes the processing flow.

[0694] User registration and authentication system

[0695] Step 1:

[0696] Terminal: Displays a form for the user to enter their name, email address, and password.

[0697] Step 2:

[0698] User: Enter your name, email address, and password, then click the "Register" button.

[0699] Step 3:

[0700] Terminal: Sends the entered data to the server.

[0701] Step 4:

[0702] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[0703] Step 5:

[0704] User: Your account will be activated by receiving an email and clicking the verification link.

[0705] Question submission and knowledge graph reference

[0706] Step 1:

[0707] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[0708] Step 2:

[0709] User: Enter your question and click the "Submit" button.

[0710] Step 3:

[0711] Terminal: Sends the question to the server.

[0712] Step 4:

[0713] Server: Analyzes question data and generates queries for the knowledge graph.

[0714] Step 5:

[0715] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[0716] Step 6:

[0717] Server: Sends the retrieved information to the terminal in JSON format.

[0718] Step 7:

[0719] Terminal: Displays received information within the chat interface.

[0720] Step 8:

[0721] User: Check the answer in the chat interface.

[0722] Knowledge sharing among users

[0723] Step 1:

[0724] Terminal: Displays questions from other users in the chat interface.

[0725] Step 2:

[0726] User: View other users' questions and enter answers based on your own knowledge.

[0727] Step 3:

[0728] User: Enter your answer and click the "Submit" button.

[0729] Step 4:

[0730] Terminal: Sends the entered response to the server.

[0731] Step 5:

[0732] Server: Saves received responses to the database and adds them to the knowledge graph.

[0733] Step 6:

[0734] Server: Sends saved answers to the terminal so that other users can also see them.

[0735] Step 7:

[0736] Terminal: Displays new replies in other users' chat interfaces.

[0737] Ad display processing

[0738] Step 1:

[0739] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0740] Step 2:

[0741] Server: Sends selected advertising data to the terminal in JSON format.

[0742] Step 3:

[0743] Device: Displays received advertisements in a specific location within the chat interface.

[0744] Step 4:

[0745] User: Views advertisements in a chat interface.

[0746] (Example 1)

[0747] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0748] There is a need to provide a platform where novice entrepreneurs can efficiently acquire information and share knowledge among users, as well as to appropriately display advertisements tailored to users' interests. However, it has been difficult to effectively achieve this using conventional methods.

[0749] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0750] In this invention, the server includes: an information provision means using knowledge graph technology; an inquiry means for generating queries to the knowledge graph based on user questions and retrieving corresponding information from the knowledge graph; a presentation means for providing the retrieved information to the user via a chat interface; a storage means for saving user-inputted information to a database; and an authentication means for generating an initial authentication token for the user and sending it via email. This enables novice entrepreneurs to easily and quickly obtain necessary information and facilitates the sharing of specific and useful knowledge among users. Furthermore, the effectiveness of advertisements can be maximized by displaying advertisements tailored to the user's interests.

[0751] "Knowledge graph technology" is a technique that semantically links and represents large amounts of data, enabling users to understand the relationships between those data points.

[0752] "Information provision means" refers to devices or systems that provide users with the information they seek.

[0753] A "query" is a command that attempts to inquire about information from a data repository, such as a database or knowledge graph.

[0754] A "query tool" is a device or system that generates queries based on user questions and retrieves information from databases or knowledge graphs.

[0755] A "chat interface" is a user interface that allows users to communicate in a text-based, conversational format.

[0756] "Presentation means" refers to a device or system for displaying acquired information to the user.

[0757] "Storage means" refers to devices or systems that store data entered by users or information acquired by the system.

[0758] "Authentication means" refers to devices or systems used to verify the identity of a user during registration.

[0759] An "initial authentication token" is a unique identifier used when a user logs in for the first time, and is generated to assist in the authentication process.

[0760] "Profile information" refers to a collection of personal data, such as a user's basic information, interests, and preferences.

[0761] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[0762] User registration and authentication system

[0763] User registration:

[0764] Terminal: Displays a form for the user to enter their name, email address, and password. This form is built using HTML and JavaScript. When the user clicks the "Register" button, the terminal sends that information to the server in JSON format.

[0765] Server: Uses a Java-based Spring Boot framework to receive user information. After validating the received information, it saves it to a MySQL database. If the save is successful, it generates a JWT (JSON Web Token) and sends it to the user's email address via an SMTP server.

[0766] Specific example:

[0767] Terminal: The user enters the name "Sato Ichiro", email address "ichiro@example.com", and password "password123", then clicks the "Register" button.

[0768] Server: Receives input data and saves it to the database. It also generates an initial authentication token and sends it to "ichiro@example.com".

[0769] Question submission and knowledge graph reference

[0770] Enter and submit your question:

[0771] Terminal: Provides a chat interface built using React, allowing users to type questions. When a user types a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0772] Server: Uses the Spring Boot framework to parse received questions and generates queries against the knowledge graph using SPARQL or Cypher. Executes the generated queries and sends the retrieved information to the terminal in JSON format.

[0773] Specific example:

[0774] User: Type "Please teach me how to create a business model" into the chat window and click the "Send" button.

[0775] Terminal: Sends the question to the server.

[0776] Server: Queries the knowledge graph to retrieve information about "how to create a business model" and responds to the user.

[0777] Terminal: Displays received responses within the chat interface.

[0778] Knowledge sharing among users

[0779] Question and answer exchange:

[0780] Terminal: Displays questions from other users in the chat interface. For example, it can display questions in real time using Polling or WebSocket.

[0781] User: Look at other users' questions, enter an answer based on your own experience, and click the "Submit" button.

[0782] Server: Received answers are saved to a MySQL database and then added to the knowledge graph.

[0783] Specific example:

[0784] User A: Asks in the chat window, "What are some recommended marketing tools?"

[0785] Terminal: Sends the question to the server and displays it to other users.

[0786] User B: Based on their own experience, they answer, "SEO tools are useful."

[0787] Terminal: Submit your answer and display it to other users.

[0788] Server: Saves the answer to the database and adds it to the knowledge graph.

[0789] Ad display processing

[0790] Selecting and displaying relevant advertisements:

[0791] Server: Analyzes user profile information and question content to select highly relevant advertisements. For example, it uses natural language processing (NLP) techniques to analyze question content.

[0792] Device: The selected advertisement is displayed in a specific location within the chat interface. The device performs rendering to display the advertisement data.

[0793] Specific example:

[0794] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[0795] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0796] User: Views the displayed advertisement.

[0797] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[0798] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0799] Step 1:

[0800] The user enters their name, email address, and password into an input form. For example, the user enters information into a form built with HTML and JavaScript on their device. The input is converted into JSON in the following format.

[0801] input:{

[0802] "Name": "Ichiro Sato",

[0803] "Email address": "ichiro@example.com",

[0804] "Password": "password123"

[0805] }

[0806] Output: User information in JSON format

[0807] Step 2:

[0808] When the device clicks the "Register" button, it sends this JSON-formatted user information to the server. Specifically, it uses JavaScript to send this data to the server via the HTTPS protocol.

[0809] Input: User information in JSON format

[0810] Output: HTTP request to the server

[0811] Step 3:

[0812] The server receives user information using the Spring Boot framework and performs validation. For example, it checks the validity of the email address and the strength of the password.

[0813] Input: Received user information

[0814] Output: Validation result (success or error)

[0815] Step 4:

[0816] After successful validation, the server saves the user information to the MySQL database. Transactions are managed during this process to verify the success or failure of the save operation.

[0817] Input: User information that passed validation

[0818] Output: Result of saving to the database (success or error)

[0819] Step 5:

[0820] If saving is successful, the server generates a JWT (JSON Web Token) for initial authentication. This token is associated with the user's email address.

[0821] Input: Confirmation of successful save operation

[0822] Output: Generated JWT

[0823] Step 6:

[0824] A confirmation email containing the generated JWT is sent to the user's email address. The email is sent using an SMTP server, and the success or failure of the transmission is recorded.

[0825] Input: JWT and user's email address

[0826] Output: Confirmation of sent emails

[0827] Step 7:

[0828] The user enters a question in the system's chat interface. The interface, built using React, allows the user to enter a question and click the "Send" button.

[0829] Input: User's question (e.g., "How do I create a business model?")

[0830] Output: Question data in JSON format

[0831] Step 8:

[0832] The device sends this JSON-formatted question data to the server. It sends the data via the HTTPS protocol using JavaScript.

[0833] Input: Question data in JSON format

[0834] Output: HTTP request to the server

[0835] Step 9:

[0836] The server analyzes the received question data and generates SPARQL or Cypher queries. These generated queries are then executed against the knowledge graph.

[0837] Input: Received question data

[0838] Output: The generated query and its execution result

[0839] Step 10:

[0840] The retrieved information is sent back to the terminal in JSON format. The server formats the retrieved information and sends it as an HTTP response.

[0841] Input: Execution results from Knowledge Graph

[0842] Output: Response data in JSON format

[0843] Step 11:

[0844] The device receives response data in JSON format and displays it within the chat interface. The React component parses the received data and displays it in a user-friendly format.

[0845] Input: Response data in JSON format

[0846] Output: Answer displayed on the interface

[0847] Step 12:

[0848] This feature allows users to submit answers to questions from other users. The chat interface displays other users' questions, and users can enter their answers and click the "Submit" button.

[0849] Input: Questions and answers from other users

[0850] Output: Response data in JSON format

[0851] Step 13:

[0852] The server stores the received response data in a database and then adds it to the knowledge graph. This response data can be reused in the future as information for other users' questions.

[0853] Input: Received response data

[0854] Output: Results saved to the database and knowledge graph

[0855] Step 14:

[0856] The system selects highly relevant advertisements based on the user's profile information and the content of their questions. Natural language processing (NLP) techniques are used to analyze the questions.

[0857] Input: User profile information and questions

[0858] Output: Selected ad data

[0859] Step 15:

[0860] Selected advertising data is displayed in a specific location within the chat interface. The device receives the advertising data and displays it in a location where the user can view it.

[0861] Input: Selected ad data

[0862] Output: Advertisements displayed on the interface

[0863] The above outlines the specific processing steps of the system. This system allows novice entrepreneurs to efficiently acquire information, promotes knowledge sharing among users, and displays advertisements tailored to their interests.

[0864] (Application Example 1)

[0865] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0866] Traditional information systems suffer from problems such as delayed support and inaccurate information provided when users submit questions. Furthermore, knowledge sharing among users is inefficient, often resulting in biased or incomplete information. Additionally, there are limitations to the means of delivering optimal advertisements to users. There is a need to develop a system that solves these problems, providing rapid and accurate information and knowledge sharing to novice entrepreneurs, and presenting appropriate advertisements.

[0867] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0868] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; advertisement presentation means for selecting highly relevant advertisements based on the content of the question and displaying the advertisements on the chat interface; storage means for saving the user's questions and answers, adding them to the knowledge graph, and displaying them to other users; and execution means as an application that operates on smartphones, smart glasses, and head-mounted displays. As a result, users can not only receive information quickly and accurately, but also efficiently share knowledge with other users and view highly relevant advertisements in a timely manner.

[0869] "Knowledge graph technology" is a technique that visualizes information entities and their interrelationships, and presents relevant information in response to user questions.

[0870] "Information provision means" refers to a function that uses a knowledge graph to provide users with the necessary information.

[0871] A "querying method" is a function that executes queries against the knowledge graph based on the user's question and retrieves the results.

[0872] "Presentation method" refers to a function that provides acquired information in a format that users can view, specifically by displaying it through a chat interface.

[0873] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's question and displays them in the chat interface.

[0874] The "storage method" refers to a function that saves user questions and answers to a database, adds them to a knowledge graph, and displays them to other users.

[0875] "Execution means" refers to the function that allows the system to run on a device such as a smartphone, smart glasses, or head-mounted display.

[0876] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. This system is implemented with the following configuration.

[0877] User registration and authentication system

[0878] User Registration

[0879] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0880] Server: Receives user information and saves it to a database (such as MongoDB). If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0881] Specific example

[0882] Enter the following information: Username "Yamada Taro", email address "taro@example.com", and password "password123", then click the "Register" button.

[0883] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0884] Question submission and knowledge graph reference

[0885] Enter and submit your question

[0886] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[0887] Server: Receives a question, generates and executes a query for the knowledge graph (e.g., Google Knowledge Graph API). Sends the information retrieved from the knowledge graph to the terminal in JSON format.

[0888] Terminal: Displays received information within the chat interface and provides responses to the user.

[0889] Specific example

[0890] User: Type "Please teach me how to write a business plan" into the chat interface and click the "Send" button.

[0891] Server: Queries the knowledge graph to retrieve information about "how to write a business plan" and responds to the user.

[0892] Terminal: Displays received responses within the chat interface.

[0893] Knowledge sharing among users

[0894] Question and answer exchange

[0895] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[0896] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[0897] Specific example

[0898] User A asks the chat interface, "Which marketing tool do you recommend?"

[0899] Terminal: Sends the question to the server and displays it to other users.

[0900] User B: Based on their own experience, they recommend HubSpot.

[0901] Terminal: Submit your answer and display it to other users.

[0902] Server: Saves the answer to the database and adds it to the knowledge graph.

[0903] Ad display processing

[0904] Selection and display of relevant advertisements

[0905] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0906] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[0907] Specific example

[0908] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[0909] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0910] User: Views the displayed advertisement.

[0911] Example of a prompt

[0912] "Methods of raising funds when starting a business"

[0913] "Common methods of raising funds when starting a business include: 1. Funding from angel investors, 2. Crowdfunding, and 3. Venture capital."

[0914] Through this system, users can receive information quickly and accurately, efficiently share knowledge with other users, and view relevant advertisements in a timely manner.

[0915] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0916] Step 1:

[0917] The user enters their name, email address, and password on their device and clicks the "Register" button.

[0918] Input: Name, email address, password

[0919] Output: User information is sent to the server.

[0920] Action: The user enters information into a form and clicks a button.

[0921] Step 2:

[0922] The server stores the received user information in a database, generates an initial authentication token, and sends it to the user via email.

[0923] Input: User information (name, email address, password)

[0924] Output: User information stored in the database, generated authentication token

[0925] Operation: The server saves data to a database and generates a token, then uses an email server to send the token.

[0926] Step 3:

[0927] The user enters a question in the chat interface and clicks the "Send" button.

[0928] Input: Question content

[0929] Output: The question content is sent to the server.

[0930] Operation: The user enters a question into the chat interface and clicks a button.

[0931] Step 4:

[0932] The server generates and executes queries in the knowledge graph based on the questions it receives.

[0933] Input: Question content

[0934] Output: Answer data from the knowledge graph

[0935] Operation: The server processes the question, queries the Knowledge Graph API, and retrieves the answer.

[0936] Step 5:

[0937] The device displays the answers received from the knowledge graph in the chat interface.

[0938] Input: Response data from Knowledge Graph

[0939] Output: Answer displayed on the user screen

[0940] Operation: The device displays the received response on the chat interface.

[0941] Step 6:

[0942] A user enters an answer to another user's question and clicks the "Submit" button.

[0943] Input: Answer content

[0944] Output: The response content is sent to the server.

[0945] Operation: Users view other users' questions, enter answers based on their own knowledge and experience, and click the submit button.

[0946] Step 7:

[0947] The server saves the received responses to the database and adds them to the knowledge graph.

[0948] Input: Answer content

[0949] Output: Answers stored in the database, information added to the knowledge graph.

[0950] Operation: The server saves the answers to the database and adds the information to the knowledge graph.

[0951] Step 8:

[0952] The server analyzes the user's profile information and questions to select highly relevant advertisements.

[0953] Input: Profile information, Question content

[0954] Output: Selected ad data

[0955] Operation: The server analyzes user information and questions, and selects the most suitable advertisement from the advertising database.

[0956] Step 9:

[0957] The system displays selected advertisements in the chat interface.

[0958] Input: Selected ad data

[0959] Output: Advertisements displayed in the chat interface

[0960] Operation: Displays the advertising data received by the device on the chat interface, making it viewable by the user.

[0961] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0962] Patent Specification

[0963] The system of this invention provides information using knowledge graph technology and promotes knowledge sharing among users. Furthermore, by combining it with an emotion engine that recognizes user emotions, it achieves more personalized information delivery and an improved user experience. The specific processing of the program of this system is described below in natural language.

[0964] User registration and authentication system

[0965] 1. User registration:

[0966] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[0967] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[0968] Question submission and knowledge graph reference

[0969] 1. Enter and submit your question:

[0970] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[0971] User: Enter your question and click the "Submit" button.

[0972] Terminal: Sends the question to the server.

[0973] 1. Generating queries to the knowledge graph:

[0974] Server: Analyzes question data and generates queries for the knowledge graph. Executes the generated queries on the knowledge graph and retrieves appropriate information from it.

[0975] Server: Sends the retrieved information to the terminal in JSON format.

[0976] Terminal: Displays received information within the chat interface and provides responses to the user.

[0977] Knowledge sharing among users

[0978] 1. Question and answer exchange:

[0979] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[0980] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[0981] Ad display processing

[0982] 1. Selection and display of relevant advertisements:

[0983] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[0984] Device: Selected advertisements are displayed in specific locations within the chat interface.

[0985] User: Advertisements can be viewed through the chat interface.

[0986] Implementation of an emotion engine

[0987] 1. Emotion recognition and information provision:

[0988] Emotion Engine: Analyzes the text of questions and messages entered by the user to recognize the user's emotions (e.g., joy, sadness, anger, etc.).

[0989] Server: Adjusts the tone and content of information based on the perceived emotions of the user. For example, if the server perceives that the user is in distress, it provides additional support.

[0990] 1. Adjusting responses based on emotions:

[0991] Server: Uses templates and guidelines to adjust the tone and content of responses according to the user's emotions. Based on the user's emotions recognized by the emotion engine, it generates responses in an appropriate tone.

[0992] Terminal: Displays the adjusted response within the chat interface.

[0993] 1. Display of emotion indicators:

[0994] Terminal: Visualizes the user's emotions as recognized by the emotion engine and displays them as emotion indicators on the chat interface. This allows users to see how their emotions are being perceived.

[0995] Specific example:

[0996] 1. Example 1: User registration and authentication:

[0997] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[0998] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[0999] 2. Example 2: Posting and answering questions:

[1000] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

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

[1002] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1003] Terminal: Displays received responses within the chat interface.

[1004] 3. Example 3: Recognizing user emotions:

[1005] User: Looking confused, types, "This process is too difficult; I don't understand it."

[1006] Emotion Engine: Recognizes the user's "confusion" from the message.

[1007] Server: Generates answers with additional support information and a friendly tone.

[1008] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[1009] As described above, the system of the present invention combines knowledge graph technology and an emotion engine to provide users with rapid and accurate information, as well as personalized services to improve the user experience.

[1010] The following describes the processing flow.

[1011] User registration and authentication system

[1012] Step 1:

[1013] Terminal: Displays a form for the user to enter their name, email address, and password.

[1014] Step 2:

[1015] User: Enter your name, email address, and password, then click the "Register" button.

[1016] Step 3:

[1017] Terminal: Sends the entered data to the server.

[1018] Step 4:

[1019] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[1020] Step 5:

[1021] User: Your account will be activated by receiving an email and clicking the verification link.

[1022] Question submission and knowledge graph reference

[1023] Step 1:

[1024] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[1025] Step 2:

[1026] User: Enter your question and click the "Submit" button.

[1027] Step 3:

[1028] Terminal: Sends the question to the server.

[1029] Step 4:

[1030] Server: Analyzes question data and generates queries for the knowledge graph.

[1031] Step 5:

[1032] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[1033] Step 6:

[1034] Server: Sends the retrieved information to the terminal in JSON format.

[1035] Step 7:

[1036] Terminal: Displays received information within the chat interface.

[1037] Step 8:

[1038] User: Check the answer in the chat interface.

[1039] Knowledge sharing among users

[1040] Step 1:

[1041] Terminal: Displays questions from other users in the chat interface.

[1042] Step 2:

[1043] User: View other users' questions and enter answers based on your own knowledge.

[1044] Step 3:

[1045] User: Enter your answer and click the "Submit" button.

[1046] Step 4:

[1047] Terminal: Sends the entered response to the server.

[1048] Step 5:

[1049] Server: Saves received responses to the database and adds them to the knowledge graph.

[1050] Step 6:

[1051] Server: Sends saved answers to the terminal so that other users can also see them.

[1052] Step 7:

[1053] Terminal: Displays new replies in other users' chat interfaces.

[1054] Ad display processing

[1055] Step 1:

[1056] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1057] Step 2:

[1058] Server: Sends selected advertising data to the terminal in JSON format.

[1059] Step 3:

[1060] Device: Displays received advertisements in a specific location within the chat interface.

[1061] Step 4:

[1062] User: Views advertisements in a chat interface.

[1063] Implementation of an emotion engine

[1064] Step 1:

[1065] Terminal: Sends the message entered by the user to the emotion engine.

[1066] Step 2:

[1067] Emotion Engine: Analyzes user input messages and recognizes emotions (e.g., joy, confusion, anger).

[1068] Step 3:

[1069] Server: Based on emotional information received from the emotion engine, adjusts the tone of the information and responses provided.

[1070] Step 4:

[1071] Terminal: Displays the adjusted response within the chat interface.

[1072] Step 5:

[1073] Terminal: Visualizes the emotions of recognized users and displays them as emotion indicators on the chat interface.

[1074] Step 6:

[1075] User: Check the displayed emotion indicator to see how your emotions are being perceived.

[1076] (Example 2)

[1077] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1078] Information provision systems using knowledge graph technology are required not only to provide answers to questions, but also to provide personalized information based on the user's emotions. However, conventional systems lack the functionality to recognize and respond to user emotions, resulting in a lack of improvement in the user experience. Furthermore, there is a need for a means to efficiently display highly relevant advertisements while promoting knowledge sharing among users. This invention aims to solve these problems.

[1079] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1080] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for analyzing text entered by the user and recognizing emotions; and emotion adaptation means for adjusting responses based on recognized emotions and providing personalized information. This enables not only quick and accurate answers to user questions but also personalized information provision that takes user emotions into consideration. Furthermore, it facilitates knowledge sharing among users and enables the efficient display of highly relevant advertisements.

[1081] A "knowledge graph" is a structured graph of knowledge that shows the relationships between data, and it is a technology that systematically organizes information and allows for quick retrieval of information through queries.

[1082] "Information provision means" refers to a part of a system that uses knowledge graph technology to provide users with necessary information.

[1083] A "querying method" is a function that generates queries to the knowledge graph based on the user's question and retrieves corresponding information from the knowledge graph.

[1084] A "presentation means" is a function that provides an interface for displaying acquired information to the user.

[1085] An "emotion recognition tool" is a function that analyzes text entered by the user to recognize the user's emotions.

[1086] "Emotional adaptation mechanisms" are functions that adjust responses based on recognized emotions and provide personalized information to users.

[1087] "Storage method" refers to a function that saves answers to questions from other users to a database and adds them to the knowledge graph.

[1088] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[1089] This system combines knowledge graph technology and an emotion engine to provide users with personalized information, promote knowledge sharing among users, and display highly relevant advertisements. The following describes a specific implementation of this system.

[1090] User registration and authentication system

[1091] The terminal displays a form for the user to enter their name, email address, and password. Once the user submits the information, the server receives it and stores it in a database. For example, MySQL or PostgreSQL can be used for the database. Upon successful saving, the server generates an initial authentication token and sends it to the user's email address. This process allows the user to obtain an authentication link and complete the registration.

[1092] Question submission and knowledge graph reference

[1093] The terminal displays a chat interface, allowing the user to enter a question. Once the user enters and submits a question, the terminal sends it to the server. The server parses the question and generates a query against a knowledge graph. Examples of knowledge graphs that can be used include Neo4j and Amazon Neptune. The generated query is executed to retrieve the appropriate information. The retrieved information is sent to the terminal in JSON format, and the terminal displays the information within the chat interface.

[1094] Knowledge sharing among users

[1095] The terminal displays questions from other users, and users can enter and submit their answers. The server saves the received answers to a database and adds them to the knowledge graph. This allows other users to share this information.

[1096] Ad display processing

[1097] The server analyzes the user's profile information and questions to select highly relevant advertisements. These selected advertisements are sent to the user's device and displayed in specific locations within the chat interface. This allows the user to view relevant advertisements.

[1098] Implementation of an emotion engine

[1099] The emotion engine analyzes the text entered by the user and recognizes the user's emotions using natural language processing techniques (such as BERT or GPT-3). Based on the recognized emotions, the server adjusts the tone and content of the information. For example, if the server recognizes that the user is in distress, it provides additional support information and a more helpful tone in its response. The terminal displays the adjusted response and emotion indicator, allowing the user to see how their emotions are being perceived.

[1100] Specific example

[1101] 1. User registration and authentication:

[1102] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[1103] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1104] 2. Posting and answering questions:

[1105] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[1106] Terminal: Sends the question to the server.

[1107] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1108] Terminal: Displays received responses within the chat interface.

[1109] 3. Recognizing user emotions:

[1110] User: Looking confused, types, "This process is too difficult; I don't understand it."

[1111] Emotion Engine: Recognizes the user's "confusion" from the message.

[1112] Server: Generates answers with additional support information and a friendly tone.

[1113] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[1114] Through the above specific examples, this system can combine knowledge graph technology and an emotion engine to provide users with fast and accurate information, thereby improving the user experience.

[1115] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1116] Step 1:

[1117] Displaying user registration

[1118] The terminal displays an input form for the user to enter their name, email address, and password. The input form includes a "Register" button, which the user clicks to submit the entered data. Input and Output: The input is the name, email address, and password entered by the user, and the output is the transmission of this data to the server.

[1119] Step 2:

[1120] Send user information

[1121] When the user clicks the "Register" button, the terminal sends the entered information (name, email address, password) to the server. Input and Output: Input is the data entered by the user, and output is the data sent to the server.

[1122] Step 3:

[1123] User information storage

[1124] The server receives the submitted user information and stores it in a database. Specifically, it uses MySQL or PostgreSQL as the database. If the storage is successful, the server generates an initial authentication token and sends it to the user's email address. Input and Output: The input is the user's registration information, and the output is the entry stored in the database and the generated authentication token.

[1125] Step 4:

[1126] Sending an authentication token

[1127] The server sends an email containing the generated initial authentication token to the user's email address. This gives the user a link to complete the authentication process. Input and Output: The input is the generated authentication token and the user's email address, and the output is the authentication email sent to the user.

[1128] Step 5:

[1129] Display of the question input screen

[1130] The device displays a chat interface, allowing the user to enter questions using a text box. A "Send" button is also provided. Input and Output: Input is the question entered by the user, and output is the display of the chat interface on the device.

[1131] Step 6:

[1132] Submit a question

[1133] The user enters a question in the text box and clicks the "Submit" button. The terminal sends this to the server. Input and Output: The input is the question entered by the user, and the output is the question data sent to the server.

[1134] Step 7:

[1135] Query generation

[1136] The server parses the submitted question and generates a query for the knowledge graph. Specifically, if the question is "How do I write a business plan?", it will search for data related to "how to write a business plan". Input and Output: The input is the question entered by the user, and the output is the query generated for the knowledge graph.

[1137] Step 8:

[1138] Executing queries on the knowledge graph

[1139] The server executes the generated queries against the knowledge graph and retrieves relevant information. Neo4j and Amazon Neptune are commonly used as the knowledge graph. The retrieved information is structured within the server in JSON format. Input and Output: The input is the generated query, and the output is the information retrieved from the knowledge graph.

[1140] Step 9:

[1141] Submit and display of responses

[1142] The server sends structured information to the terminal in JSON format. The terminal displays the received information within the chat interface and provides answers to the user. Input and Output: The input is information obtained from the knowledge graph, and the output is the answers displayed in the chat interface.

[1143] Step 10:

[1144] Displaying questions from other users

[1145] The terminal displays questions from other users in a chat interface. Users can then type and submit their answers. Input and Output: Input is the question from another user, and output is the displayed question.

[1146] Step 11:

[1147] Enter and submit your response.

[1148] The user enters an answer to another user's question and clicks the "Submit" button. The terminal sends the entered answer to the server. Input and Output: The input is the answer entered by the user, and the output is the answer data sent to the server.

[1149] Step 12:

[1150] Save and share your answers

[1151] The server saves the received responses to the database and adds them to the knowledge graph. This allows other users to access this information. Input and Output: The input is the user's response, and the output is the entries saved in the database and updates to the knowledge graph.

[1152] Step 13:

[1153] Ad selection

[1154] The server analyzes the user's profile information and questions to select highly relevant advertisements. For example, if the question includes "business plan," it will select advertisements for business books. Input and Output: The input is the user's profile information and questions, and the output is the selected advertisement information.

[1155] Step 14:

[1156] Displaying ads

[1157] The device displays selected advertisements in specific locations within the chat interface. This allows users to view relevant advertisements. Input and Output: The input is the selected advertisement information, and the output is the advertisement displayed in the chat interface.

[1158] Step 15:

[1159] Recognition of emotions

[1160] The emotion engine analyzes text entered by the user and recognizes the user's emotions using natural language processing techniques (e.g., BERT and GPT-3). For example, it recognizes confusion from keywords such as "troubled" and "difficult." Input and Output: The input is the user's text, and the output is the recognized emotion information.

[1161] Step 16:

[1162] Coordination of information provision

[1163] The server adjusts the tone and content of information based on the recognized user's emotions. For example, it provides additional support information and a gentler tone of message to a user who is in distress. Input and Output: The input is the recognized emotion information, and the output is the adjusted response.

[1164] Step 17:

[1165] Display of emotion indicator

[1166] The device visualizes the user's emotions, as recognized by the emotion engine, and displays them as emotion indicators on the chat interface. This allows the user to see how their emotions are being perceived. Input and Output: The input is the recognized emotion information, and the output is the displayed emotion indicator.

[1167] (Application Example 2)

[1168] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1169] Traditional information provision systems merely provided information in response to user questions, failing to consider user emotions. This could lead to decreased user satisfaction and trust. Furthermore, the system did not effectively facilitate knowledge sharing among users or present relevant advertisements, limiting the quality of information provided and the effectiveness of advertising.

[1170] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1171] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for recognizing the user's emotions using an emotion engine and adjusting the tone and content of the information based on those emotions; and emotion indicator means for visualizing the results of emotion recognition to the user. This enables personalized information provision, increasing not only user satisfaction but also trust. Furthermore, by saving answers to questions from other users in a database and adding them to the knowledge graph, knowledge sharing among users is promoted. The effectiveness of advertisements can also be enhanced by selecting and displaying highly relevant advertisements based on profile information and the context of the questions.

[1172] "Knowledge graph technology" is a technique that represents data in a graph structure and organizes and displays information using nodes (individual elements of data) and edges (relationships between nodes).

[1173] "Information provision means" refers to systems and functions that provide users with the information they need.

[1174] "Query means" refers to a system or function that generates queries in a knowledge graph based on user questions and retrieves information from that knowledge graph.

[1175] "Presentation means" refers to a system or function for displaying acquired information to the user.

[1176] An "emotion engine" refers to a system or algorithm that analyzes and recognizes a user's emotions from text and audio data.

[1177] "Emotion recognition means" refers to a system or function that uses an emotion engine to recognize a user's emotions and adjusts information based on the results.

[1178] "Emotion indicator means" refers to systems or functions that visualize recognized emotions for the user.

[1179] "Storage method" refers to a system or function for saving answers to questions from other users to a database and adding them to a knowledge graph.

[1180] "Advertising display method" refers to a system or function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[1181] This invention aims to realize a system that provides personalized information to users by utilizing knowledge graph technology and an emotion engine. The necessary hardware and software configuration and each processing step for this purpose will be described.

[1182] Hardware configuration

[1183] Servers: Database server (e.g., MySQL), Application server (e.g., Node.js)

[1184] Client device: Smartphone (iOS / Android)

[1185] Software Configuration

[1186] Data analysis: Python, Knowledge graph (e.g., Neo4j)

[1187] Emotion recognition: Natural language processing libraries (NLP) and AI models (e.g., TensorFlow, Hugging Face)

[1188] Explanation of processing details

[1189] 1. User registration and authentication:

[1190] The user registers by entering their name, email address, and password. The entered data is sent to the server and stored in the database (MySQL). An authentication token is generated and sent to the user via email.

[1191] 2. Question posting and knowledge graph referencing:

[1192] The user submits a question through the chat interface. The server analyzes the question and generates a query for the knowledge graph (Neo4j). Based on the generated query, information is retrieved from the knowledge graph. The retrieved information is sent in JSON format and displayed on the smartphone.

[1193] 3. Knowledge sharing among users:

[1194] Other users' questions and answers are displayed in the chat interface. Users can type and submit their answers. The answers are stored in a database by the server and added to the knowledge graph.

[1195] 4. Emotion recognition and information provision:

[1196] The user's message is sent to an emotion engine (TensorFlow, Hugging Face) and analyzed. The emotion engine recognizes the user's emotions from the sent message, and based on the result, the server generates a response in an appropriate tone. The generated response is then provided to the user.

[1197] 5. Display of emotion indicators:

[1198] Recognized emotions are displayed as emotion indicators in the smartphone's chat interface. This allows users to see how their emotions are being perceived.

[1199] 6. Advertisement display:

[1200] The server analyzes the user's profile information and the context of the question to select the most relevant advertisements. The selected advertisements are then displayed in the chat interface.

[1201] Examples of specific cases and prompt statements

[1202] Specific example:

[1203] 1. Question posted: "Please tell me the latest movie reviews."

[1204] 2. Emotion Recognition: Recognizing the emotion "I was disappointed because the movie reviews were terrible."

[1205] Example of a prompt:

[1206] "The user has asked about the latest movie reviews and expressed disappointment. How should the system respond considering the user's emotional state?"

[1207] Based on these configurations, a system combining a knowledge graph and an emotion engine will provide users with fast and appropriate information and personalized support, resulting in a better user experience.

[1208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1209] Step 1:

[1210] User registration and authentication

[1211] The user enters their name, email address, and password in the smartphone app and clicks the registration button.

[1212] The terminal sends the entered data to the server.

[1213] The server saves the received data to a database (MySQL) and generates an authentication token. This token is then sent to the user via email.

[1214] Input: Name, email address, password

[1215] Output: Authentication token

[1216] Step 2:

[1217] Question submission and knowledge graph reference

[1218] The user enters their question in the chat interface and clicks the send button.

[1219] The terminal sends the question data to the server.

[1220] The server analyzes the received question and generates a query against the knowledge graph (Neo4j). It executes the generated query and retrieves the necessary information from the knowledge graph. The retrieved information is sent to the terminal in JSON format. The terminal displays the retrieved information in the chat interface.

[1221] Input: User's question text

[1222] Output: Information obtained from the knowledge graph

[1223] Step 3:

[1224] Knowledge sharing among users

[1225] The device displays questions and answers from other users in a chat interface.

[1226] Users enter their answers based on their knowledge and experience and click the submit button.

[1227] The device sends the response data to the server.

[1228] The server saves the received answers to a database and adds them to the knowledge graph. The saved answers are also visible to other users, facilitating knowledge sharing.

[1229] Input: User's response text

[1230] Output: Answers stored in the database, information added to the knowledge graph.

[1231] Step 4:

[1232] Emotion recognition and information provision

[1233] The user types a message in the chat interface and clicks the send button.

[1234] The terminal sends message data to the server.

[1235] The server sends the received messages to the emotion engine (TensorFlow, Hugging Face) for analysis.

[1236] The emotion engine analyzes the user's emotions from the message and returns the results to the server.

[1237] Based on the emotion recognition results, the server generates a response in an appropriate tone, sends it to the terminal, and displays it.

[1238] Input: User's message text

[1239] Output: Emotion recognition results from the emotion engine, adjusted response

[1240] Step 5:

[1241] Display of emotion indicator

[1242] The device displays emotion indicators recognized by the emotion engine on the chat interface. This allows users to see how their emotions are being perceived.

[1243] Input: Sentiment recognition result

[1244] Output: Visual display of emotion indicators

[1245] Step 6:

[1246] Advertisement

[1247] The server analyzes the user's profile information and question data to select highly relevant advertisements.

[1248] Selected advertisements are displayed in the chat interface. Users can view relevant advertisements.

[1249] Input: User profile information, question data

[1250] Output: Advertisements displayed in the chat interface

[1251] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1252] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1253] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1254] [Third Embodiment]

[1255] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1256] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1257] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1258] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1259] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1260] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1261] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1262] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1263] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1264] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1265] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1266] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1267] Patent Specification

[1268] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[1269] User registration and authentication system

[1270] 1. User registration:

[1271] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[1272] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[1273] Question submission and knowledge graph reference

[1274] 1. Enter and submit your question:

[1275] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[1276] Server: Receives a question and generates a query against the knowledge graph. Executes the generated query against the knowledge graph and sends the information obtained from the knowledge graph to the terminal in JSON format.

[1277] Terminal: Displays received information within the chat interface and provides responses to the user.

[1278] Knowledge sharing among users

[1279] 1. Question and answer exchange:

[1280] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[1281] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[1282] Ad display processing

[1283] 1. Selection and display of relevant advertisements:

[1284] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1285] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[1286] Specific example:

[1287] 1. Example 1: User registration and authentication:

[1288] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[1289] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1290] 2. Example 2: Posting and answering questions:

[1291] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[1292] Terminal: Sends the question to the server.

[1293] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1294] Terminal: Displays received responses within the chat interface.

[1295] User knowledge sharing and ad display

[1296] 1. Example 3: Answering another user's question:

[1297] User A: Asks in the chat window, "Which marketing tool do you recommend?"

[1298] Terminal: Sends the question to the server and displays it to other users.

[1299] User B: Based on their own experience, they recommend HubSpot.

[1300] Terminal: Submit your answer and display it to other users.

[1301] Server: Saves the answer to the database and adds it to the knowledge graph.

[1302] 2. Example 4: Displaying related ads:

[1303] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[1304] Device: Selected advertisements are displayed in specific locations within the chat interface.

[1305] User: Views the displayed advertisement.

[1306] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[1307] The following describes the processing flow.

[1308] User registration and authentication system

[1309] Step 1:

[1310] Terminal: Displays a form for the user to enter their name, email address, and password.

[1311] Step 2:

[1312] User: Enter your name, email address, and password, then click the "Register" button.

[1313] Step 3:

[1314] Terminal: Sends the entered data to the server.

[1315] Step 4:

[1316] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[1317] Step 5:

[1318] User: Your account will be activated by receiving an email and clicking the verification link.

[1319] Question submission and knowledge graph reference

[1320] Step 1:

[1321] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[1322] Step 2:

[1323] User: Enter your question and click the "Submit" button.

[1324] Step 3:

[1325] Terminal: Sends the question to the server.

[1326] Step 4:

[1327] Server: Analyzes question data and generates queries for the knowledge graph.

[1328] Step 5:

[1329] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[1330] Step 6:

[1331] Server: Sends the retrieved information to the terminal in JSON format.

[1332] Step 7:

[1333] Terminal: Displays received information within the chat interface.

[1334] Step 8:

[1335] User: Check the answer in the chat interface.

[1336] Knowledge sharing among users

[1337] Step 1:

[1338] Terminal: Displays questions from other users in the chat interface.

[1339] Step 2:

[1340] User: View other users' questions and enter answers based on your own knowledge.

[1341] Step 3:

[1342] User: Enter your answer and click the "Submit" button.

[1343] Step 4:

[1344] Terminal: Sends the entered response to the server.

[1345] Step 5:

[1346] Server: Saves received responses to the database and adds them to the knowledge graph.

[1347] Step 6:

[1348] Server: Sends saved answers to the terminal so that other users can also see them.

[1349] Step 7:

[1350] Terminal: Displays new replies in other users' chat interfaces.

[1351] Ad display processing

[1352] Step 1:

[1353] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1354] Step 2:

[1355] Server: Sends selected advertising data to the terminal in JSON format.

[1356] Step 3:

[1357] Device: Displays received advertisements in a specific location within the chat interface.

[1358] Step 4:

[1359] User: Views advertisements in a chat interface.

[1360] (Example 1)

[1361] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1362] There is a need to provide a platform where novice entrepreneurs can efficiently acquire information and share knowledge among users, as well as to appropriately display advertisements tailored to users' interests. However, it has been difficult to effectively achieve this using conventional methods.

[1363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1364] In this invention, the server includes: an information provision means using knowledge graph technology; an inquiry means for generating queries to the knowledge graph based on user questions and retrieving corresponding information from the knowledge graph; a presentation means for providing the retrieved information to the user via a chat interface; a storage means for saving user-inputted information to a database; and an authentication means for generating an initial authentication token for the user and sending it via email. This enables novice entrepreneurs to easily and quickly obtain necessary information and facilitates the sharing of specific and useful knowledge among users. Furthermore, the effectiveness of advertisements can be maximized by displaying advertisements tailored to the user's interests.

[1365] "Knowledge graph technology" is a technique that semantically links and represents large amounts of data, enabling users to understand the relationships between those data points.

[1366] "Information provision means" refers to devices or systems that provide users with the information they seek.

[1367] A "query" is a command that attempts to inquire about information from a data repository, such as a database or knowledge graph.

[1368] A "query tool" is a device or system that generates queries based on user questions and retrieves information from databases or knowledge graphs.

[1369] A "chat interface" is a user interface that allows users to communicate in a text-based, conversational format.

[1370] "Presentation means" refers to a device or system for displaying acquired information to the user.

[1371] "Storage means" refers to devices or systems that store data entered by users or information acquired by the system.

[1372] "Authentication means" refers to devices or systems used to verify the identity of a user during registration.

[1373] An "initial authentication token" is a unique identifier used when a user logs in for the first time, and is generated to assist in the authentication process.

[1374] "Profile information" refers to a collection of personal data, such as a user's basic information, interests, and preferences.

[1375] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[1376] User registration and authentication system

[1377] User registration:

[1378] Terminal: Displays a form for the user to enter their name, email address, and password. This form is built using HTML and JavaScript. When the user clicks the "Register" button, the terminal sends that information to the server in JSON format.

[1379] Server: Uses a Java-based Spring Boot framework to receive user information. After validating the received information, it saves it to a MySQL database. If the save is successful, it generates a JWT (JSON Web Token) and sends it to the user's email address via an SMTP server.

[1380] Specific example:

[1381] Terminal: The user enters the name "Sato Ichiro", email address "ichiro@example.com", and password "password123", then clicks the "Register" button.

[1382] Server: Receives input data and saves it to the database. It also generates an initial authentication token and sends it to "ichiro@example.com".

[1383] Question submission and knowledge graph reference

[1384] Enter and submit your question:

[1385] Terminal: Provides a chat interface built using React, allowing users to type questions. When a user types a question and clicks the "Send" button, the question is sent from the terminal to the server.

[1386] Server: Uses the Spring Boot framework to parse received questions and generates queries against the knowledge graph using SPARQL or Cypher. Executes the generated queries and sends the retrieved information to the terminal in JSON format.

[1387] Specific example:

[1388] User: Type "Please teach me how to create a business model" into the chat window and click the "Send" button.

[1389] Terminal: Sends the question to the server.

[1390] Server: Queries the knowledge graph to retrieve information about "how to create a business model" and responds to the user.

[1391] Terminal: Displays received responses within the chat interface.

[1392] Knowledge sharing among users

[1393] Question and answer exchange:

[1394] Terminal: Displays questions from other users in the chat interface. For example, it can display questions in real time using Polling or WebSocket.

[1395] User: Look at other users' questions, enter an answer based on your own experience, and click the "Submit" button.

[1396] Server: Received answers are saved to a MySQL database and then added to the knowledge graph.

[1397] Specific example:

[1398] User A: Asks in the chat window, "What are some recommended marketing tools?"

[1399] Terminal: Sends the question to the server and displays it to other users.

[1400] User B: Based on their own experience, they answer, "SEO tools are useful."

[1401] Terminal: Submit your answer and display it to other users.

[1402] Server: Saves the answer to the database and adds it to the knowledge graph.

[1403] Ad display processing

[1404] Selecting and displaying relevant advertisements:

[1405] Server: Analyzes user profile information and question content to select highly relevant advertisements. For example, it uses natural language processing (NLP) techniques to analyze question content.

[1406] Device: The selected advertisement is displayed in a specific location within the chat interface. The device performs rendering to display the advertisement data.

[1407] Specific example:

[1408] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[1409] Device: Selected advertisements are displayed in specific locations within the chat interface.

[1410] User: Views the displayed advertisement.

[1411] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[1412] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1413] Step 1:

[1414] The user enters their name, email address, and password into an input form. For example, the user enters information into a form built with HTML and JavaScript on their device. The input is converted into JSON in the following format.

[1415] input:{

[1416] "Name": "Ichiro Sato",

[1417] "Email address": "ichiro@example.com",

[1418] "Password": "password123"

[1419] }

[1420] Output: User information in JSON format

[1421] Step 2:

[1422] When the device clicks the "Register" button, it sends this JSON-formatted user information to the server. Specifically, it uses JavaScript to send this data to the server via the HTTPS protocol.

[1423] Input: User information in JSON format

[1424] Output: HTTP request to the server

[1425] Step 3:

[1426] The server receives user information using the Spring Boot framework and performs validation. For example, it checks the validity of the email address and the strength of the password.

[1427] Input: Received user information

[1428] Output: Validation result (success or error)

[1429] Step 4:

[1430] After successful validation, the server saves the user information to the MySQL database. Transactions are managed during this process to verify the success or failure of the save operation.

[1431] Input: User information that passed validation

[1432] Output: Result of saving to the database (success or error)

[1433] Step 5:

[1434] If saving is successful, the server generates a JWT (JSON Web Token) for initial authentication. This token is associated with the user's email address.

[1435] Input: Confirmation of successful save operation

[1436] Output: Generated JWT

[1437] Step 6:

[1438] A confirmation email containing the generated JWT is sent to the user's email address. The email is sent using an SMTP server, and the success or failure of the transmission is recorded.

[1439] Input: JWT and user's email address

[1440] Output: Confirmation of sent emails

[1441] Step 7:

[1442] The user enters a question in the system's chat interface. The interface, built using React, allows the user to enter a question and click the "Send" button.

[1443] Input: User's question (e.g., "How do I create a business model?")

[1444] Output: Question data in JSON format

[1445] Step 8:

[1446] The device sends this JSON-formatted question data to the server. It sends the data via the HTTPS protocol using JavaScript.

[1447] Input: Question data in JSON format

[1448] Output: HTTP request to the server

[1449] Step 9:

[1450] The server analyzes the received question data and generates SPARQL or Cypher queries. These generated queries are then executed against the knowledge graph.

[1451] Input: Received question data

[1452] Output: The generated query and its execution result

[1453] Step 10:

[1454] The retrieved information is sent back to the terminal in JSON format. The server formats the retrieved information and sends it as an HTTP response.

[1455] Input: Execution results from Knowledge Graph

[1456] Output: Response data in JSON format

[1457] Step 11:

[1458] The device receives response data in JSON format and displays it within the chat interface. The React component parses the received data and displays it in a user-friendly format.

[1459] Input: Response data in JSON format

[1460] Output: Answer displayed on the interface

[1461] Step 12:

[1462] This feature allows users to submit answers to questions from other users. The chat interface displays other users' questions, and users can enter their answers and click the "Submit" button.

[1463] Input: Questions and answers from other users

[1464] Output: Response data in JSON format

[1465] Step 13:

[1466] The server stores the received response data in a database and then adds it to the knowledge graph. This response data can be reused in the future as information for other users' questions.

[1467] Input: Received response data

[1468] Output: Results saved to the database and knowledge graph

[1469] Step 14:

[1470] The system selects highly relevant advertisements based on the user's profile information and the content of their questions. Natural language processing (NLP) techniques are used to analyze the questions.

[1471] Input: User profile information and questions

[1472] Output: Selected ad data

[1473] Step 15:

[1474] Selected advertising data is displayed in a specific location within the chat interface. The device receives the advertising data and displays it in a location where the user can view it.

[1475] Input: Selected ad data

[1476] Output: Advertisements displayed on the interface

[1477] The above outlines the specific processing steps of the system. This system allows novice entrepreneurs to efficiently acquire information, promotes knowledge sharing among users, and displays advertisements tailored to their interests.

[1478] (Application Example 1)

[1479] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1480] Traditional information systems suffer from problems such as delayed support and inaccurate information provided when users submit questions. Furthermore, knowledge sharing among users is inefficient, often resulting in biased or incomplete information. Additionally, there are limitations to the means of delivering optimal advertisements to users. There is a need to develop a system that solves these problems, providing rapid and accurate information and knowledge sharing to novice entrepreneurs, and presenting appropriate advertisements.

[1481] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1482] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; advertisement presentation means for selecting highly relevant advertisements based on the content of the question and displaying the advertisements on the chat interface; storage means for saving the user's questions and answers, adding them to the knowledge graph, and displaying them to other users; and execution means as an application that operates on smartphones, smart glasses, and head-mounted displays. As a result, users can not only receive information quickly and accurately, but also efficiently share knowledge with other users and view highly relevant advertisements in a timely manner.

[1483] "Knowledge graph technology" is a technique that visualizes information entities and their interrelationships, and presents relevant information in response to user questions.

[1484] "Information provision means" refers to a function that uses a knowledge graph to provide users with the necessary information.

[1485] A "querying method" is a function that executes queries against the knowledge graph based on the user's question and retrieves the results.

[1486] "Presentation method" refers to a function that provides acquired information in a format that users can view, specifically by displaying it through a chat interface.

[1487] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's question and displays them in the chat interface.

[1488] The "storage method" refers to a function that saves user questions and answers to a database, adds them to a knowledge graph, and displays them to other users.

[1489] "Execution means" refers to the function that allows the system to run on a device such as a smartphone, smart glasses, or head-mounted display.

[1490] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. This system is implemented with the following configuration.

[1491] User registration and authentication system

[1492] User Registration

[1493] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[1494] Server: Receives user information and saves it to a database (such as MongoDB). If the save is successful, it generates an initial authentication token and sends it to the user via email.

[1495] Specific example

[1496] Enter the following information: Username "Yamada Taro", email address "taro@example.com", and password "password123", then click the "Register" button.

[1497] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1498] Question submission and knowledge graph reference

[1499] Enter and submit your question

[1500] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[1501] Server: Receives a question, generates and executes a query for the knowledge graph (e.g., Google Knowledge Graph API). Sends the information retrieved from the knowledge graph to the terminal in JSON format.

[1502] Terminal: Displays received information within the chat interface and provides responses to the user.

[1503] Specific example

[1504] User: Type "Please teach me how to write a business plan" into the chat interface and click the "Send" button.

[1505] Server: Queries the knowledge graph to retrieve information about "how to write a business plan" and responds to the user.

[1506] Terminal: Displays received responses within the chat interface.

[1507] Knowledge sharing among users

[1508] Question and answer exchange

[1509] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[1510] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[1511] Specific example

[1512] User A asks the chat interface, "Which marketing tool do you recommend?"

[1513] Terminal: Sends the question to the server and displays it to other users.

[1514] User B: Based on their own experience, they recommend HubSpot.

[1515] Terminal: Submit your answer and display it to other users.

[1516] Server: Saves the answer to the database and adds it to the knowledge graph.

[1517] Ad display processing

[1518] Selection and display of relevant advertisements

[1519] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1520] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[1521] Specific example

[1522] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[1523] Device: Selected advertisements are displayed in specific locations within the chat interface.

[1524] User: Views the displayed advertisement.

[1525] Example of a prompt

[1526] "Methods of raising funds when starting a business"

[1527] "Common methods of raising funds when starting a business include: 1. Funding from angel investors, 2. Crowdfunding, and 3. Venture capital."

[1528] Through this system, users can receive information quickly and accurately, efficiently share knowledge with other users, and view relevant advertisements in a timely manner.

[1529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1530] Step 1:

[1531] The user enters their name, email address, and password on their device and clicks the "Register" button.

[1532] Input: Name, email address, password

[1533] Output: User information is sent to the server.

[1534] Action: The user enters information into a form and clicks a button.

[1535] Step 2:

[1536] The server stores the received user information in a database, generates an initial authentication token, and sends it to the user via email.

[1537] Input: User information (name, email address, password)

[1538] Output: User information stored in the database, generated authentication token

[1539] Operation: The server saves data to a database and generates a token, then uses an email server to send the token.

[1540] Step 3:

[1541] The user enters a question in the chat interface and clicks the "Send" button.

[1542] Input: Question content

[1543] Output: The question content is sent to the server.

[1544] Operation: The user enters a question into the chat interface and clicks a button.

[1545] Step 4:

[1546] The server generates and executes queries in the knowledge graph based on the questions it receives.

[1547] Input: Question content

[1548] Output: Answer data from the knowledge graph

[1549] Operation: The server processes the question, queries the Knowledge Graph API, and retrieves the answer.

[1550] Step 5:

[1551] The device displays the answers received from the knowledge graph in the chat interface.

[1552] Input: Response data from Knowledge Graph

[1553] Output: Answer displayed on the user screen

[1554] Operation: The device displays the received response on the chat interface.

[1555] Step 6:

[1556] A user enters an answer to another user's question and clicks the "Submit" button.

[1557] Input: Answer content

[1558] Output: The response content is sent to the server.

[1559] Operation: Users view other users' questions, enter answers based on their own knowledge and experience, and click the submit button.

[1560] Step 7:

[1561] The server saves the received responses to the database and adds them to the knowledge graph.

[1562] Input: Answer content

[1563] Output: Answers stored in the database, information added to the knowledge graph.

[1564] Operation: The server saves the answers to the database and adds the information to the knowledge graph.

[1565] Step 8:

[1566] The server analyzes the user's profile information and questions to select highly relevant advertisements.

[1567] Input: Profile information, Question content

[1568] Output: Selected ad data

[1569] Operation: The server analyzes user information and questions, and selects the most suitable advertisement from the advertising database.

[1570] Step 9:

[1571] The system displays selected advertisements in the chat interface.

[1572] Input: Selected ad data

[1573] Output: Advertisements displayed in the chat interface

[1574] Operation: Displays the advertising data received by the device on the chat interface, making it viewable by the user.

[1575] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1576] Patent Specification

[1577] The system of this invention provides information using knowledge graph technology and promotes knowledge sharing among users. Furthermore, by combining it with an emotion engine that recognizes user emotions, it achieves more personalized information delivery and an improved user experience. The specific processing of the program of this system is described below in natural language.

[1578] User registration and authentication system

[1579] 1. User registration:

[1580] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[1581] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[1582] Question submission and knowledge graph reference

[1583] 1. Enter and submit your question:

[1584] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[1585] User: Enter your question and click the "Submit" button.

[1586] Terminal: Sends the question to the server.

[1587] 1. Generating queries to the knowledge graph:

[1588] Server: Analyzes question data and generates queries for the knowledge graph. Executes the generated queries on the knowledge graph and retrieves appropriate information from it.

[1589] Server: Sends the retrieved information to the terminal in JSON format.

[1590] Terminal: Displays received information within the chat interface and provides responses to the user.

[1591] Knowledge sharing among users

[1592] 1. Question and answer exchange:

[1593] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[1594] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[1595] Ad display processing

[1596] 1. Selection and display of relevant advertisements:

[1597] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1598] Device: Selected advertisements are displayed in specific locations within the chat interface.

[1599] User: Advertisements can be viewed through the chat interface.

[1600] Implementation of an emotion engine

[1601] 1. Emotion recognition and information provision:

[1602] Emotion Engine: Analyzes the text of questions and messages entered by the user to recognize the user's emotions (e.g., joy, sadness, anger, etc.).

[1603] Server: Adjusts the tone and content of information based on the perceived emotions of the user. For example, if the server perceives that the user is in distress, it provides additional support.

[1604] 1. Adjusting responses based on emotions:

[1605] Server: Uses templates and guidelines to adjust the tone and content of responses according to the user's emotions. Based on the user's emotions recognized by the emotion engine, it generates responses in an appropriate tone.

[1606] Terminal: Displays the adjusted response within the chat interface.

[1607] 1. Display of emotion indicators:

[1608] Terminal: Visualizes the user's emotions as recognized by the emotion engine and displays them as emotion indicators on the chat interface. This allows users to see how their emotions are being perceived.

[1609] Specific example:

[1610] 1. Example 1: User registration and authentication:

[1611] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[1612] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1613] 2. Example 2: Posting and answering questions:

[1614] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[1615] Terminal: Sends the question to the server.

[1616] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1617] Terminal: Displays received responses within the chat interface.

[1618] 3. Example 3: Recognizing user emotions:

[1619] User: Looking confused, types, "This process is too difficult; I don't understand it."

[1620] Emotion Engine: Recognizes the user's "confusion" from the message.

[1621] Server: Generates answers with additional support information and a friendly tone.

[1622] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[1623] As described above, the system of the present invention combines knowledge graph technology and an emotion engine to provide users with rapid and accurate information, as well as personalized services to improve the user experience.

[1624] The following describes the processing flow.

[1625] User registration and authentication system

[1626] Step 1:

[1627] Terminal: Displays a form for the user to enter their name, email address, and password.

[1628] Step 2:

[1629] User: Enter your name, email address, and password, then click the "Register" button.

[1630] Step 3:

[1631] Terminal: Sends the entered data to the server.

[1632] Step 4:

[1633] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[1634] Step 5:

[1635] User: Your account will be activated by receiving an email and clicking the verification link.

[1636] Question submission and knowledge graph reference

[1637] Step 1:

[1638] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[1639] Step 2:

[1640] User: Enter your question and click the "Submit" button.

[1641] Step 3:

[1642] Terminal: Sends the question to the server.

[1643] Step 4:

[1644] Server: Analyzes question data and generates queries for the knowledge graph.

[1645] Step 5:

[1646] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[1647] Step 6:

[1648] Server: Sends the retrieved information to the terminal in JSON format.

[1649] Step 7:

[1650] Terminal: Displays received information within the chat interface.

[1651] Step 8:

[1652] User: Check the answer in the chat interface.

[1653] Knowledge sharing among users

[1654] Step 1:

[1655] Terminal: Displays questions from other users in the chat interface.

[1656] Step 2:

[1657] User: View other users' questions and enter answers based on your own knowledge.

[1658] Step 3:

[1659] User: Enter your answer and click the "Submit" button.

[1660] Step 4:

[1661] Terminal: Sends the entered response to the server.

[1662] Step 5:

[1663] Server: Saves received responses to the database and adds them to the knowledge graph.

[1664] Step 6:

[1665] Server: Sends saved answers to the terminal so that other users can also see them.

[1666] Step 7:

[1667] Terminal: Displays new replies in other users' chat interfaces.

[1668] Ad display processing

[1669] Step 1:

[1670] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1671] Step 2:

[1672] Server: Sends selected advertising data to the terminal in JSON format.

[1673] Step 3:

[1674] Device: Displays received advertisements in a specific location within the chat interface.

[1675] Step 4:

[1676] User: Views advertisements in a chat interface.

[1677] Implementation of an emotion engine

[1678] Step 1:

[1679] Terminal: Sends the message entered by the user to the emotion engine.

[1680] Step 2:

[1681] Emotion Engine: Analyzes user input messages and recognizes emotions (e.g., joy, confusion, anger).

[1682] Step 3:

[1683] Server: Based on emotional information received from the emotion engine, adjusts the tone of the information and responses provided.

[1684] Step 4:

[1685] Terminal: Displays the adjusted response within the chat interface.

[1686] Step 5:

[1687] Terminal: Visualizes the emotions of recognized users and displays them as emotion indicators on the chat interface.

[1688] Step 6:

[1689] User: Check the displayed emotion indicator to see how your emotions are being perceived.

[1690] (Example 2)

[1691] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1692] Information provision systems using knowledge graph technology are required not only to provide answers to questions, but also to provide personalized information based on the user's emotions. However, conventional systems lack the functionality to recognize and respond to user emotions, resulting in a lack of improvement in the user experience. Furthermore, there is a need for a means to efficiently display highly relevant advertisements while promoting knowledge sharing among users. This invention aims to solve these problems.

[1693] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1694] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for analyzing text entered by the user and recognizing emotions; and emotion adaptation means for adjusting responses based on recognized emotions and providing personalized information. This enables not only quick and accurate answers to user questions but also personalized information provision that takes user emotions into consideration. Furthermore, it facilitates knowledge sharing among users and enables the efficient display of highly relevant advertisements.

[1695] A "knowledge graph" is a structured graph of knowledge that shows the relationships between data, and it is a technology that systematically organizes information and allows for quick retrieval of information through queries.

[1696] "Information provision means" refers to a part of a system that uses knowledge graph technology to provide users with necessary information.

[1697] A "querying method" is a function that generates queries to the knowledge graph based on the user's question and retrieves corresponding information from the knowledge graph.

[1698] A "presentation means" is a function that provides an interface for displaying acquired information to the user.

[1699] An "emotion recognition tool" is a function that analyzes text entered by the user to recognize the user's emotions.

[1700] "Emotional adaptation mechanisms" are functions that adjust responses based on recognized emotions and provide personalized information to users.

[1701] "Storage method" refers to a function that saves answers to questions from other users to a database and adds them to the knowledge graph.

[1702] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[1703] This system combines knowledge graph technology and an emotion engine to provide users with personalized information, promote knowledge sharing among users, and display highly relevant advertisements. The following describes a specific implementation of this system.

[1704] User registration and authentication system

[1705] The terminal displays a form for the user to enter their name, email address, and password. Once the user submits the information, the server receives it and stores it in a database. For example, MySQL or PostgreSQL can be used for the database. Upon successful saving, the server generates an initial authentication token and sends it to the user's email address. This process allows the user to obtain an authentication link and complete the registration.

[1706] Question submission and knowledge graph reference

[1707] The terminal displays a chat interface, allowing the user to enter a question. Once the user enters and submits a question, the terminal sends it to the server. The server parses the question and generates a query against a knowledge graph. Examples of knowledge graphs that can be used include Neo4j and Amazon Neptune. The generated query is executed to retrieve the appropriate information. The retrieved information is sent to the terminal in JSON format, and the terminal displays the information within the chat interface.

[1708] Knowledge sharing among users

[1709] The terminal displays questions from other users, and users can enter and submit their answers. The server saves the received answers to a database and adds them to the knowledge graph. This allows other users to share this information.

[1710] Ad display processing

[1711] The server analyzes the user's profile information and questions to select highly relevant advertisements. These selected advertisements are sent to the user's device and displayed in specific locations within the chat interface. This allows the user to view relevant advertisements.

[1712] Implementation of an emotion engine

[1713] The emotion engine analyzes the text entered by the user and recognizes the user's emotions using natural language processing techniques (such as BERT or GPT-3). Based on the recognized emotions, the server adjusts the tone and content of the information. For example, if the server recognizes that the user is in distress, it provides additional support information and a more helpful tone in its response. The terminal displays the adjusted response and emotion indicator, allowing the user to see how their emotions are being perceived.

[1714] Specific example

[1715] 1. User registration and authentication:

[1716] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[1717] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1718] 2. Posting and answering questions:

[1719] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[1720] Terminal: Sends the question to the server.

[1721] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1722] Terminal: Displays received responses within the chat interface.

[1723] 3. Recognizing user emotions:

[1724] User: Looking confused, types, "This process is too difficult; I don't understand it."

[1725] Emotion Engine: Recognizes the user's "confusion" from the message.

[1726] Server: Generates answers with additional support information and a friendly tone.

[1727] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[1728] Through the above specific examples, this system can combine knowledge graph technology and an emotion engine to provide users with fast and accurate information, thereby improving the user experience.

[1729] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1730] Step 1:

[1731] Displaying user registration

[1732] The terminal displays an input form for the user to enter their name, email address, and password. The input form includes a "Register" button, which the user clicks to submit the entered data. Input and Output: The input is the name, email address, and password entered by the user, and the output is the transmission of this data to the server.

[1733] Step 2:

[1734] Send user information

[1735] When the user clicks the "Register" button, the terminal sends the entered information (name, email address, password) to the server. Input and Output: Input is the data entered by the user, and output is the data sent to the server.

[1736] Step 3:

[1737] User information storage

[1738] The server receives the submitted user information and stores it in a database. Specifically, it uses MySQL or PostgreSQL as the database. If the storage is successful, the server generates an initial authentication token and sends it to the user's email address. Input and Output: The input is the user's registration information, and the output is the entry stored in the database and the generated authentication token.

[1739] Step 4:

[1740] Sending an authentication token

[1741] The server sends an email containing the generated initial authentication token to the user's email address. This gives the user a link to complete the authentication process. Input and Output: The input is the generated authentication token and the user's email address, and the output is the authentication email sent to the user.

[1742] Step 5:

[1743] Display of the question input screen

[1744] The device displays a chat interface, allowing the user to enter questions using a text box. A "Send" button is also provided. Input and Output: Input is the question entered by the user, and output is the display of the chat interface on the device.

[1745] Step 6:

[1746] Submit a question

[1747] The user enters a question in the text box and clicks the "Submit" button. The terminal sends this to the server. Input and Output: The input is the question entered by the user, and the output is the question data sent to the server.

[1748] Step 7:

[1749] Query generation

[1750] The server parses the submitted question and generates a query for the knowledge graph. Specifically, if the question is "How do I write a business plan?", it will search for data related to "how to write a business plan". Input and Output: The input is the question entered by the user, and the output is the query generated for the knowledge graph.

[1751] Step 8:

[1752] Executing queries on the knowledge graph

[1753] The server executes the generated queries against the knowledge graph and retrieves relevant information. Neo4j and Amazon Neptune are commonly used as the knowledge graph. The retrieved information is structured within the server in JSON format. Input and Output: The input is the generated query, and the output is the information retrieved from the knowledge graph.

[1754] Step 9:

[1755] Submit and display of responses

[1756] The server sends structured information to the terminal in JSON format. The terminal displays the received information within the chat interface and provides answers to the user. Input and Output: The input is information obtained from the knowledge graph, and the output is the answers displayed in the chat interface.

[1757] Step 10:

[1758] Displaying questions from other users

[1759] The terminal displays questions from other users in a chat interface. Users can then type and submit their answers. Input and Output: Input is the question from another user, and output is the displayed question.

[1760] Step 11:

[1761] Enter and submit your response.

[1762] The user enters an answer to another user's question and clicks the "Submit" button. The terminal sends the entered answer to the server. Input and Output: The input is the answer entered by the user, and the output is the answer data sent to the server.

[1763] Step 12:

[1764] Save and share your answers

[1765] The server saves the received responses to the database and adds them to the knowledge graph. This allows other users to access this information. Input and Output: The input is the user's response, and the output is the entries saved in the database and updates to the knowledge graph.

[1766] Step 13:

[1767] Ad selection

[1768] The server analyzes the user's profile information and questions to select highly relevant advertisements. For example, if the question includes "business plan," it will select advertisements for business books. Input and Output: The input is the user's profile information and questions, and the output is the selected advertisement information.

[1769] Step 14:

[1770] Displaying ads

[1771] The device displays selected advertisements in specific locations within the chat interface. This allows users to view relevant advertisements. Input and Output: The input is the selected advertisement information, and the output is the advertisement displayed in the chat interface.

[1772] Step 15:

[1773] Recognition of emotions

[1774] The emotion engine analyzes text entered by the user and recognizes the user's emotions using natural language processing techniques (e.g., BERT and GPT-3). For example, it recognizes confusion from keywords such as "troubled" and "difficult." Input and Output: The input is the user's text, and the output is the recognized emotion information.

[1775] Step 16:

[1776] Coordination of information provision

[1777] The server adjusts the tone and content of information based on the recognized user's emotions. For example, it provides additional support information and a gentler tone of message to a user who is in distress. Input and Output: The input is the recognized emotion information, and the output is the adjusted response.

[1778] Step 17:

[1779] Display of emotion indicator

[1780] The device visualizes the user's emotions, as recognized by the emotion engine, and displays them as emotion indicators on the chat interface. This allows the user to see how their emotions are being perceived. Input and Output: The input is the recognized emotion information, and the output is the displayed emotion indicator.

[1781] (Application Example 2)

[1782] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1783] Traditional information provision systems merely provided information in response to user questions, failing to consider user emotions. This could lead to decreased user satisfaction and trust. Furthermore, the system did not effectively facilitate knowledge sharing among users or present relevant advertisements, limiting the quality of information provided and the effectiveness of advertising.

[1784] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1785] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for recognizing the user's emotions using an emotion engine and adjusting the tone and content of the information based on those emotions; and emotion indicator means for visualizing the results of emotion recognition to the user. This enables personalized information provision, increasing not only user satisfaction but also trust. Furthermore, by saving answers to questions from other users in a database and adding them to the knowledge graph, knowledge sharing among users is promoted. The effectiveness of advertisements can also be enhanced by selecting and displaying highly relevant advertisements based on profile information and the context of the questions.

[1786] "Knowledge graph technology" is a technique that represents data in a graph structure and organizes and displays information using nodes (individual elements of data) and edges (relationships between nodes).

[1787] "Information provision means" refers to systems and functions that provide users with the information they need.

[1788] "Query means" refers to a system or function that generates queries in a knowledge graph based on user questions and retrieves information from that knowledge graph.

[1789] "Presentation means" refers to a system or function for displaying acquired information to the user.

[1790] An "emotion engine" refers to a system or algorithm that analyzes and recognizes a user's emotions from text and audio data.

[1791] "Emotion recognition means" refers to a system or function that uses an emotion engine to recognize a user's emotions and adjusts information based on the results.

[1792] "Emotion indicator means" refers to systems or functions that visualize recognized emotions for the user.

[1793] "Storage method" refers to a system or function for saving answers to questions from other users to a database and adding them to a knowledge graph.

[1794] "Advertising display method" refers to a system or function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[1795] This invention aims to realize a system that provides personalized information to users by utilizing knowledge graph technology and an emotion engine. The necessary hardware and software configuration and each processing step for this purpose will be described.

[1796] Hardware configuration

[1797] Servers: Database server (e.g., MySQL), Application server (e.g., Node.js)

[1798] Client device: Smartphone (iOS / Android)

[1799] Software Configuration

[1800] Data analysis: Python, Knowledge graph (e.g., Neo4j)

[1801] Emotion recognition: Natural language processing libraries (NLP) and AI models (e.g., TensorFlow, Hugging Face)

[1802] Explanation of processing details

[1803] 1. User registration and authentication:

[1804] The user registers by entering their name, email address, and password. The entered data is sent to the server and stored in the database (MySQL). An authentication token is generated and sent to the user via email.

[1805] 2. Question posting and knowledge graph referencing:

[1806] The user submits a question through the chat interface. The server analyzes the question and generates a query for the knowledge graph (Neo4j). Based on the generated query, information is retrieved from the knowledge graph. The retrieved information is sent in JSON format and displayed on the smartphone.

[1807] 3. Knowledge sharing among users:

[1808] Other users' questions and answers are displayed in the chat interface. Users can type and submit their answers. The answers are stored in a database by the server and added to the knowledge graph.

[1809] 4. Emotion recognition and information provision:

[1810] The user's message is sent to an emotion engine (TensorFlow, Hugging Face) and analyzed. The emotion engine recognizes the user's emotions from the sent message, and based on the result, the server generates a response in an appropriate tone. The generated response is then provided to the user.

[1811] 5. Display of emotion indicators:

[1812] Recognized emotions are displayed as emotion indicators in the smartphone's chat interface. This allows users to see how their emotions are being perceived.

[1813] 6. Advertisement display:

[1814] The server analyzes the user's profile information and the context of the question to select the most relevant advertisements. The selected advertisements are then displayed in the chat interface.

[1815] Examples of specific cases and prompt statements

[1816] Specific example:

[1817] 1. Question posted: "Please tell me the latest movie reviews."

[1818] 2. Emotion Recognition: Recognizing the emotion "I was disappointed because the movie reviews were terrible."

[1819] Example of a prompt:

[1820] "The user has asked about the latest movie reviews and expressed disappointment. How should the system respond considering the user's emotional state?"

[1821] Based on these configurations, a system combining a knowledge graph and an emotion engine will provide users with fast and appropriate information and personalized support, resulting in a better user experience.

[1822] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1823] Step 1:

[1824] User registration and authentication

[1825] The user enters their name, email address, and password in the smartphone app and clicks the registration button.

[1826] The terminal sends the entered data to the server.

[1827] The server saves the received data to a database (MySQL) and generates an authentication token. This token is then sent to the user via email.

[1828] Input: Name, email address, password

[1829] Output: Authentication token

[1830] Step 2:

[1831] Question submission and knowledge graph reference

[1832] The user enters their question in the chat interface and clicks the send button.

[1833] The terminal sends the question data to the server.

[1834] The server analyzes the received question and generates a query against the knowledge graph (Neo4j). It executes the generated query and retrieves the necessary information from the knowledge graph. The retrieved information is sent to the terminal in JSON format. The terminal displays the retrieved information in the chat interface.

[1835] Input: User's question text

[1836] Output: Information obtained from the knowledge graph

[1837] Step 3:

[1838] Knowledge sharing among users

[1839] The device displays questions and answers from other users in a chat interface.

[1840] Users enter their answers based on their knowledge and experience and click the submit button.

[1841] The device sends the response data to the server.

[1842] The server saves the received answers to a database and adds them to the knowledge graph. The saved answers are also visible to other users, facilitating knowledge sharing.

[1843] Input: User's response text

[1844] Output: Answers stored in the database, information added to the knowledge graph.

[1845] Step 4:

[1846] Emotion recognition and information provision

[1847] The user types a message in the chat interface and clicks the send button.

[1848] The terminal sends message data to the server.

[1849] The server sends the received messages to the emotion engine (TensorFlow, Hugging Face) for analysis.

[1850] The emotion engine analyzes the user's emotions from the message and returns the results to the server.

[1851] Based on the emotion recognition results, the server generates a response in an appropriate tone, sends it to the terminal, and displays it.

[1852] Input: User's message text

[1853] Output: Emotion recognition results from the emotion engine, adjusted response

[1854] Step 5:

[1855] Display of emotion indicator

[1856] The device displays emotion indicators recognized by the emotion engine on the chat interface. This allows users to see how their emotions are being perceived.

[1857] Input: Sentiment recognition result

[1858] Output: Visual display of emotion indicators

[1859] Step 6:

[1860] Advertisement

[1861] The server analyzes the user's profile information and question data to select highly relevant advertisements.

[1862] Selected advertisements are displayed in the chat interface. Users can view relevant advertisements.

[1863] Input: User profile information, question data

[1864] Output: Advertisements displayed in the chat interface

[1865] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1866] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1867] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1868] [Fourth Embodiment]

[1869] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1870] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1871] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1872] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1873] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1874] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1875] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1876] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1877] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1878] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1879] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1880] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1881] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1882] Patent Specification

[1883] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[1884] User registration and authentication system

[1885] 1. User registration:

[1886] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[1887] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[1888] Question submission and knowledge graph reference

[1889] 1. Enter and submit your question:

[1890] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[1891] Server: Receives a question and generates a query against the knowledge graph. Executes the generated query against the knowledge graph and sends the information obtained from the knowledge graph to the terminal in JSON format.

[1892] Terminal: Displays received information within the chat interface and provides responses to the user.

[1893] Knowledge sharing among users

[1894] 1. Question and answer exchange:

[1895] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[1896] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[1897] Ad display processing

[1898] 1. Selection and display of relevant advertisements:

[1899] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1900] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[1901] Specific example:

[1902] 1. Example 1: User registration and authentication:

[1903] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[1904] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[1905] 2. Example 2: Posting and answering questions:

[1906] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[1907] Terminal: Sends the question to the server.

[1908] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[1909] Terminal: Displays received responses within the chat interface.

[1910] User knowledge sharing and ad display

[1911] 1. Example 3: Answering another user's question:

[1912] User A: Asks in the chat window, "Which marketing tool do you recommend?"

[1913] Terminal: Sends the question to the server and displays it to other users.

[1914] User B: Based on their own experience, they recommend HubSpot.

[1915] Terminal: Submit your answer and display it to other users.

[1916] Server: Saves the answer to the database and adds it to the knowledge graph.

[1917] 2. Example 4: Displaying related ads:

[1918] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[1919] Device: Selected advertisements are displayed in specific locations within the chat interface.

[1920] User: Views the displayed advertisement.

[1921] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[1922] The following describes the processing flow.

[1923] User registration and authentication system

[1924] Step 1:

[1925] Terminal: Displays a form for the user to enter their name, email address, and password.

[1926] Step 2:

[1927] User: Enter your name, email address, and password, then click the "Register" button.

[1928] Step 3:

[1929] Terminal: Sends the entered data to the server.

[1930] Step 4:

[1931] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[1932] Step 5:

[1933] User: Your account will be activated by receiving an email and clicking the verification link.

[1934] Question submission and knowledge graph reference

[1935] Step 1:

[1936] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[1937] Step 2:

[1938] User: Enter your question and click the "Submit" button.

[1939] Step 3:

[1940] Terminal: Sends the question to the server.

[1941] Step 4:

[1942] Server: Analyzes question data and generates queries for the knowledge graph.

[1943] Step 5:

[1944] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[1945] Step 6:

[1946] Server: Sends the retrieved information to the terminal in JSON format.

[1947] Step 7:

[1948] Terminal: Displays received information within the chat interface.

[1949] Step 8:

[1950] User: Check the answer in the chat interface.

[1951] Knowledge sharing among users

[1952] Step 1:

[1953] Terminal: Displays questions from other users in the chat interface.

[1954] Step 2:

[1955] User: View other users' questions and enter answers based on your own knowledge.

[1956] Step 3:

[1957] User: Enter your answer and click the "Submit" button.

[1958] Step 4:

[1959] Terminal: Sends the entered response to the server.

[1960] Step 5:

[1961] Server: Saves received responses to the database and adds them to the knowledge graph.

[1962] Step 6:

[1963] Server: Sends saved answers to the terminal so that other users can also see them.

[1964] Step 7:

[1965] Terminal: Displays new replies in other users' chat interfaces.

[1966] Ad display processing

[1967] Step 1:

[1968] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[1969] Step 2:

[1970] Server: Sends selected advertising data to the terminal in JSON format.

[1971] Step 3:

[1972] Device: Displays received advertisements in a specific location within the chat interface.

[1973] Step 4:

[1974] User: Views advertisements in a chat interface.

[1975] (Example 1)

[1976] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1977] There is a need to provide a platform where novice entrepreneurs can efficiently acquire information and share knowledge among users, as well as to appropriately display advertisements tailored to users' interests. However, it has been difficult to effectively achieve this using conventional methods.

[1978] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1979] In this invention, the server includes: an information provision means using knowledge graph technology; an inquiry means for generating queries to the knowledge graph based on user questions and retrieving corresponding information from the knowledge graph; a presentation means for providing the retrieved information to the user via a chat interface; a storage means for saving user-inputted information to a database; and an authentication means for generating an initial authentication token for the user and sending it via email. This enables novice entrepreneurs to easily and quickly obtain necessary information and facilitates the sharing of specific and useful knowledge among users. Furthermore, the effectiveness of advertisements can be maximized by displaying advertisements tailored to the user's interests.

[1980] "Knowledge graph technology" is a technique that semantically links and represents large amounts of data, enabling users to understand the relationships between those data points.

[1981] "Information provision means" refers to devices or systems that provide users with the information they seek.

[1982] A "query" is a command that attempts to inquire about information from a data repository, such as a database or knowledge graph.

[1983] A "query tool" is a device or system that generates queries based on user questions and retrieves information from databases or knowledge graphs.

[1984] A "chat interface" is a user interface that allows users to communicate in a text-based, conversational format.

[1985] "Presentation means" refers to a device or system for displaying acquired information to the user.

[1986] "Storage means" refers to devices or systems that store data entered by users or information acquired by the system.

[1987] "Authentication means" refers to devices or systems used to verify the identity of a user during registration.

[1988] An "initial authentication token" is a unique identifier used when a user logs in for the first time, and is generated to assist in the authentication process.

[1989] "Profile information" refers to a collection of personal data, such as a user's basic information, interests, and preferences.

[1990] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. The specific processing of this system's program is described below in natural language.

[1991] User registration and authentication system

[1992] User registration:

[1993] Terminal: Displays a form for the user to enter their name, email address, and password. This form is built using HTML and JavaScript. When the user clicks the "Register" button, the terminal sends that information to the server in JSON format.

[1994] Server: Uses a Java-based Spring Boot framework to receive user information. After validating the received information, it saves it to a MySQL database. If the save is successful, it generates a JWT (JSON Web Token) and sends it to the user's email address via an SMTP server.

[1995] Specific example:

[1996] Terminal: The user enters the name "Sato Ichiro", email address "ichiro@example.com", and password "password123", then clicks the "Register" button.

[1997] Server: Receives input data and saves it to the database. It also generates an initial authentication token and sends it to "ichiro@example.com".

[1998] Question submission and knowledge graph reference

[1999] Enter and submit your question:

[2000] Terminal: Provides a chat interface built using React, allowing users to type questions. When a user types a question and clicks the "Send" button, the question is sent from the terminal to the server.

[2001] Server: Uses the Spring Boot framework to parse received questions and generates queries against the knowledge graph using SPARQL or Cypher. Executes the generated queries and sends the retrieved information to the terminal in JSON format.

[2002] Specific example:

[2003] User: Type "Please teach me how to create a business model" into the chat window and click the "Send" button.

[2004] Terminal: Sends the question to the server.

[2005] Server: Queries the knowledge graph to retrieve information about "how to create a business model" and responds to the user.

[2006] Terminal: Displays received responses within the chat interface.

[2007] Knowledge sharing among users

[2008] Question and answer exchange:

[2009] Terminal: Displays questions from other users in the chat interface. For example, it can display questions in real time using Polling or WebSocket.

[2010] User: Look at other users' questions, enter an answer based on your own experience, and click the "Submit" button.

[2011] Server: Received answers are saved to a MySQL database and then added to the knowledge graph.

[2012] Specific example:

[2013] User A: Asks in the chat window, "What are some recommended marketing tools?"

[2014] Terminal: Sends the question to the server and displays it to other users.

[2015] User B: Based on their own experience, they answer, "SEO tools are useful."

[2016] Terminal: Submit your answer and display it to other users.

[2017] Server: Saves the answer to the database and adds it to the knowledge graph.

[2018] Ad display processing

[2019] Selecting and displaying relevant advertisements:

[2020] Server: Analyzes user profile information and question content to select highly relevant advertisements. For example, it uses natural language processing (NLP) techniques to analyze question content.

[2021] Device: The selected advertisement is displayed in a specific location within the chat interface. The device performs rendering to display the advertisement data.

[2022] Specific example:

[2023] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[2024] Device: Selected advertisements are displayed in specific locations within the chat interface.

[2025] User: Views the displayed advertisement.

[2026] As described above, the system of the present invention utilizes a knowledge graph based on user questions to provide information quickly and accurately, and efficiently facilitates knowledge sharing among users and advertisement delivery.

[2027] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2028] Step 1:

[2029] The user enters their name, email address, and password into an input form. For example, the user enters information into a form built with HTML and JavaScript on their device. The input is converted into JSON in the following format.

[2030] input:{

[2031] "Name": "Ichiro Sato",

[2032] "Email address": "ichiro@example.com",

[2033] "Password": "password123"

[2034] }

[2035] Output: User information in JSON format

[2036] Step 2:

[2037] When the device clicks the "Register" button, it sends this JSON-formatted user information to the server. Specifically, it uses JavaScript to send this data to the server via the HTTPS protocol.

[2038] Input: User information in JSON format

[2039] Output: HTTP request to the server

[2040] Step 3:

[2041] The server receives user information using the Spring Boot framework and performs validation. For example, it checks the validity of the email address and the strength of the password.

[2042] Input: Received user information

[2043] Output: Validation result (success or error)

[2044] Step 4:

[2045] After successful validation, the server saves the user information to the MySQL database. Transactions are managed during this process to verify the success or failure of the save operation.

[2046] Input: User information that passed validation

[2047] Output: Result of saving to the database (success or error)

[2048] Step 5:

[2049] If saving is successful, the server generates a JWT (JSON Web Token) for initial authentication. This token is associated with the user's email address.

[2050] Input: Confirmation of successful save operation

[2051] Output: Generated JWT

[2052] Step 6:

[2053] A confirmation email containing the generated JWT is sent to the user's email address. The email is sent using an SMTP server, and the success or failure of the transmission is recorded.

[2054] Input: JWT and user's email address

[2055] Output: Confirmation of sent emails

[2056] Step 7:

[2057] The user enters a question in the system's chat interface. The interface, built using React, allows the user to enter a question and click the "Send" button.

[2058] Input: User's question (e.g., "How do I create a business model?")

[2059] Output: Question data in JSON format

[2060] Step 8:

[2061] The device sends this JSON-formatted question data to the server. It sends the data via the HTTPS protocol using JavaScript.

[2062] Input: Question data in JSON format

[2063] Output: HTTP request to the server

[2064] Step 9:

[2065] The server analyzes the received question data and generates SPARQL or Cypher queries. These generated queries are then executed against the knowledge graph.

[2066] Input: Received question data

[2067] Output: The generated query and its execution result

[2068] Step 10:

[2069] The retrieved information is sent back to the terminal in JSON format. The server formats the retrieved information and sends it as an HTTP response.

[2070] Input: Execution results from Knowledge Graph

[2071] Output: Response data in JSON format

[2072] Step 11:

[2073] The device receives response data in JSON format and displays it within the chat interface. The React component parses the received data and displays it in a user-friendly format.

[2074] Input: Response data in JSON format

[2075] Output: Answer displayed on the interface

[2076] Step 12:

[2077] This feature allows users to submit answers to questions from other users. The chat interface displays other users' questions, and users can enter their answers and click the "Submit" button.

[2078] Input: Questions and answers from other users

[2079] Output: Response data in JSON format

[2080] Step 13:

[2081] The server stores the received response data in a database and then adds it to the knowledge graph. This response data can be reused in the future as information for other users' questions.

[2082] Input: Received response data

[2083] Output: Results saved to the database and knowledge graph

[2084] Step 14:

[2085] The system selects highly relevant advertisements based on the user's profile information and the content of their questions. Natural language processing (NLP) techniques are used to analyze the questions.

[2086] Input: User profile information and questions

[2087] Output: Selected ad data

[2088] Step 15:

[2089] Selected advertising data is displayed in a specific location within the chat interface. The device receives the advertising data and displays it in a location where the user can view it.

[2090] Input: Selected ad data

[2091] Output: Advertisements displayed on the interface

[2092] The above outlines the specific processing steps of the system. This system allows novice entrepreneurs to efficiently acquire information, promotes knowledge sharing among users, and displays advertisements tailored to their interests.

[2093] (Application Example 1)

[2094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2095] Traditional information systems suffer from problems such as delayed support and inaccurate information provided when users submit questions. Furthermore, knowledge sharing among users is inefficient, often resulting in biased or incomplete information. Additionally, there are limitations to the means of delivering optimal advertisements to users. There is a need to develop a system that solves these problems, providing rapid and accurate information and knowledge sharing to novice entrepreneurs, and presenting appropriate advertisements.

[2096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2097] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; advertisement presentation means for selecting highly relevant advertisements based on the content of the question and displaying the advertisements on the chat interface; storage means for saving the user's questions and answers, adding them to the knowledge graph, and displaying them to other users; and execution means as an application that operates on smartphones, smart glasses, and head-mounted displays. As a result, users can not only receive information quickly and accurately, but also efficiently share knowledge with other users and view highly relevant advertisements in a timely manner.

[2098] "Knowledge graph technology" is a technique that visualizes information entities and their interrelationships, and presents relevant information in response to user questions.

[2099] "Information provision means" refers to a function that uses a knowledge graph to provide users with the necessary information.

[2100] A "querying method" is a function that executes queries against the knowledge graph based on the user's question and retrieves the results.

[2101] "Presentation method" refers to a function that provides acquired information in a format that users can view, specifically by displaying it through a chat interface.

[2102] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's question and displays them in the chat interface.

[2103] The "storage method" refers to a function that saves user questions and answers to a database, adds them to a knowledge graph, and displays them to other users.

[2104] "Execution means" refers to the function that allows the system to run on a device such as a smartphone, smart glasses, or head-mounted display.

[2105] The system of this invention uses knowledge graph technology to provide information to novice entrepreneurs and promotes knowledge sharing among users. This system is implemented with the following configuration.

[2106] User registration and authentication system

[2107] User Registration

[2108] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[2109] Server: Receives user information and saves it to a database (such as MongoDB). If the save is successful, it generates an initial authentication token and sends it to the user via email.

[2110] Specific example

[2111] Enter the following information: Username "Yamada Taro", email address "taro@example.com", and password "password123", then click the "Register" button.

[2112] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[2113] Question submission and knowledge graph reference

[2114] Enter and submit your question

[2115] Terminal: Provides the user with a chat interface, allowing them to enter questions. When the user enters a question and clicks the "Send" button, the question is sent from the terminal to the server.

[2116] Server: Receives a question, generates and executes a query for the knowledge graph (e.g., Google Knowledge Graph API). Sends the information retrieved from the knowledge graph to the terminal in JSON format.

[2117] Terminal: Displays received information within the chat interface and provides responses to the user.

[2118] Specific example

[2119] User: Type "Please teach me how to write a business plan" into the chat interface and click the "Send" button.

[2120] Server: Queries the knowledge graph to retrieve information about "how to write a business plan" and responds to the user.

[2121] Terminal: Displays received responses within the chat interface.

[2122] Knowledge sharing among users

[2123] Question and answer exchange

[2124] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[2125] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[2126] Specific example

[2127] User A asks the chat interface, "Which marketing tool do you recommend?"

[2128] Terminal: Sends the question to the server and displays it to other users.

[2129] User B: Based on their own experience, they recommend HubSpot.

[2130] Terminal: Submit your answer and display it to other users.

[2131] Server: Saves the answer to the database and adds it to the knowledge graph.

[2132] Ad display processing

[2133] Selection and display of relevant advertisements

[2134] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[2135] Device: Selected advertisements are displayed in specific locations within the chat interface. Users can view the advertisements within the chat interface.

[2136] Specific example

[2137] Server: Based on the user's question about "marketing tools," it selects relevant advertisements.

[2138] Device: Selected advertisements are displayed in specific locations within the chat interface.

[2139] User: Views the displayed advertisement.

[2140] Example of a prompt

[2141] "Methods of raising funds when starting a business"

[2142] "Common methods of raising funds when starting a business include: 1. Funding from angel investors, 2. Crowdfunding, and 3. Venture capital."

[2143] Through this system, users can receive information quickly and accurately, efficiently share knowledge with other users, and view relevant advertisements in a timely manner.

[2144] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2145] Step 1:

[2146] The user enters their name, email address, and password on their device and clicks the "Register" button.

[2147] Input: Name, email address, password

[2148] Output: User information is sent to the server.

[2149] Action: The user enters information into a form and clicks a button.

[2150] Step 2:

[2151] The server stores the received user information in a database, generates an initial authentication token, and sends it to the user via email.

[2152] Input: User information (name, email address, password)

[2153] Output: User information stored in the database, generated authentication token

[2154] Operation: The server saves data to a database and generates a token, then uses an email server to send the token.

[2155] Step 3:

[2156] The user enters a question in the chat interface and clicks the "Send" button.

[2157] Input: Question content

[2158] Output: The question content is sent to the server.

[2159] Operation: The user enters a question into the chat interface and clicks a button.

[2160] Step 4:

[2161] The server generates and executes queries in the knowledge graph based on the questions it receives.

[2162] Input: Question content

[2163] Output: Answer data from the knowledge graph

[2164] Operation: The server processes the question, queries the Knowledge Graph API, and retrieves the answer.

[2165] Step 5:

[2166] The device displays the answers received from the knowledge graph in the chat interface.

[2167] Input: Response data from Knowledge Graph

[2168] Output: Answer displayed on the user screen

[2169] Operation: The device displays the received response on the chat interface.

[2170] Step 6:

[2171] A user enters an answer to another user's question and clicks the "Submit" button.

[2172] Input: Answer content

[2173] Output: The response content is sent to the server.

[2174] Operation: Users view other users' questions, enter answers based on their own knowledge and experience, and click the submit button.

[2175] Step 7:

[2176] The server saves the received responses to the database and adds them to the knowledge graph.

[2177] Input: Answer content

[2178] Output: Answers stored in the database, information added to the knowledge graph.

[2179] Operation: The server saves the answers to the database and adds the information to the knowledge graph.

[2180] Step 8:

[2181] The server analyzes the user's profile information and questions to select highly relevant advertisements.

[2182] Input: Profile information, Question content

[2183] Output: Selected ad data

[2184] Operation: The server analyzes user information and questions, and selects the most suitable advertisement from the advertising database.

[2185] Step 9:

[2186] The system displays selected advertisements in the chat interface.

[2187] Input: Selected ad data

[2188] Output: Advertisements displayed in the chat interface

[2189] Operation: Displays the advertising data received by the device on the chat interface, making it viewable by the user.

[2190] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2191] Patent Specification

[2192] The system of this invention provides information using knowledge graph technology and promotes knowledge sharing among users. Furthermore, by combining it with an emotion engine that recognizes user emotions, it achieves more personalized information delivery and an improved user experience. The specific processing of the program of this system is described below in natural language.

[2193] User registration and authentication system

[2194] 1. User registration:

[2195] Terminal: Displays a form for the user to enter their name, email address, and password. When the user clicks the "Register" button, the terminal sends that information to the server.

[2196] Server: Receives user information and saves it to the database. If the save is successful, it generates an initial authentication token and sends it to the user via email.

[2197] Question submission and knowledge graph reference

[2198] 1. Enter and submit your question:

[2199] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[2200] User: Enter your question and click the "Submit" button.

[2201] Terminal: Sends the question to the server.

[2202] 1. Generating queries to the knowledge graph:

[2203] Server: Analyzes question data and generates queries for the knowledge graph. Executes the generated queries on the knowledge graph and retrieves appropriate information from it.

[2204] Server: Sends the retrieved information to the terminal in JSON format.

[2205] Terminal: Displays received information within the chat interface and provides responses to the user.

[2206] Knowledge sharing among users

[2207] 1. Question and answer exchange:

[2208] Terminal: Displays questions from other users in the chat interface. Users can view other users' questions, enter answers based on their own experience and knowledge, and submit them.

[2209] Server: Saves received answers to the database and adds them to the knowledge graph. Saved answers are also made visible to other users.

[2210] Ad display processing

[2211] 1. Selection and display of relevant advertisements:

[2212] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[2213] Device: Selected advertisements are displayed in specific locations within the chat interface.

[2214] User: Advertisements can be viewed through the chat interface.

[2215] Implementation of an emotion engine

[2216] 1. Emotion recognition and information provision:

[2217] Emotion Engine: Analyzes the text of questions and messages entered by the user to recognize the user's emotions (e.g., joy, sadness, anger, etc.).

[2218] Server: Adjusts the tone and content of information based on the perceived emotions of the user. For example, if the server perceives that the user is in distress, it provides additional support.

[2219] 1. Adjusting responses based on emotions:

[2220] Server: Uses templates and guidelines to adjust the tone and content of responses according to the user's emotions. Based on the user's emotions recognized by the emotion engine, it generates responses in an appropriate tone.

[2221] Terminal: Displays the adjusted response within the chat interface.

[2222] 1. Display of emotion indicators:

[2223] Terminal: Visualizes the user's emotions as recognized by the emotion engine and displays them as emotion indicators on the chat interface. This allows users to see how their emotions are being perceived.

[2224] Specific example:

[2225] 1. Example 1: User registration and authentication:

[2226] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[2227] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[2228] 2. Example 2: Posting and answering questions:

[2229] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[2230] Terminal: Sends the question to the server.

[2231] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[2232] Terminal: Displays received responses within the chat interface.

[2233] 3. Example 3: Recognizing user emotions:

[2234] User: Looking confused, types, "This process is too difficult; I don't understand it."

[2235] Emotion Engine: Recognizes the user's "confusion" from the message.

[2236] Server: Generates answers with additional support information and a friendly tone.

[2237] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[2238] As described above, the system of the present invention combines knowledge graph technology and an emotion engine to provide users with rapid and accurate information, as well as personalized services to improve the user experience.

[2239] The following describes the processing flow.

[2240] User registration and authentication system

[2241] Step 1:

[2242] Terminal: Displays a form for the user to enter their name, email address, and password.

[2243] Step 2:

[2244] User: Enter your name, email address, and password, then click the "Register" button.

[2245] Step 3:

[2246] Terminal: Sends the entered data to the server.

[2247] Step 4:

[2248] Server: Stores the received user information in the database. Generates an initial authentication token and sends it to the user's email address.

[2249] Step 5:

[2250] User: Your account will be activated by receiving an email and clicking the verification link.

[2251] Question submission and knowledge graph reference

[2252] Step 1:

[2253] Terminal: Displays a chat interface to the user and provides a text box for entering questions.

[2254] Step 2:

[2255] User: Enter your question and click the "Submit" button.

[2256] Step 3:

[2257] Terminal: Sends the question to the server.

[2258] Step 4:

[2259] Server: Analyzes question data and generates queries for the knowledge graph.

[2260] Step 5:

[2261] Server: Executes the generated query on the knowledge graph and retrieves the appropriate information from the knowledge graph.

[2262] Step 6:

[2263] Server: Sends the retrieved information to the terminal in JSON format.

[2264] Step 7:

[2265] Terminal: Displays received information within the chat interface.

[2266] Step 8:

[2267] User: Check the answer in the chat interface.

[2268] Knowledge sharing among users

[2269] Step 1:

[2270] Terminal: Displays questions from other users in the chat interface.

[2271] Step 2:

[2272] User: View other users' questions and enter answers based on your own knowledge.

[2273] Step 3:

[2274] User: Enter your answer and click the "Submit" button.

[2275] Step 4:

[2276] Terminal: Sends the entered response to the server.

[2277] Step 5:

[2278] Server: Saves received responses to the database and adds them to the knowledge graph.

[2279] Step 6:

[2280] Server: Sends saved answers to the terminal so that other users can also see them.

[2281] Step 7:

[2282] Terminal: Displays new replies in other users' chat interfaces.

[2283] Ad display processing

[2284] Step 1:

[2285] Server: Analyzes user profile information and questions to select highly relevant advertisements.

[2286] Step 2:

[2287] Server: Sends selected advertising data to the terminal in JSON format.

[2288] Step 3:

[2289] Device: Displays received advertisements in a specific location within the chat interface.

[2290] Step 4:

[2291] User: Views advertisements in a chat interface.

[2292] Implementation of an emotion engine

[2293] Step 1:

[2294] Terminal: Sends the message entered by the user to the emotion engine.

[2295] Step 2:

[2296] Emotion Engine: Analyzes user input messages and recognizes emotions (e.g., joy, confusion, anger).

[2297] Step 3:

[2298] Server: Based on emotional information received from the emotion engine, adjusts the tone of the information and responses provided.

[2299] Step 4:

[2300] Terminal: Displays the adjusted response within the chat interface.

[2301] Step 5:

[2302] Terminal: Visualizes the emotions of recognized users and displays them as emotion indicators on the chat interface.

[2303] Step 6:

[2304] User: Check the displayed emotion indicator to see how your emotions are being perceived.

[2305] (Example 2)

[2306] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2307] Information provision systems using knowledge graph technology are required not only to provide answers to questions, but also to provide personalized information based on the user's emotions. However, conventional systems lack the functionality to recognize and respond to user emotions, resulting in a lack of improvement in the user experience. Furthermore, there is a need for a means to efficiently display highly relevant advertisements while promoting knowledge sharing among users. This invention aims to solve these problems.

[2308] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2309] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for analyzing text entered by the user and recognizing emotions; and emotion adaptation means for adjusting responses based on recognized emotions and providing personalized information. This enables not only quick and accurate answers to user questions but also personalized information provision that takes user emotions into consideration. Furthermore, it facilitates knowledge sharing among users and enables the efficient display of highly relevant advertisements.

[2310] A "knowledge graph" is a structured graph of knowledge that shows the relationships between data, and it is a technology that systematically organizes information and allows for quick retrieval of information through queries.

[2311] "Information provision means" refers to a part of a system that uses knowledge graph technology to provide users with necessary information.

[2312] A "querying method" is a function that generates queries to the knowledge graph based on the user's question and retrieves corresponding information from the knowledge graph.

[2313] A "presentation means" is a function that provides an interface for displaying acquired information to the user.

[2314] An "emotion recognition tool" is a function that analyzes text entered by the user to recognize the user's emotions.

[2315] "Emotional adaptation mechanisms" are functions that adjust responses based on recognized emotions and provide personalized information to users.

[2316] "Storage method" refers to a function that saves answers to questions from other users to a database and adds them to the knowledge graph.

[2317] "Advertising display method" refers to a function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[2318] This system combines knowledge graph technology and an emotion engine to provide users with personalized information, promote knowledge sharing among users, and display highly relevant advertisements. The following describes a specific implementation of this system.

[2319] User registration and authentication system

[2320] The terminal displays a form for the user to enter their name, email address, and password. Once the user submits the information, the server receives it and stores it in a database. For example, MySQL or PostgreSQL can be used for the database. Upon successful saving, the server generates an initial authentication token and sends it to the user's email address. This process allows the user to obtain an authentication link and complete the registration.

[2321] Question submission and knowledge graph reference

[2322] The terminal displays a chat interface, allowing the user to enter a question. Once the user enters and submits a question, the terminal sends it to the server. The server parses the question and generates a query against a knowledge graph. Examples of knowledge graphs that can be used include Neo4j and Amazon Neptune. The generated query is executed to retrieve the appropriate information. The retrieved information is sent to the terminal in JSON format, and the terminal displays the information within the chat interface.

[2323] Knowledge sharing among users

[2324] The terminal displays questions from other users, and users can enter and submit their answers. The server saves the received answers to a database and adds them to the knowledge graph. This allows other users to share this information.

[2325] Ad display processing

[2326] The server analyzes the user's profile information and questions to select highly relevant advertisements. These selected advertisements are sent to the user's device and displayed in specific locations within the chat interface. This allows the user to view relevant advertisements.

[2327] Implementation of an emotion engine

[2328] The emotion engine analyzes the text entered by the user and recognizes the user's emotions using natural language processing techniques (such as BERT or GPT-3). Based on the recognized emotions, the server adjusts the tone and content of the information. For example, if the server recognizes that the user is in distress, it provides additional support information and a more helpful tone in its response. The terminal displays the adjusted response and emotion indicator, allowing the user to see how their emotions are being perceived.

[2329] Specific example

[2330] 1. User registration and authentication:

[2331] Terminal: The user enters the name "Taro Yamada", email address "taro@example.com", and password "password123", then clicks the "Register" button.

[2332] Server: Receives input data and saves it to the database. It also generates an initial login token and sends it to "taro@example.com".

[2333] 2. Posting and answering questions:

[2334] User: Type "Please teach me how to write a business plan" into the chat window and click the "Send" button.

[2335] Terminal: Sends the question to the server.

[2336] Server: Querys the knowledge graph to retrieve information about "How to write a business plan" and responds to the user.

[2337] Terminal: Displays received responses within the chat interface.

[2338] 3. Recognizing user emotions:

[2339] User: Looking confused, types, "This process is too difficult; I don't understand it."

[2340] Emotion Engine: Recognizes the user's "confusion" from the message.

[2341] Server: Generates answers with additional support information and a friendly tone.

[2342] Device: Displays responses and emotion indicators adjusted to the appropriate tone.

[2343] Through the above specific examples, this system can combine knowledge graph technology and an emotion engine to provide users with fast and accurate information, thereby improving the user experience.

[2344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2345] Step 1:

[2346] Displaying user registration

[2347] The terminal displays an input form for the user to enter their name, email address, and password. The input form includes a "Register" button, which the user clicks to submit the entered data. Input and Output: The input is the name, email address, and password entered by the user, and the output is the transmission of this data to the server.

[2348] Step 2:

[2349] Send user information

[2350] When the user clicks the "Register" button, the terminal sends the entered information (name, email address, password) to the server. Input and Output: Input is the data entered by the user, and output is the data sent to the server.

[2351] Step 3:

[2352] User information storage

[2353] The server receives the submitted user information and stores it in a database. Specifically, it uses MySQL or PostgreSQL as the database. If the storage is successful, the server generates an initial authentication token and sends it to the user's email address. Input and Output: The input is the user's registration information, and the output is the entry stored in the database and the generated authentication token.

[2354] Step 4:

[2355] Sending an authentication token

[2356] The server sends an email containing the generated initial authentication token to the user's email address. This gives the user a link to complete the authentication process. Input and Output: The input is the generated authentication token and the user's email address, and the output is the authentication email sent to the user.

[2357] Step 5:

[2358] Display of the question input screen

[2359] The device displays a chat interface, allowing the user to enter questions using a text box. A "Send" button is also provided. Input and Output: Input is the question entered by the user, and output is the display of the chat interface on the device.

[2360] Step 6:

[2361] Submit a question

[2362] The user enters a question in the text box and clicks the "Submit" button. The terminal sends this to the server. Input and Output: The input is the question entered by the user, and the output is the question data sent to the server.

[2363] Step 7:

[2364] Query generation

[2365] The server parses the submitted question and generates a query for the knowledge graph. Specifically, if the question is "How do I write a business plan?", it will search for data related to "how to write a business plan". Input and Output: The input is the question entered by the user, and the output is the query generated for the knowledge graph.

[2366] Step 8:

[2367] Executing queries on the knowledge graph

[2368] The server executes the generated queries against the knowledge graph and retrieves relevant information. Neo4j and Amazon Neptune are commonly used as the knowledge graph. The retrieved information is structured within the server in JSON format. Input and Output: The input is the generated query, and the output is the information retrieved from the knowledge graph.

[2369] Step 9:

[2370] Submit and display of responses

[2371] The server sends structured information to the terminal in JSON format. The terminal displays the received information within the chat interface and provides answers to the user. Input and Output: The input is information obtained from the knowledge graph, and the output is the answers displayed in the chat interface.

[2372] Step 10:

[2373] Displaying questions from other users

[2374] The terminal displays questions from other users in a chat interface. Users can then type and submit their answers. Input and Output: Input is the question from another user, and output is the displayed question.

[2375] Step 11:

[2376] Enter and submit your response.

[2377] The user enters an answer to another user's question and clicks the "Submit" button. The terminal sends the entered answer to the server. Input and Output: The input is the answer entered by the user, and the output is the answer data sent to the server.

[2378] Step 12:

[2379] Save and share your answers

[2380] The server saves the received responses to the database and adds them to the knowledge graph. This allows other users to access this information. Input and Output: The input is the user's response, and the output is the entries saved in the database and updates to the knowledge graph.

[2381] Step 13:

[2382] Ad selection

[2383] The server analyzes the user's profile information and questions to select highly relevant advertisements. For example, if the question includes "business plan," it will select advertisements for business books. Input and Output: The input is the user's profile information and questions, and the output is the selected advertisement information.

[2384] Step 14:

[2385] Displaying ads

[2386] The device displays selected advertisements in specific locations within the chat interface. This allows users to view relevant advertisements. Input and Output: The input is the selected advertisement information, and the output is the advertisement displayed in the chat interface.

[2387] Step 15:

[2388] Recognition of emotions

[2389] The emotion engine analyzes text entered by the user and recognizes the user's emotions using natural language processing techniques (e.g., BERT and GPT-3). For example, it recognizes confusion from keywords such as "troubled" and "difficult." Input and Output: The input is the user's text, and the output is the recognized emotion information.

[2390] Step 16:

[2391] Coordination of information provision

[2392] The server adjusts the tone and content of information based on the recognized user's emotions. For example, it provides additional support information and a gentler tone of message to a user who is in distress. Input and Output: The input is the recognized emotion information, and the output is the adjusted response.

[2393] Step 17:

[2394] Display of emotion indicator

[2395] The device visualizes the user's emotions, as recognized by the emotion engine, and displays them as emotion indicators on the chat interface. This allows the user to see how their emotions are being perceived. Input and Output: The input is the recognized emotion information, and the output is the displayed emotion indicator.

[2396] (Application Example 2)

[2397] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2398] Traditional information provision systems merely provided information in response to user questions, failing to consider user emotions. This could lead to decreased user satisfaction and trust. Furthermore, the system did not effectively facilitate knowledge sharing among users or present relevant advertisements, limiting the quality of information provided and the effectiveness of advertising.

[2399] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2400] In this invention, the server includes: information provision means using knowledge graph technology; query means for generating queries to the knowledge graph based on user questions and obtaining corresponding information from the knowledge graph; presentation means for providing the obtained information to the user via a chat interface; emotion recognition means for recognizing the user's emotions using an emotion engine and adjusting the tone and content of the information based on those emotions; and emotion indicator means for visualizing the results of emotion recognition to the user. This enables personalized information provision, increasing not only user satisfaction but also trust. Furthermore, by saving answers to questions from other users in a database and adding them to the knowledge graph, knowledge sharing among users is promoted. The effectiveness of advertisements can also be enhanced by selecting and displaying highly relevant advertisements based on profile information and the context of the questions.

[2401] "Knowledge graph technology" is a technique that represents data in a graph structure and organizes and displays information using nodes (individual elements of data) and edges (relationships between nodes).

[2402] "Information provision means" refers to systems and functions that provide users with the information they need.

[2403] "Query means" refers to a system or function that generates queries in a knowledge graph based on user questions and retrieves information from that knowledge graph.

[2404] "Presentation means" refers to a system or function for displaying acquired information to the user.

[2405] An "emotion engine" refers to a system or algorithm that analyzes and recognizes a user's emotions from text and audio data.

[2406] "Emotion recognition means" refers to a system or function that uses an emotion engine to recognize a user's emotions and adjusts information based on the results.

[2407] "Emotion indicator means" refers to systems or functions that visualize recognized emotions for the user.

[2408] "Storage method" refers to a system or function for saving answers to questions from other users to a database and adding them to a knowledge graph.

[2409] "Advertising display method" refers to a system or function that selects highly relevant advertisements based on the user's profile information and the context of their question, and displays them in the chat interface.

[2410] This invention aims to realize a system that provides personalized information to users by utilizing knowledge graph technology and an emotion engine. The necessary hardware and software configuration and each processing step for this purpose will be described.

[2411] Hardware configuration

[2412] Servers: Database server (e.g., MySQL), Application server (e.g., Node.js)

[2413] Client device: Smartphone (iOS / Android)

[2414] Software Configuration

[2415] Data analysis: Python, Knowledge graph (e.g., Neo4j)

[2416] Emotion recognition: Natural language processing libraries (NLP) and AI models (e.g., TensorFlow, Hugging Face)

[2417] Explanation of processing details

[2418] 1. User registration and authentication:

[2419] The user registers by entering their name, email address, and password. The entered data is sent to the server and stored in the database (MySQL). An authentication token is generated and sent to the user via email.

[2420] 2. Question posting and knowledge graph referencing:

[2421] The user submits a question through the chat interface. The server analyzes the question and generates a query for the knowledge graph (Neo4j). Based on the generated query, information is retrieved from the knowledge graph. The retrieved information is sent in JSON format and displayed on the smartphone.

[2422] 3. Knowledge sharing among users:

[2423] Other users' questions and answers are displayed in the chat interface. Users can type and submit their answers. The answers are stored in a database by the server and added to the knowledge graph.

[2424] 4. Emotion recognition and information provision:

[2425] The user's message is sent to an emotion engine (TensorFlow, Hugging Face) and analyzed. The emotion engine recognizes the user's emotions from the sent message, and based on the result, the server generates a response in an appropriate tone. The generated response is then provided to the user.

[2426] 5. Display of emotion indicators:

[2427] Recognized emotions are displayed as emotion indicators in the smartphone's chat interface. This allows users to see how their emotions are being perceived.

[2428] 6. Advertisement display:

[2429] The server analyzes the user's profile information and the context of the question to select the most relevant advertisements. The selected advertisements are then displayed in the chat interface.

[2430] Examples of specific cases and prompt statements

[2431] Specific example:

[2432] 1. Question posted: "Please tell me the latest movie reviews."

[2433] 2. Emotion Recognition: Recognizing the emotion "I was disappointed because the movie reviews were terrible."

[2434] Example of a prompt:

[2435] "The user has asked about the latest movie reviews and expressed disappointment. How should the system respond considering the user's emotional state?"

[2436] Based on these configurations, a system combining a knowledge graph and an emotion engine will provide users with fast and appropriate information and personalized support, resulting in a better user experience.

[2437] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2438] Step 1:

[2439] User registration and authentication

[2440] The user enters their name, email address, and password in the smartphone app and clicks the registration button.

[2441] The terminal sends the entered data to the server.

[2442] The server saves the received data to a database (MySQL) and generates an authentication token. This token is then sent to the user via email.

[2443] Input: Name, email address, password

[2444] Output: Authentication token

[2445] Step 2:

[2446] Question submission and knowledge graph reference

[2447] The user enters their question in the chat interface and clicks the send button.

[2448] The terminal sends the question data to the server.

[2449] The server analyzes the received question and generates a query against the knowledge graph (Neo4j). It executes the generated query and retrieves the necessary information from the knowledge graph. The retrieved information is sent to the terminal in JSON format. The terminal displays the retrieved information in the chat interface.

[2450] Input: User's question text

[2451] Output: Information obtained from the knowledge graph

[2452] Step 3:

[2453] Knowledge sharing among users

[2454] The device displays questions and answers from other users in a chat interface.

[2455] Users enter their answers based on their knowledge and experience and click the submit button.

[2456] The device sends the response data to the server.

[2457] The server saves the received answers to a database and adds them to the knowledge graph. The saved answers are also visible to other users, facilitating knowledge sharing.

[2458] Input: User's response text

[2459] Output: Answers stored in the database, information added to the knowledge graph.

[2460] Step 4:

[2461] Emotion recognition and information provision

[2462] The user types a message in the chat interface and clicks the send button.

[2463] The terminal sends message data to the server.

[2464] The server sends the received messages to the emotion engine (TensorFlow, Hugging Face) for analysis.

[2465] The emotion engine analyzes the user's emotions from the message and returns the results to the server.

[2466] Based on the emotion recognition results, the server generates a response in an appropriate tone, sends it to the terminal, and displays it.

[2467] Input: User's message text

[2468] Output: Emotion recognition results from the emotion engine, adjusted response

[2469] Step 5:

[2470] Display of emotion indicator

[2471] The device displays emotion indicators recognized by the emotion engine on the chat interface. This allows users to see how their emotions are being perceived.

[2472] Input: Sentiment recognition result

[2473] Output: Visual display of emotion indicators

[2474] Step 6:

[2475] Advertisement

[2476] The server analyzes the user's profile information and question data to select highly relevant advertisements.

[2477] Selected advertisements are displayed in the chat interface. Users can view relevant advertisements.

[2478] Input: User profile information, question data

[2479] Output: Advertisements displayed in the chat interface

[2480] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2481] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2482] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2483] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2484] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2485] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2486] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2487] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2488] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2489] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2490] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2491] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2492] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2493] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2494] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2495] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2496] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2497] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2498] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2499] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2500] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2501] The following is further disclosed regarding the embodiments described above.

[2502] (Claim 1)

[2503] Information provision methods using knowledge graph technology,

[2504] A query mechanism for generating queries in a knowledge graph based on user questions and retrieving corresponding information from the knowledge graph,

[2505] A means of providing acquired information to the user via a chat interface,

[2506] A system that includes this.

[2507] (Claim 2)

[2508] The system according to claim 1, further comprising storage means f...

Claims

1. Information provision methods using knowledge graph technology, A query mechanism for generating queries in a knowledge graph based on user questions and retrieving corresponding information from the knowledge graph, A means of providing acquired information to the user via a chat interface, A system that includes this.

2. The system according to claim 1, further comprising storage means for storing answers to questions from other users in a database and adding said answers to a knowledge graph.

3. The system according to claim 1, further comprising an advertising presentation means for selecting highly relevant advertisements based on the user's profile information and the context of the question, and displaying said advertisements in the chat interface.

4. The system according to claim 1, further comprising authentication means for storing user authentication information in a database and generating and sending an initial authentication token to the user.

5. The system according to claim 1, further comprising a sharing means for providing answers to questions from other users in order to share knowledge among users.

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