system

Abstract

Provide a system. [Solution] a means for providing an interface for user access; a means for receiving input from a user and transmitting it to a server; a means for passing input to a natural language processing engine for analysis and answer generation; a means of receiving and presenting the answers to the user; A system including:

Description

[Technical Field]

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

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

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

[0004] For most people, buying and selling real estate is a major purchase that they rarely make in their lifetime, and the process requires a huge amount of time and effort. As a result, users are often anxious and need to seek the advice of experts as they go along. However, current systems lack the functionality to provide fair and individual support to users, which often results in users not receiving enough information and increasing their anxiety. The purpose of this invention is to develop a system that alleviates users' anxieties and questions regarding real estate buying and selling, and provides efficient and fair support. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including the following means: means for providing an interface accessed by a user, means for receiving input from a user and sending it to a server, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving the answer and presenting it to the user, means for comparing the analysis results with the user's history and desired conditions and adding related information, and means for comparing the user's authentication information with a database and issuing an authentication token. This system makes it possible to support users efficiently and fairly, allowing users to quickly obtain the information they need and reducing their anxiety when buying and selling real estate.

[0006] "Interface" refers to the entire screen and input means by which a user interacts with a system.

[0007] "User" refers to any individual or legal entity that uses the System to obtain information regarding real estate transactions.

[0008] "User Input" means text or other input submitted by a user to the system through an interface.

[0009] A "server" refers to a computer system that receives input from a user, processes it, and returns the results.

[0010] A "natural language processing engine" refers to a data processing system that analyzes input text from a user, understands its meaning, and generates an appropriate answer.

[0011] "Parsing" refers to the process by which a natural language processing engine understands the content of text input from a user.

[0012] "Answer generation" refers to the process by which a natural language processing engine creates an appropriate answer for a user's inquiry based on the analysis results.

[0013] "Means for presenting to the user" refers to a display method or display device for presenting the generated answers to the user in an easy-to-see manner.

[0014] "User history" refers to the record of inquiries and actions a user has taken in the past using the system.

[0015] "Desired conditions" refers to the requests and conditions related to real estate entered by the user.

[0016] "Relevant information" refers to additional information that is relevant and useful to the user's inquiry.

[0017] "Authentication information" refers to the identification information used by a user when initially registering or logging into the system.

[0018] "Database" means an information management system for storing User credentials and other related data.

[0019] An "authentication token" is a digital key that proves that a user has been properly authenticated and allows the session to continue. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] This invention realizes a real estate buying and selling support system called "Smart Consulting." The purpose of this system is to provide fair and efficient support when users obtain information and support regarding real estate buying and selling.

[0042] System configuration

[0043] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[0044] Program processing

[0045] The operation of the system is described below.

[0046] 1. User authentication and initial setup

[0047] Users access "Smart Consult" through a web browser or smartphone app and first log in or register. The device accepts this operation and sends the entered information to the server. The server compares the information with information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard.

[0048] 2. Enter and submit your question

[0049] Users can input real estate-related questions or inquiries into the chat box. For example, if a user types a question like "What are the interest rates for a mortgage?", the device sends this input to the server. The server then passes the input question to a natural language processing engine for analysis.

[0050] 3. Question Analysis and Answer Generation

[0051] The natural language processing engine analyzes the intent of the user's question. Based on the results of this analysis, it generates the most appropriate answer. For example, in response to a question about mortgage interest rates, it generates the answer, "Current mortgage interest rates average around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0052] 4. Sending the answer and showing it to the user

[0053] The server sends the generated answer to the device, which displays it on the user's screen, allowing the user to review the information and ask further questions if necessary.

[0054] Specific examples

[0055] First-Time User Scenario

[0056] 1. User: Download the smartphone app and open it for the first time.

[0057] 2. Device: Display the new registration screen.

[0058] 3. User: Enter your name, email address, and password and submit.

[0059] 4. Device: Sends user information to the server.

[0060] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[0061] 6. Terminal: Displays the dashboard and guides you through the available functions.

[0062] Question-answering scenario

[0063] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[0064] 2. Terminal: Sends the entered question to the server.

[0065] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0066] 4. Server: Sends the generated answer to the device.

[0067] 5. Terminal: Display the answer on the user's screen.

[0068] 6. User: Check the displayed information and consider your next action.

[0069] This system provides users with information efficiently and fairly, helping to alleviate their concerns and support their decision-making. In particular, it is capable of providing detailed and accurate information quickly to support the major decision of buying or selling real estate.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] Users access the system through a smartphone app or web browser, log in or register, and enter their first name, email address, and password, then click the submit button.

[0073] Step 2:

[0074] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[0075] Step 3:

[0076] If the authentication is successful, the server issues an authentication token and sends it to the terminal, which receives the token and displays the dashboard screen to the user.

[0077] Step 4:

[0078] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[0079] Step 5:

[0080] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[0081] Step 6:

[0082] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[0083] Step 7:

[0084] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0085] Step 8:

[0086] The server generates a response and sends it to the device, which displays it in the user's chat box. The user can then confirm the displayed information.

[0087] Step 9:

[0088] The user continues to ask questions as needed, for example, "Do you have any recommendations for properties with these criteria?" The device sends the new question to the server and repeats the process from step 5.

[0089] Step 10:

[0090] The server matches the user's history and preferences and adds relevant information, such as suggesting property listings in a particular area or price range based on the user's previous questions.

[0091] Step 11:

[0092] The server sends the relevant information to the device, which then presents it to the user, who then reviews the suggested information and considers their next course of action.

[0093] In this way, this system efficiently and fairly provides information in response to user questions and inquiries. Users can quickly obtain detailed information about real estate transactions, reducing their anxiety.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] When buying and selling real estate, it has been difficult for users to quickly and appropriately obtain the information they need. Conventional methods require consulting with experts, which takes time and costs money. Another issue is that it is difficult for users to efficiently obtain information that best suits their situation and desired conditions.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes a means for providing an interface for users to access, a means for receiving input from users and sending it to the server, a means for passing the input to a natural language processing engine for analysis and answer generation, a means for receiving the answer and presenting it to the user, and a means for comparing the user's authentication information with a database and issuing an authentication token. This allows users to easily ask questions or get advice about real estate, and to receive information efficiently and fairly.

[0099] "User" means any individual or entity that accesses the System and seeks information or assistance regarding real estate.

[0100] "Interface" refers to the screen and input means that users use to access and operate the system.

[0101] "Server" refers to a computer system that receives input from a user, analyzes and processes it, and returns the results to the user.

[0102] A "natural language processing engine" refers to an artificial intelligence technology that analyzes user input, understands intent, and generates appropriate answers.

[0103] "Authentication Token" refers to a digital certificate that indicates a user is authenticated when accessing a system.

[0104] "Database" refers to a system that manages and stores data such as user information, answers to questions, and history.

[0105] "Parsing" refers to the process by which a natural language processing engine understands a user's input and understands their intent.

[0106] "Answer generation" refers to the process by which a natural language processing engine creates an appropriate answer to a question.

[0107] The present invention is a system for users to obtain information and support regarding real estate transactions, and aims to provide efficient and fair support. This system is configured as follows.

[0108] System configuration

[0109] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[0110] Hardware and Software Configuration

[0111] User: Accesses the system via an internet connection using a smartphone or PC.

[0112] Terminal: A device that accepts user input and sends it to a server. Examples include smartphone apps and web browsers.

[0113] Server: Manages a database (e.g., MySQL or PostgreSQL) and uses a natural language processing engine (e.g., GPT-3 or BERT) to analyze user questions and generate answers.

[0114] Natural Language Processing Engine: Artificial intelligence techniques for understanding user input and understanding intent, such as GPT-3 and BERT.

[0115] Program processing

[0116] The system process is as follows:

[0117] User authentication and initial setup

[0118] 1. User: Access the system from a smartphone app or web browser and register or log in.

[0119] 2. Device: Sends the entered name, email address, and password to the server.

[0120] 3. Server: Compares with the database, and if authentication is successful, issues an authentication token and sends it to the terminal.

[0121] 4. Terminal: Receives the authentication token and displays the user's dashboard.

[0122] Enter and submit your question

[0123] 1. User: Type your real estate question into the chat box on the screen.

[0124] 2. Terminal: Sends a query to the server.

[0125] Parsing questions and generating answers

[0126] 1. Server: Passes the question to the natural language processing engine and requests analysis.

[0127] 2. Natural language processing engine: Analyzes the intent of the user's question and generates the most appropriate answer.

[0128] Example: To the question "What are mortgage interest rates?", the answer would be: "Current mortgage interest rates average around 2.5%. However, this can vary depending on your circumstances, so we recommend you inquire with your lender."

[0129] Sending the answer and showing it to the user

[0130] 1. Server: Sends the generated answer to the device.

[0131] 2. Terminal: Displays the received answer on the user's screen.

[0132] Specific examples

[0133] Below is an example of a prompt sentence to input to the generative AI model.

[0134] Prompt Sentence Examples

[0135] Q: A user asks, "What are the mortgage interest rates?" Generate a suitable answer to this question.

[0136] A: The current average interest rate for a home loan is around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution.

[0137] The system utilizes efficient natural language processing technology to provide users with prompt and appropriate information, thereby supporting the important decision-making process of buying and selling real estate, alleviating users' concerns and enabling them to obtain information efficiently.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1:

[0140] User: Access the system from a smartphone app or web browser and register or log in.

[0141] Input: The name, email address, and password entered by the user.

[0142] What happens: A user opens the app or browser, enters the required information, and clicks the submit button.

[0143] Output: The entered user information is passed to the terminal.

[0144] Step 2:

[0145] Terminal: Sends information entered by the user to the server.

[0146] Input: Name, email address, and password received from the user.

[0147] What it does: Input information is packaged in an appropriate format and sent to the server as an HTTP request.

[0148] Output: User information is passed to the server.

[0149] Step 3:

[0150] Server: Compares the received user information with a database.

[0151] Input: User information sent from the device.

[0152] How it works: The server compares the new user information with existing information in a database (e.g., MySQL or PostgreSQL) and authenticates them.

[0153] Output: If authentication is successful, an authentication token is generated.

[0154] Step 4:

[0155] Server: If authentication is successful, generate an authentication token and send it to the device.

[0156] Input: User information matching results.

[0157] What it does: Generates an authentication token and constructs an HTTP response to send it to the device.

[0158] Output: The authentication token is sent to the device.

[0159] Step 5:

[0160] Terminal: Receives the authentication token and displays the user's dashboard.

[0161] Input: The received authentication token.

[0162] What it does: Stores the authentication token and displays the dashboard screen to the user.

[0163] Output: The user's dashboard screen is displayed.

[0164] Step 6:

[0165] User: Type your real estate question into the chat box on the screen.

[0166] Input: The question the user types into the chat box.

[0167] Action: Enter a question and click the submit button.

[0168] Output: The entered question is sent to the terminal.

[0169] Step 7:

[0170] Terminal: Sends the entered question to the server.

[0171] Input: The question received from the user.

[0172] What it does: Packages the question into an appropriate format and sends it to the server as an HTTP request.

[0173] Output: The question is passed to the server.

[0174] Step 8:

[0175] Server: Passes the received question to the natural language processing engine and requests analysis.

[0176] Input: Question sent from terminal.

[0177] How it works: A question is fed into a generative AI model (such as GPT-3 or BERT), which analyzes it and generates an answer.

[0178] Output: The generated answer is sent back to the server.

[0179] Step 9:

[0180] Server: Sends the generated answer to the device.

[0181] Input: The answer returned by the natural language processing engine.

[0182] What it does: Constructs the answer as an HTTP response and sends it to the device.

[0183] Output: The answer is sent to the terminal.

[0184] Step 10:

[0185] Terminal: Displays the received answer on the user's screen.

[0186] Input: The answer sent by the server.

[0187] What it does: Displays the answer on the screen for the user to review.

[0188] Output: The answer is displayed on the user's screen.

[0189] These are the specific processing steps of the system, which allows users to get fast and accurate answers to their real estate questions.

[0190] (Application example 1)

[0191] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0192] Conventional real estate purchase and sale support systems have difficulty in providing users with the information they need quickly and appropriately, and a solution that provides efficient, fair, and detailed information is needed. In addition, there is a lack of means for users to resolve their questions and concerns in real time, so technology that can quickly support users in making decisions is needed.

[0193] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0194] In this invention, the server includes means for providing a display device accessed by a user, means for receiving input from the user and sending it to a processing device, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving the generated answer and presenting it to the user, and means for linking with a database for adding related information based on the analysis results, thereby enabling users to obtain real estate information in real time and make decisions quickly.

[0195] A "display device" is a device that allows a user to visually confirm information.

[0196] A "processor" is a device for receiving input from a user and analyzing and processing it.

[0197] A "natural language processing engine" is a system and software that analyzes text data, understands the user's intent, and generates appropriate answers.

[0198] A "generated answer" is information provided as a result of analysis by a natural language processing engine.

[0199] A "database" is a system that stores user history and related information and provides that information as needed.

[0200] "User history" refers to a record of searches and entries made by a user in the past, as well as any related information.

[0201] "Desired conditions" are specific requirements or conditions that a user specifies when providing information about a property.

[0202] "Authentication Token" means a piece of authentication information that uniquely identifies a user and is issued to the user when the user accesses a system.

[0203] "Surrounding environment information" refers to information about facilities and transportation methods around the real estate property.

[0204] "Additional information" is supplementary information that is deemed highly relevant based on the user's input and history.

[0205] This invention aims to realize a real estate buying and selling support system called "Smart Consulting Real Estate Assistant (Store Version)." The purpose of this system is to enable users to obtain real estate information in real time at a physical store and receive fair and efficient support.

[0206] System configuration

[0207] The system includes a display device accessed by a user, a means for transmitting input from the user to a processing device, a natural language processing engine for analysis and answer generation, a means for providing the generated answer, and a database for linking related information.

[0208] The hardware used includes tablets, smart glasses, and head-mounted displays, which are used as display devices for users to directly view information. Servers and databases are used to receive, process, and store user input. The software used includes natural language processing engines (e.g., Google® Cloud Natural Language API, Amazon Comprehend), authentication systems (e.g., OAuth 2.0), and UI frameworks (e.g., React Native, Flutter®).

[0209] Program processing

[0210] 1. User authentication and initial setup

[0211] The user accesses the system through a display device (tablet or smart glasses) and logs in or registers. The user's input information is sent to the server and checked against a database. If authentication is successful, an authentication token is issued and sent to the user's display device. At this stage, the user's dashboard is displayed, and available functions are explained.

[0212] 2. Enter and submit your question

[0213] The user uses the chat box to input questions or inquiries about real estate. For example, they can input, "Please tell me about the surrounding area." This input is sent from the display device to the server.

[0214] 3. Question Analysis and Answer Generation

[0215] The server receives the input question and passes it to a natural language processing engine, which analyzes the user's question and generates the most appropriate answer.

[0216] 4. Providing Additional Information

[0217] Based on the analysis results, related information is obtained from a database that links the user's history, desired conditions, and related information, such as information on nearby facilities, transportation, and the environment.

[0218] 5. View Answers

[0219] The server sends the generated answer to a display device and presents it to the user, who then checks the information and considers their next course of action.

[0220] This system is a powerful support tool that allows users to efficiently and fairly obtain real estate information in physical stores and make quick decisions.

[0221] Examples and prompts

[0222] In-store usage scenario

[0223] 1. Customer: Picks up the tablet and types, "I'd like to know about the surrounding area."

[0224] 2. Terminal: Sends a query to the server.

[0225] 3. Server: Analyzes the question using a natural language processing engine.

[0226] 4. Server: Based on the analysis results, obtain surrounding information from the database.

[0227] 5. Server: Sends the generated answer to the device.

[0228] 6. Terminal: Show the answer to the customer. For example, "There are schools, supermarkets, and train stations nearby."

[0229] 7. Visitors: Review the displayed information and explore properties that interest them further.

[0230] Example prompts for generative AI models

[0231] Sample prompt: "Please provide information about the surrounding area of ​​the property."

[0232] Example prompt: "What are the best mortgage terms?"

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1: User authentication and initial setup

[0235] 1. The user picks up a display device (tablet or smart glasses), accesses the system, and logs in or registers.

[0236] Input: Name, Email Address, Password

[0237] Processing: The input information is sent from the terminal to the server. The server checks the database to see if the user is registered. If the user is new, the new user information is saved in the database.

[0238] Output: An authentication token is issued and sent to the device.

[0239] Step 2: View the dashboard

[0240] 1. The device receives the authentication token and displays the user's dashboard.

[0241] Input: Authentication Token

[0242] Processing: The device receives the authentication token, checks the features the user has access to, and configures the dashboard.

[0243] Output: The dashboard screen is displayed.

[0244] Step 3: Enter and submit your question

[0245] 1. The user enters their real estate question or inquiry in the chat box.

[0246] Input: Questions such as "Tell me about the surrounding area"

[0247] Processing: The device sends the entered question to the server, which receives the question and prepares it for passing to the natural language processing engine.

[0248] Output: The question data is passed to a natural language processing engine.

[0249] Step 4: Parsing the question and generating an answer

[0250] 1. The server passes the question to a natural language processing engine for analysis and answer generation.

[0251] Input: User question data

[0252] Processing: A natural language processing engine (e.g., Google Cloud Natural Language API, Amazon Comprehend) analyzes the question and understands the user's intent. Based on the analysis results, it generates the most appropriate answer.

[0253] Output: The generated answer

[0254] Step 5: Obtain additional information

[0255] 1. Based on the analysis results, the server retrieves relevant information from the database.

[0256] Input: Analysis results, user history and desired conditions

[0257] Processing: The server connects to the database to search for and retrieve relevant information (such as information about the surrounding environment) based on the user's history and desired conditions.

[0258] Output: Additional relevant information

[0259] Step 6: Submit and view your answers and additional information

[0260] 1. The server sends the generated answer and any additional relevant information to the terminal.

[0261] Input: Generated answers, related information

[0262] Processing: The server aggregates the generated answers and related information and sends them to the terminal, which receives them and displays them to the user.

[0263] Output: Answers and related information displayed on the user's tablet or smart glasses

[0264] Step 7: User confirmation and further action

[0265] 1. The user reviews the displayed information and considers their next question or action.

[0266] Input: Displayed answers and related information

[0267] Processing: If the user enters an additional question, process the new input again according to steps 3 through 6.

[0268] Output: If a new question is input, a continuous question-answering cycle begins.

[0269] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0270] This invention provides more appropriate support to users by combining a real estate buying and selling support system called "Smart Consulting" with an emotion engine that recognizes user emotions. The system aims to provide fair, efficient, and emotion-responsive support when users obtain information and support related to real estate buying and selling.

[0271] System configuration

[0272] The system includes an interface accessed by the user, a means for sending user input to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, a means for comparing the user's authentication information with a database and issuing an authentication token, and an emotion engine for recognizing the user's emotions.

[0273] Program processing

[0274] The operation of the system is described below.

[0275] 1. User authentication and initial setup

[0276] The user accesses the interface and logs in or registers. The device accepts this operation and sends the entered information to the server. The server compares the information with the information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard screen.

[0277] 2. Enter and submit your question

[0278] The user enters a real estate question or inquiry into the chat box. For example, they might type, "Please tell me about mortgage interest rates." The device then sends this input to the server, which then passes the input data to a natural language processing engine for analysis.

[0279] 3. Question Analysis and Answer Generation

[0280] The natural language processing engine analyzes the intent of the user's question and generates the most appropriate answer based on the results of this analysis. For example, it creates an answer such as, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0281] 4. Recognizing emotions and adjusting responses

[0282] The emotion engine analyzes the user's input text and interaction data to assess the user's emotional state. For example, it may recognize from the user's language and frequent questions that the user is feeling anxious. Based on this, the emotion engine can adjust the content and tone of its responses and provide additional information to ease the user's anxiety.

[0283] 5. Sending the answer and showing it to the user

[0284] The server sends the generated answers and the results of the emotion engine adjustments to the device, which displays the answers in the user's chat box. The user can review this information and continue asking further questions if necessary.

[0285] Specific examples

[0286] First-Time User Scenario

[0287] 1. User: Download the smartphone app and open it for the first time.

[0288] 2. Device: Display the new registration screen.

[0289] 3. User: Enter your name, email address, and password and submit.

[0290] 4. Device: Sends user information to the server.

[0291] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[0292] 6. Terminal: Displays the dashboard and guides you through the available functions.

[0293] Question-answering scenario

[0294] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[0295] 2. Terminal: Sends the entered question to the server.

[0296] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0297] 4. Emotion Engine: Analyzes user input, recognizes when the user is feeling anxious, and generates corresponding countermeasures.

[0298] 5. Server: Sends the generated answer and adjusted information to the terminal.

[0299] 6. Device: The answer is displayed on the user's screen. The user checks the displayed information and considers their next action.

[0300] This system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, allowing it to provide more attentive support. Users can not only quickly obtain detailed information about real estate sales and purchases, but also reduce anxiety during the process.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] Users access the system through a smartphone app or web browser to register or log in. They enter their name, email address, and password and click the "Submit" button.

[0304] Step 2:

[0305] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[0306] Step 3:

[0307] If authentication is successful, the server issues an authentication token and sends it to the device. The device receives this token and displays the user's dashboard screen.

[0308] Step 4:

[0309] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[0310] Step 5:

[0311] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[0312] Step 6:

[0313] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[0314] Step 7:

[0315] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0316] Step 8:

[0317] The emotion engine analyzes user input text and interaction data to assess the user's emotional state. For example, it may recognize that the user is feeling anxious based on their language and frequent questions.

[0318] Step 9:

[0319] Based on the analysis, the sentiment engine adjusts the tone and content of the generated answers, for example, providing a more confident response to a user who is feeling anxious, with additional advice and resources.

[0320] Step 10:

[0321] The server sends the final answer and the adjustment results of the emotion engine to the device, which receives them and displays them in the user's chat box.

[0322] Step 11:

[0323] The user checks the displayed information and continues to ask questions if necessary. For example, enter the question again, "Do you have any recommended properties that meet these criteria?" The device then sends the new question to the server and repeats the process from step 5.

[0324] The above is the specific processing flow of the "Smart Consulting" system. In this way, this system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, making it possible to provide more detailed support. Not only can users quickly obtain detailed information about real estate sales and purchases, but they can also reduce their anxiety during the process.

[0325] Example 2

[0326] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0327] Conventional real estate buying and selling support systems provide efficient and accurate answers to user input, but they do not take into account the user's emotional state, which means that the system does not fully resolve the user's anxieties or questions.In addition, they do not suggest related information based on the user's history or desired conditions, which means that user convenience is not improved.

[0328] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0329] In this invention, the server includes a means for analyzing user input using a natural language processing engine and generating a response, a means for evaluating the user's emotional state based on the analysis results and adjusting the tone and content of the response, and a means for verifying the user's authentication information against a database and issuing an authentication token. This makes it possible to provide emotionally responsive support to the user and alleviate their anxieties and doubts. Furthermore, by suggesting related information based on the user's history and desired conditions, user convenience is improved.

[0330] "Interface" refers to the screen or operating section that allows users to access the system and input information.

[0331] A "natural language processing engine" refers to an algorithm or program that analyzes user input, understands its intent, and generates an answer.

[0332] An "emotion engine" refers to an algorithm or program that analyzes user input data and interactions and assesses the user's emotional state.

[0333] An "authentication token" is a temporary identification code issued when a user logs in to a system, and is used to verify the user's authentication status.

[0334] "User history" refers to the record of the user's past operations and inquiries.

[0335] "Desired conditions" refers to specific requests or conditions that a user specifies to the system.

[0336] "Tone of the answer" refers to the expression and atmosphere of the generated answer, and is a factor that determines how it is conveyed to the user.

[0337] "Related information" refers to additional useful data or suggestions provided in response to a user's question or input.

[0338] "User authentication" refers to the process of verifying that a user is a legitimate user when logging into a system.

[0339] MODE FOR CARRYING OUT THE INVENTION

[0340] The present invention provides a real estate buying and selling support system that provides more appropriate support by combining an emotion engine that recognizes the user's emotions. The system configuration and operation are described in detail below.

[0341] System Configuration

[0342] This system is configured using the following hardware and software.

[0343] User device: A device such as a PC or smartphone used by a user.

[0344] Server: A server that performs data processing, authentication, natural language processing, and emotion recognition. Specifically, this includes database servers, application servers, etc.

[0345] Database: Stores user registration information, authentication information, past interactions, historical information, etc.

[0346] Natural language processing engines: Examples include Google BERT and OpenAI® GPT-3.

[0347] Emotion engine: A program for analyzing user input text and interaction data.

[0348] Data processing and calculation

[0349] User authentication

[0350] A user accesses the interface and logs in or registers.

[0351] Terminal: The entered user information is sent to the server in JSON format.

[0352] Server: Compares the received information with the database, generates an authentication token (such as a JWT), and sends it to the device.

[0353] Enter and submit your question

[0354] The user types a question into the chat box.

[0355] Example: "What are the mortgage interest rates?"

[0356] Terminal: Sends the entered question to the server.

[0357] Question analysis and answer generation

[0358] Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0359] The natural language processing engine uses Google BERT and OpenAI GPT-3 to analyze the intent of the question and generate appropriate answers.

[0360] Example answer: "Current mortgage interest rates average around 2.5%. However, this varies depending on the terms, so we recommend checking with your financial institution."

[0361] Recognizing emotions and adjusting responses

[0362] Server: Passes the analysis results and user input to the emotion engine.

[0363] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[0364] Example: A user's frequent questions and negative language indicate anxiety.

[0365] Server: Adjusts the tone and content of the response based on the evaluation results from the emotion engine.

[0366] Example: To ease concerns, additional information is added, such as, "Don't worry. Current mortgage interest rates average around 2.5%. We recommend checking with your financial institution for details."

[0367] Providing an answer

[0368] Server: Sends the adjusted answer to the device.

[0369] Terminal: Display received responses in the chat box.

[0370] A key feature of this system is that it adjusts responses based on the user's emotional state. As a result, users not only receive detailed information about real estate transactions, but also reduce any anxiety or doubts they may have during the process. It also suggests related information based on the user's history and desired conditions, improving user convenience and satisfaction.

[0371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0372] Step 1:

[0373] Users: Access the interface and register or log in.

[0374] Enter your name, email address, and password.

[0375] Output: The user information is sent to the server.

[0376] Terminal: Sends the entered information to the server.

[0377] Specific operation: The terminal converts the input data into JSON format and sends it to the server as an API request.

[0378] Step 2:

[0379] Server: Compares the received user information with a database and performs authentication.

[0380] Input: User information in JSON format.

[0381] Output: An authentication token or an error message.

[0382] What happens: The server runs an SQL query to verify the user information and, if there is a match, generates an authentication token (such as a JWT).

[0383] Step 3:

[0384] Server: If authentication is successful, it sends an authentication token to the device. If authentication fails, it sends an error message.

[0385] Input: An authentication token or an error message.

[0386] Output: An authentication token or an error message is sent to the terminal.

[0387] Terminal: Save the received authentication token and display the dashboard screen.

[0388] Specific operation: The device stores the authentication token in a cookie or session storage.

[0389] Step 4:

[0390] User: Type your real estate question in the chat box.

[0391] Input: A question like "What are the mortgage interest rates?"

[0392] Output: The question is sent to the system.

[0393] Terminal: Sends the entered question to the server.

[0394] Specific operation: The device converts the question into JSON format and sends it to the server as an API request.

[0395] Step 5:

[0396] Server: Passes question data to a natural language processing engine for analysis and answer generation.

[0397] Input: User question data.

[0398] Output: The answer from the natural language processing engine.

[0399] Specific operation: The server sends an API request to a natural language processing engine (e.g., OpenAI GPT-3) and receives the analysis results.

[0400] Step 6:

[0401] Server: Passes the analysis results to the emotion engine to evaluate the user's emotional state.

[0402] Input: Analysis results from the natural language processing engine and user input data.

[0403] Output: Emotion evaluation results from the emotion engine.

[0404] Specific operation: The server sends the analysis results and the user's input data to the emotion engine.

[0405] Step 7:

[0406] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[0407] Input: Analysis results and user input data.

[0408] Output: Emotion evaluation result (e.g., anxiety, relief, etc.).

[0409] Specific behavior: The emotion engine analyzes the user's text and operation history to evaluate their emotional state.

[0410] Step 8:

[0411] Server: Adjust the tone and content of the response based on the sentiment assessment results.

[0412] Input: Emotion assessment results.

[0413] Output: The adjusted answer.

[0414] Specific behavior: The server appropriately adjusts the tone of the response based on the evaluation from the emotion engine.

[0415] Step 9:

[0416] Server: Sends the final adjusted answer to the device.

[0417] Input: Adjusted answer.

[0418] Output: The answer is sent to the terminal.

[0419] Terminal: Display received responses in the chat box.

[0420] Specific operation: The device analyzes the received data and displays it in the chat box.

[0421] Through these processing steps, the system provides quick and appropriate answers to the user's questions, taking into account the user's emotional state in the process, thereby reducing the user's anxiety.

[0422] (Application example 2)

[0423] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0424] Existing real estate transaction support systems do not take into account the user's emotional state, which can lead to users receiving information with feelings of anxiety or distrust. Furthermore, information provided through the dialogue interface may not be adequately matched with the user's desired conditions or history, resulting in inappropriate information being provided. Furthermore, there are issues with insufficient efficiency and security in user authentication.

[0425] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for providing an interface accessed by the user, means for receiving input from the user and sending it to the server, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving an answer and presenting it to the user, means for recognizing the user's emotions and adjusting the answer content based on the results, means for comparing the analysis results with the user's history and desired conditions based on the user's emotional state and adding related information, and means for comparing the user's authentication information with a database and issuing an authentication token. This makes it possible to provide appropriate information to the user in a timely manner, taking into account the user's emotional state.

[0426] A "user-accessible interface" is the means by which a user accesses a system and enters or views information.

[0427] "User input" is data, such as text or voice commands, that a user provides through an interface.

[0428] A "server" is a computer system that receives input from a user, processes it, and provides the results to the user.

[0429] A "natural language processing engine" is a program that analyzes input from users, understands their intent, and generates appropriate responses.

[0430] An "emotion engine" is a program that analyzes user input and interaction data to recognize the user's emotional state.

[0431] An "authentication token" is a digital key that proves that a user is authenticated when accessing a system.

[0432] The "dashboard screen" is the main screen that is displayed when a user logs in to the system and allows the user to perform operations and check information.

[0433] A "chat box" is an interactive input field where users can freely enter questions or messages.

[0434] "Adjusting the answer content" refers to the act of optimizing the generated answer according to the user's emotional state and providing the most appropriate information for the user's situation.

[0435] "Analysis results" refers to information resulting from the analysis of user input by a natural language processing engine or emotion engine.

[0436] "History and desired conditions" refers to data such as information entered by the user in the past and desired conditions.

[0437] "Related information" is supplementary or additional information provided based on the user's question or situation.

[0438] This invention is applied to a real estate sales support system called "Smart Consulting Glasses." The smart glasses, which are used by real estate consultants when dealing with customers in brick-and-mortar stores, are used to understand the user's emotional state and provide more appropriate information. The purpose of this invention is to enable users to receive fair and efficient support for specific questions and inquiries through an interactive interface.

[0439] System configuration

[0440] Hardware and Software Configuration

[0441] Hardware: smart glasses, camera, display, microphone, server.

[0442] Software: Emotion Recognition model, Transformers library (for natural language processing), OpenCV (image processing framework), Speech-to-Text engine (audio to text conversion).

[0443] Overall system flow

[0444] 1. User authentication and initial setup:

[0445] The user puts on the smart glasses and logs in or registers.

[0446] The terminal accepts this operation and transmits the input information to the server.

[0447] The server checks the authentication information against a database, generates an authentication token, and sends it to the terminal.

[0448] The device receives the authentication token and displays the dashboard screen.

[0449] 2. User input and submit question:

[0450] Users use the smart glasses interface to input real estate questions and inquiries.

[0451] For example, ask a voice question such as, "Please tell me about mortgage interest rates."

[0452] The device converts the voice into text and sends the input data to the server.

[0453] 3. Analysis and Answer Generation:

[0454] A natural language processing engine analyzes the user's question, understands their intent, and generates the most appropriate answer.

[0455] For example, generate an answer like, "Current mortgage interest rates average around 2.5%, but this can vary depending on the terms."

[0456] 4. Emotion recognition and response adjustment:

[0457] The emotion engine analyzes the user's facial expressions from camera footage and recognizes their emotional state.

[0458] If the user is perceived as feeling anxious, the emotion engine will adjust its responses based on that information.

[0459] For example, provide additional information such as "We will also provide you with detailed contact information."

[0460] 5. Submitting and Presenting Your Answers:

[0461] The server sends the generated answer and the adjusted information to the display of the smart glasses.

[0462] The user checks the information displayed on the smart glasses display and considers their next action.

[0463] Specific examples

[0464] Scenarios when users ask questions

[0465] 1. User: "What are the mortgage interest rates?"

[0466] 2. Device: Converts speech into text and sends it to the server.

[0467] 3. Server: Analyzes the question using a natural language processing engine and generates an answer.

[0468] 4. Emotion engine: Recognizes anxiety from the user's facial expressions.

[0469] 5. Server: Generates answers and additional anxiety-reducing information and sends them to the device.

[0470] 6. Terminal: Shows answers and additional information.

[0471] Prompt Sentence Examples

[0472] Q: What are the interest rates for home loans?

[0473] Expression: He looks anxious.

[0474] This system can dramatically improve the quality of real estate consulting by recognizing users' anxieties and questions in real time and providing more appropriate and satisfying information.

[0475] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0476] Step 1:

[0477] User authentication and initial setup

[0478] Input: User login information (username, password)

[0479] Data processing / calculation: The user puts on the smart glasses and logs in or registers. The device accepts this operation, captures the entered login information, and sends it to the server. The server compares it with existing authentication information in a database and generates an authentication token if authentication is successful.

[0480] Output: Authentication token

[0481] Specific behavior:

[0482] The user enters their login information through the smart glasses.

[0483] The server generates an authentication token and sends it to the device.

[0484] The device receives the authentication token and displays the user's dashboard screen.

[0485] Step 2:

[0486] Enter and submit your question

[0487] Input: A spoken question asked by the user (e.g., "What are the mortgage interest rates?")

[0488] Data processing / computation: The user asks a question by voice through the smart glasses interface. The device uses a microphone to capture the voice and converts it into text using a speech-to-text engine. The converted text data is then sent to the server.

[0489] Output: Questions converted to text

[0490] Specific behavior:

[0491] The user asks aloud, "What are the interest rates for a mortgage?"

[0492] The device captures the audio and converts it into text.

[0493] Send a textual question to the server.

[0494] Step 3:

[0495] Question analysis and answer generation

[0496] Input: Textual question data

[0497] Data processing / calculation: The server passes the textual question data to a natural language processing engine for analysis. The natural language processing engine understands the intent of the question and generates the most appropriate answer.

[0498] Output: The generated answer (e.g., "Current mortgage interest rates average around 2.5%")

[0499] Specific behavior:

[0500] The server passes the text data to a natural language processing engine.

[0501] A natural language processing engine analyzes the question and generates an appropriate answer.

[0502] Step 4:

[0503] Emotion recognition and response adjustment

[0504] Input: Camera footage, generated answers

[0505] Data processing / computation: The emotion engine processes the camera footage, analyzes the user's facial expressions for each frame, and recognizes their emotional state. Based on the emotion, the server can add additional information or adjust the tone of the generated answer.

[0506] Output: Tailored response (e.g., "We will also provide you with further contact information")

[0507] Specific behavior:

[0508] The server passes the camera images from the smart glasses to the emotion engine.

[0509] The emotion engine analyzes the user's facial expressions and recognizes that they are feeling anxious.

[0510] The server appends additional anxiety-reducing information to the response.

[0511] Step 5:

[0512] Submitting and Presenting Answers

[0513] Input: Adjusted Answer

[0514] Data processing / calculation: The server sends the adjusted answer to the smart glasses display and displays it to the user. The user confirms the presented information and considers their next action.

[0515] Output: The answer is displayed

[0516] Specific behavior:

[0517] The server sends the adjusted response to the terminal.

[0518] The device displays the answer on the smart glasses display.

[0519] The above is the specific flow and operation of each processing step of the system for realizing the application example.

[0520] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0521] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0522] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0523] [Second embodiment]

[0524] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0525] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0526] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0527] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0528] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0529] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0530] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0531] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0532] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0533] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0534] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0535] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0536] This invention realizes a real estate buying and selling support system called "Smart Consulting." The purpose of this system is to provide fair and efficient support when users obtain information and support regarding real estate buying and selling.

[0537] System configuration

[0538] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[0539] Program processing

[0540] The operation of the system is described below.

[0541] 1. User authentication and initial setup

[0542] Users access "Smart Consult" through a web browser or smartphone app and first log in or register. The device accepts this operation and sends the entered information to the server. The server compares the information with information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard.

[0543] 2. Enter and submit your question

[0544] Users can input real estate-related questions or inquiries into the chat box. For example, if a user types a question like "What are the interest rates for a mortgage?", the device sends this input to the server. The server then passes the input question to a natural language processing engine for analysis.

[0545] 3. Question Analysis and Answer Generation

[0546] The natural language processing engine analyzes the intent of the user's question. Based on the results of this analysis, it generates the most appropriate answer. For example, in response to a question about mortgage interest rates, it generates the answer, "Current mortgage interest rates average around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0547] 4. Sending the answer and showing it to the user

[0548] The server sends the generated answer to the device, which displays it on the user's screen, allowing the user to review the information and ask further questions if necessary.

[0549] Specific examples

[0550] First-Time User Scenario

[0551] 1. User: Download the smartphone app and open it for the first time.

[0552] 2. Device: Display the new registration screen.

[0553] 3. User: Enter your name, email address, and password and submit.

[0554] 4. Device: Sends user information to the server.

[0555] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[0556] 6. Terminal: Displays the dashboard and guides you through the available functions.

[0557] Question-answering scenario

[0558] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[0559] 2. Terminal: Sends the entered question to the server.

[0560] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0561] 4. Server: Sends the generated answer to the device.

[0562] 5. Terminal: Display the answer on the user's screen.

[0563] 6. User: Check the displayed information and consider your next action.

[0564] This system provides users with information efficiently and fairly, helping to alleviate their concerns and support their decision-making. In particular, it is capable of providing detailed and accurate information quickly to support the major decision of buying or selling real estate.

[0565] The processing flow will be explained below.

[0566] Step 1:

[0567] Users access the system through a smartphone app or web browser, log in or register, and enter their first name, email address, and password, then click the submit button.

[0568] Step 2:

[0569] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[0570] Step 3:

[0571] If the authentication is successful, the server issues an authentication token and sends it to the terminal, which receives the token and displays the dashboard screen to the user.

[0572] Step 4:

[0573] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[0574] Step 5:

[0575] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[0576] Step 6:

[0577] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[0578] Step 7:

[0579] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0580] Step 8:

[0581] The server generates a response and sends it to the device, which displays it in the user's chat box. The user can then confirm the displayed information.

[0582] Step 9:

[0583] The user continues to ask questions as needed, for example, "Do you have any recommendations for properties with these criteria?" The device sends the new question to the server and repeats the process from step 5.

[0584] Step 10:

[0585] The server matches the user's history and preferences and adds relevant information, such as suggesting property listings in a particular area or price range based on the user's previous questions.

[0586] Step 11:

[0587] The server sends the relevant information to the device, which then presents it to the user, who then reviews the suggested information and considers their next course of action.

[0588] In this way, this system efficiently and fairly provides information in response to user questions and inquiries. Users can quickly obtain detailed information about real estate transactions, reducing their anxiety.

[0589] Example 1

[0590] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0591] When buying and selling real estate, it has been difficult for users to quickly and appropriately obtain the information they need. Conventional methods require consulting with experts, which takes time and costs money. Another issue is that it is difficult for users to efficiently obtain information that best suits their situation and desired conditions.

[0592] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0593] In this invention, the server includes a means for providing an interface for users to access, a means for receiving input from users and sending it to the server, a means for passing the input to a natural language processing engine for analysis and answer generation, a means for receiving the answer and presenting it to the user, and a means for comparing the user's authentication information with a database and issuing an authentication token. This allows users to easily ask questions or get advice about real estate, and to receive information efficiently and fairly.

[0594] "User" means any individual or entity that accesses the System and seeks information or assistance regarding real estate.

[0595] "Interface" refers to the screen and input means that users use to access and operate the system.

[0596] "Server" refers to a computer system that receives input from a user, analyzes and processes it, and returns the results to the user.

[0597] A "natural language processing engine" refers to an artificial intelligence technology that analyzes user input, understands intent, and generates appropriate answers.

[0598] "Authentication Token" refers to a digital certificate that indicates a user is authenticated when accessing a system.

[0599] "Database" refers to a system that manages and stores data such as user information, answers to questions, and history.

[0600] "Parsing" refers to the process by which a natural language processing engine understands a user's input and understands their intent.

[0601] "Answer generation" refers to the process by which a natural language processing engine creates an appropriate answer to a question.

[0602] The present invention is a system for users to obtain information and support regarding real estate transactions, and aims to provide efficient and fair support. This system is configured as follows.

[0603] System configuration

[0604] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[0605] Hardware and Software Configuration

[0606] User: Accesses the system via an internet connection using a smartphone or PC.

[0607] Terminal: A device that accepts user input and sends it to a server. Examples include smartphone apps and web browsers.

[0608] Server: Manages the database (e.g., MySQL or PostgreSQL) and uses a natural language processing engine (e.g., GPT-3 or BERT) to analyze user questions and generate answers.

[0609] Natural Language Processing Engine: Artificial intelligence techniques for understanding user input and understanding intent, such as GPT-3 and BERT.

[0610] Program processing

[0611] The system process is as follows:

[0612] User authentication and initial setup

[0613] 1. User: Access the system from a smartphone app or web browser and register or log in.

[0614] 2. Device: Sends the entered name, email address, and password to the server.

[0615] 3. Server: Compares with the database, and if authentication is successful, issues an authentication token and sends it to the terminal.

[0616] 4. Terminal: Receives the authentication token and displays the user's dashboard.

[0617] Enter and submit your question

[0618] 1. User: Type your real estate question into the chat box on the screen.

[0619] 2. Terminal: Sends a query to the server.

[0620] Parsing questions and generating answers

[0621] 1. Server: Passes the question to the natural language processing engine and requests analysis.

[0622] 2. Natural language processing engine: Analyzes the intent of the user's question and generates the most appropriate answer.

[0623] Example: To the question "What are mortgage interest rates?", the answer would be: "Current mortgage interest rates average around 2.5%. However, this can vary depending on your circumstances, so we recommend you inquire with your lender."

[0624] Sending the answer and showing it to the user

[0625] 1. Server: Sends the generated answer to the device.

[0626] 2. Terminal: Displays the received answer on the user's screen.

[0627] Specific examples

[0628] Below is an example of a prompt sentence to input to the generative AI model.

[0629] Prompt Sentence Examples

[0630] Q: A user asks, "What are the mortgage interest rates?" Generate a suitable answer to this question.

[0631] A: The current average interest rate for a home loan is around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution.

[0632] The system utilizes efficient natural language processing technology to provide users with prompt and appropriate information, thereby supporting the important decision-making process of buying and selling real estate, alleviating users' concerns and enabling them to obtain information efficiently.

[0633] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0634] Step 1:

[0635] User: Access the system from a smartphone app or web browser and register or log in.

[0636] Input: The name, email address, and password entered by the user.

[0637] What happens: A user opens the app or browser, enters the required information, and clicks the submit button.

[0638] Output: The entered user information is passed to the terminal.

[0639] Step 2:

[0640] Terminal: Sends information entered by the user to the server.

[0641] Input: Name, email address, and password received from the user.

[0642] What it does: Input information is packaged in an appropriate format and sent to the server as an HTTP request.

[0643] Output: User information is passed to the server.

[0644] Step 3:

[0645] Server: Compares the received user information with a database.

[0646] Input: User information sent from the device.

[0647] How it works: The server compares the new user information with existing information in a database (e.g., MySQL or PostgreSQL) and authenticates them.

[0648] Output: If authentication is successful, an authentication token is generated.

[0649] Step 4:

[0650] Server: If authentication is successful, generate an authentication token and send it to the device.

[0651] Input: User information matching results.

[0652] What it does: Generates an authentication token and constructs an HTTP response to send it to the device.

[0653] Output: The authentication token is sent to the device.

[0654] Step 5:

[0655] Terminal: Receives the authentication token and displays the user's dashboard.

[0656] Input: The received authentication token.

[0657] What it does: Stores the authentication token and displays the dashboard screen to the user.

[0658] Output: The user's dashboard screen is displayed.

[0659] Step 6:

[0660] User: Type your real estate question into the chat box on the screen.

[0661] Input: The question the user types into the chat box.

[0662] Action: Enter a question and click the submit button.

[0663] Output: The entered question is sent to the terminal.

[0664] Step 7:

[0665] Terminal: Sends the entered question to the server.

[0666] Input: The question received from the user.

[0667] What it does: Packages the question into an appropriate format and sends it to the server as an HTTP request.

[0668] Output: The question is passed to the server.

[0669] Step 8:

[0670] Server: Passes the received question to the natural language processing engine and requests analysis.

[0671] Input: Question sent from terminal.

[0672] How it works: A question is fed into a generative AI model (such as GPT-3 or BERT), which analyzes it and generates an answer.

[0673] Output: The generated answer is sent back to the server.

[0674] Step 9:

[0675] Server: Sends the generated answer to the device.

[0676] Input: The answer returned by the natural language processing engine.

[0677] What it does: Constructs the answer as an HTTP response and sends it to the device.

[0678] Output: The answer is sent to the terminal.

[0679] Step 10:

[0680] Terminal: Displays the received answer on the user's screen.

[0681] Input: The answer sent by the server.

[0682] What it does: Displays the answer on the screen for the user to review.

[0683] Output: The answer is displayed on the user's screen.

[0684] These are the specific processing steps of the system, which allows users to get fast and accurate answers to their real estate questions.

[0685] (Application example 1)

[0686] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0687] Conventional real estate purchase and sale support systems have difficulty in providing users with the information they need quickly and appropriately, and a solution that provides efficient, fair, and detailed information is needed. In addition, there is a lack of means for users to resolve their questions and concerns in real time, so technology that can quickly support users in making decisions is needed.

[0688] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0689] In this invention, the server includes means for providing a display device accessed by a user, means for receiving input from the user and sending it to a processing device, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving the generated answer and presenting it to the user, and means for linking with a database for adding related information based on the analysis results, thereby enabling users to obtain real estate information in real time and make decisions quickly.

[0690] A "display device" is a device that allows a user to visually confirm information.

[0691] A "processor" is a device for receiving input from a user and analyzing and processing it.

[0692] A "natural language processing engine" is a system and software that analyzes text data, understands the user's intent, and generates appropriate answers.

[0693] A "generated answer" is information provided as a result of analysis by a natural language processing engine.

[0694] A "database" is a system that stores user history and related information and provides that information as needed.

[0695] "User history" refers to a record of searches and entries made by a user in the past, as well as any related information.

[0696] "Desired conditions" are specific requirements or conditions that a user specifies when providing information about a property.

[0697] "Authentication Token" means a piece of authentication information that uniquely identifies a user and is issued to the user when the user accesses a system.

[0698] "Surrounding environment information" refers to information about facilities and transportation methods around the real estate property.

[0699] "Additional information" is supplementary information that is deemed highly relevant based on the user's input and history.

[0700] This invention aims to realize a real estate buying and selling support system called "Smart Consulting Real Estate Assistant (Store Version)." The purpose of this system is to enable users to obtain real estate information in real time at a physical store and receive fair and efficient support.

[0701] System configuration

[0702] The system includes a display device accessed by a user, a means for transmitting input from the user to a processing device, a natural language processing engine for analysis and answer generation, a means for providing the generated answer, and a database for linking related information.

[0703] The hardware used includes tablets, smart glasses, and head-mounted displays, which are used as display devices for users to directly view information. Servers and databases are used to receive, process, and store user input. The software used includes natural language processing engines (e.g., Google Cloud Natural Language API, Amazon Comprehend), authentication systems (e.g., OAuth 2.0), and UI frameworks (e.g., React Native, Flutter).

[0704] Program processing

[0705] 1. User authentication and initial setup

[0706] The user accesses the system through a display device (tablet or smart glasses) and logs in or registers. The user's input information is sent to the server and checked against a database. If authentication is successful, an authentication token is issued and sent to the user's display device. At this stage, the user's dashboard is displayed, and available functions are explained.

[0707] 2. Enter and submit your question

[0708] The user uses the chat box to input questions or inquiries about real estate. For example, they can input, "Please tell me about the surrounding area." This input is sent from the display device to the server.

[0709] 3. Question Analysis and Answer Generation

[0710] The server receives the input question and passes it to a natural language processing engine, which analyzes the user's question and generates the most appropriate answer.

[0711] 4. Providing Additional Information

[0712] Based on the analysis results, related information is obtained from a database that links the user's history, desired conditions, and related information, such as information on nearby facilities, transportation, and the environment.

[0713] 5. View Answers

[0714] The server sends the generated answer to a display device and presents it to the user, who then checks the information and considers their next course of action.

[0715] This system is a powerful support tool that allows users to efficiently and fairly obtain real estate information in physical stores and make quick decisions.

[0716] Examples and prompts

[0717] In-store usage scenario

[0718] 1. Customer: Picks up the tablet and types, "I'd like to know about the surrounding area."

[0719] 2. Terminal: Sends a query to the server.

[0720] 3. Server: Analyzes the question using a natural language processing engine.

[0721] 4. Server: Based on the analysis results, obtain surrounding information from the database.

[0722] 5. Server: Sends the generated answer to the device.

[0723] 6. Terminal: Show the answer to the customer. For example, "There are schools, supermarkets, and train stations nearby."

[0724] 7. Visitors: Review the displayed information and explore properties that interest them further.

[0725] Example prompts for generative AI models

[0726] Sample prompt: "Please provide information about the surrounding area of ​​the property."

[0727] Example prompt: "What are the best mortgage terms?"

[0728] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0729] Step 1: User authentication and initial setup

[0730] 1. The user picks up a display device (tablet or smart glasses), accesses the system, and logs in or registers.

[0731] Input: Name, Email Address, Password

[0732] Processing: The input information is sent from the terminal to the server. The server checks the database to see if the user is registered. If the user is new, the new user information is saved in the database.

[0733] Output: An authentication token is issued and sent to the device.

[0734] Step 2: View the dashboard

[0735] 1. The device receives the authentication token and displays the user's dashboard.

[0736] Input: Authentication Token

[0737] Processing: The device receives the authentication token, checks the features the user has access to, and configures the dashboard.

[0738] Output: The dashboard screen is displayed.

[0739] Step 3: Enter and submit your question

[0740] 1. The user enters their real estate question or inquiry in the chat box.

[0741] Input: Questions such as "Tell me about the surrounding area"

[0742] Processing: The device sends the entered question to the server, which receives the question and prepares it for passing to the natural language processing engine.

[0743] Output: The question data is passed to a natural language processing engine.

[0744] Step 4: Parsing the question and generating an answer

[0745] 1. The server passes the question to a natural language processing engine for analysis and answer generation.

[0746] Input: User question data

[0747] Processing: A natural language processing engine (e.g., Google Cloud Natural Language API, Amazon Comprehend) analyzes the question and understands the user's intent. Based on the analysis results, it generates the most appropriate answer.

[0748] Output: The generated answer

[0749] Step 5: Obtain additional information

[0750] 1. Based on the analysis results, the server retrieves relevant information from the database.

[0751] Input: Analysis results, user history and desired conditions

[0752] Processing: The server connects to the database to search for and retrieve relevant information (such as information about the surrounding environment) based on the user's history and desired conditions.

[0753] Output: Additional relevant information

[0754] Step 6: Submit and view your answers and additional information

[0755] 1. The server sends the generated answer and any additional relevant information to the terminal.

[0756] Input: Generated answers, related information

[0757] Processing: The server aggregates the generated answers and related information and sends them to the terminal, which receives them and displays them to the user.

[0758] Output: Answers and related information displayed on the user's tablet or smart glasses

[0759] Step 7: User confirmation and further action

[0760] 1. The user reviews the displayed information and considers their next question or action.

[0761] Input: Displayed answers and related information

[0762] Processing: If the user enters an additional question, process the new input again according to steps 3 through 6.

[0763] Output: If a new question is input, a continuous question-answering cycle begins.

[0764] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0765] This invention provides more appropriate support to users by combining a real estate buying and selling support system called "Smart Consulting" with an emotion engine that recognizes user emotions. The system aims to provide fair, efficient, and emotion-responsive support when users obtain information and support related to real estate buying and selling.

[0766] System configuration

[0767] The system includes an interface accessed by the user, a means for sending user input to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, a means for comparing the user's authentication information with a database and issuing an authentication token, and an emotion engine for recognizing the user's emotions.

[0768] Program processing

[0769] The operation of the system is described below.

[0770] 1. User authentication and initial setup

[0771] The user accesses the interface and logs in or registers. The device accepts this operation and sends the entered information to the server. The server compares the information with the information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard screen.

[0772] 2. Enter and submit your question

[0773] The user enters a real estate question or inquiry into the chat box. For example, they might type, "Please tell me about mortgage interest rates." The device then sends this input to the server, which then passes the input data to a natural language processing engine for analysis.

[0774] 3. Question Analysis and Answer Generation

[0775] The natural language processing engine analyzes the intent of the user's question and generates the most appropriate answer based on the results of this analysis. For example, it creates an answer such as, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0776] 4. Recognizing emotions and adjusting responses

[0777] The emotion engine analyzes the user's input text and interaction data to assess the user's emotional state. For example, it may recognize from the user's language and frequent questions that the user is feeling anxious. Based on this, the emotion engine can adjust the content and tone of its responses and provide additional information to ease the user's anxiety.

[0778] 5. Sending the answer and showing it to the user

[0779] The server sends the generated answers and the results of the emotion engine adjustments to the device, which displays the answers in the user's chat box. The user can review this information and continue asking further questions if necessary.

[0780] Specific examples

[0781] First-Time User Scenario

[0782] 1. User: Download the smartphone app and open it for the first time.

[0783] 2. Device: Display the new registration screen.

[0784] 3. User: Enter your name, email address, and password and submit.

[0785] 4. Device: Sends user information to the server.

[0786] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[0787] 6. Terminal: Displays the dashboard and guides you through the available functions.

[0788] Question-answering scenario

[0789] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[0790] 2. Terminal: Sends the entered question to the server.

[0791] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0792] 4. Emotion Engine: Analyzes user input, recognizes when the user is feeling anxious, and generates corresponding countermeasures.

[0793] 5. Server: Sends the generated answer and adjusted information to the terminal.

[0794] 6. Device: The answer is displayed on the user's screen. The user checks the displayed information and considers their next action.

[0795] This system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, allowing it to provide more attentive support. Users can not only quickly obtain detailed information about real estate sales and purchases, but also reduce anxiety during the process.

[0796] The processing flow will be explained below.

[0797] Step 1:

[0798] Users access the system through a smartphone app or web browser to register or log in. They enter their name, email address, and password and click the "Submit" button.

[0799] Step 2:

[0800] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[0801] Step 3:

[0802] If authentication is successful, the server issues an authentication token and sends it to the device. The device receives this token and displays the user's dashboard screen.

[0803] Step 4:

[0804] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[0805] Step 5:

[0806] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[0807] Step 6:

[0808] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[0809] Step 7:

[0810] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[0811] Step 8:

[0812] The emotion engine analyzes user input text and interaction data to assess the user's emotional state. For example, it may recognize that the user is feeling anxious based on their language and frequent questions.

[0813] Step 9:

[0814] Based on the analysis, the sentiment engine adjusts the tone and content of the generated answers, for example, providing a more confident response to a user who is feeling anxious, with additional advice and resources.

[0815] Step 10:

[0816] The server sends the final answer and the adjustment results of the emotion engine to the device, which receives them and displays them in the user's chat box.

[0817] Step 11:

[0818] The user checks the displayed information and continues to ask questions if necessary. For example, enter the question again, "Do you have any recommended properties that meet these criteria?" The device then sends the new question to the server and repeats the process from step 5.

[0819] The above is the specific processing flow of the "Smart Consulting" system. In this way, this system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, making it possible to provide more detailed support. Not only can users quickly obtain detailed information about real estate sales and purchases, but they can also reduce their anxiety during the process.

[0820] Example 2

[0821] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0822] Conventional real estate buying and selling support systems provide efficient and accurate answers to user input, but they do not take into account the user's emotional state, which means that the system does not fully resolve the user's anxieties or questions.In addition, they do not suggest related information based on the user's history or desired conditions, which means that user convenience is not improved.

[0823] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0824] In this invention, the server includes a means for analyzing user input using a natural language processing engine and generating a response, a means for evaluating the user's emotional state based on the analysis results and adjusting the tone and content of the response, and a means for verifying the user's authentication information against a database and issuing an authentication token. This makes it possible to provide emotionally responsive support to the user and alleviate their anxieties and doubts. Furthermore, by suggesting related information based on the user's history and desired conditions, user convenience is improved.

[0825] "Interface" refers to the screen or operating section that allows users to access the system and input information.

[0826] A "natural language processing engine" refers to an algorithm or program that analyzes user input, understands its intent, and generates an answer.

[0827] An "emotion engine" refers to an algorithm or program that analyzes user input data and interactions and assesses the user's emotional state.

[0828] An "authentication token" is a temporary identification code issued when a user logs in to a system, and is used to verify the user's authentication status.

[0829] "User history" refers to the record of the user's past operations and inquiries.

[0830] "Desired conditions" refers to specific requests or conditions that a user specifies to the system.

[0831] "Tone of the answer" refers to the expression and atmosphere of the generated answer, and is a factor that determines how it is conveyed to the user.

[0832] "Related information" refers to additional useful data or suggestions provided in response to a user's question or input.

[0833] "User authentication" refers to the process of verifying that a user is a legitimate user when logging into a system.

[0834] MODE FOR CARRYING OUT THE INVENTION

[0835] The present invention provides a real estate buying and selling support system that provides more appropriate support by combining an emotion engine that recognizes the user's emotions. The system configuration and operation are described in detail below.

[0836] System Configuration

[0837] This system is configured using the following hardware and software.

[0838] User device: A device such as a PC or smartphone used by a user.

[0839] Server: A server that performs data processing, authentication, natural language processing, and emotion recognition. Specifically, this includes database servers, application servers, etc.

[0840] Database: Stores user registration information, authentication information, past interactions, historical information, etc.

[0841] Natural language processing engines: Examples include Google BERT and OpenAI GPT-3.

[0842] Emotion engine: A program for analyzing user input text and interaction data.

[0843] Data processing and calculation

[0844] User authentication

[0845] A user accesses the interface and logs in or registers.

[0846] Terminal: The entered user information is sent to the server in JSON format.

[0847] Server: Compares the received information with the database, generates an authentication token (such as a JWT), and sends it to the device.

[0848] Enter and submit your question

[0849] The user types a question into the chat box.

[0850] Example: "What are the mortgage interest rates?"

[0851] Terminal: Sends the entered question to the server.

[0852] Question analysis and answer generation

[0853] Server: Passes the question to a natural language processing engine for analysis and answer generation.

[0854] The natural language processing engine uses Google BERT and OpenAI GPT-3 to analyze the intent of the question and generate appropriate answers.

[0855] Example answer: "Current mortgage interest rates average around 2.5%. However, this varies depending on the terms, so we recommend checking with your financial institution."

[0856] Recognizing emotions and adjusting responses

[0857] Server: Passes the analysis results and user input to the emotion engine.

[0858] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[0859] Example: A user's frequent questions and negative language indicate anxiety.

[0860] Server: Adjusts the tone and content of the response based on the evaluation results from the emotion engine.

[0861] Example: To ease concerns, additional information is added, such as, "Don't worry. Current mortgage interest rates average around 2.5%. We recommend checking with your financial institution for details."

[0862] Providing an answer

[0863] Server: Sends the adjusted answer to the device.

[0864] Terminal: Display received responses in the chat box.

[0865] A key feature of this system is that it adjusts responses based on the user's emotional state. As a result, users not only receive detailed information about real estate transactions, but also reduce any anxiety or doubts they may have during the process. It also suggests related information based on the user's history and desired conditions, improving user convenience and satisfaction.

[0866] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0867] Step 1:

[0868] Users: Access the interface and register or log in.

[0869] Enter your name, email address, and password.

[0870] Output: The user information is sent to the server.

[0871] Terminal: Sends the entered information to the server.

[0872] Specific operation: The terminal converts the input data into JSON format and sends it to the server as an API request.

[0873] Step 2:

[0874] Server: Compares the received user information with a database and performs authentication.

[0875] Input: User information in JSON format.

[0876] Output: An authentication token or an error message.

[0877] What happens: The server runs an SQL query to verify the user information and, if there is a match, generates an authentication token (such as a JWT).

[0878] Step 3:

[0879] Server: If authentication is successful, it sends an authentication token to the device. If authentication fails, it sends an error message.

[0880] Input: An authentication token or an error message.

[0881] Output: An authentication token or an error message is sent to the terminal.

[0882] Terminal: Save the received authentication token and display the dashboard screen.

[0883] Specific operation: The device stores the authentication token in a cookie or session storage.

[0884] Step 4:

[0885] User: Type your real estate question in the chat box.

[0886] Input: A question like "What are the mortgage interest rates?"

[0887] Output: The question is sent to the system.

[0888] Terminal: Sends the entered question to the server.

[0889] Specific operation: The device converts the question into JSON format and sends it to the server as an API request.

[0890] Step 5:

[0891] Server: Passes question data to a natural language processing engine for analysis and answer generation.

[0892] Input: User question data.

[0893] Output: The answer from the natural language processing engine.

[0894] Specific operation: The server sends an API request to a natural language processing engine (e.g., OpenAI GPT-3) and receives the analysis results.

[0895] Step 6:

[0896] Server: Passes the analysis results to the emotion engine to evaluate the user's emotional state.

[0897] Input: Analysis results from the natural language processing engine and user input data.

[0898] Output: Emotion evaluation results from the emotion engine.

[0899] Specific operation: The server sends the analysis results and the user's input data to the emotion engine.

[0900] Step 7:

[0901] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[0902] Input: Analysis results and user input data.

[0903] Output: Emotion evaluation result (e.g., anxiety, relief, etc.).

[0904] Specific behavior: The emotion engine analyzes the user's text and operation history to evaluate their emotional state.

[0905] Step 8:

[0906] Server: Adjust the tone and content of the response based on the sentiment assessment results.

[0907] Input: Emotion assessment results.

[0908] Output: The adjusted answer.

[0909] Specific behavior: The server appropriately adjusts the tone of the response based on the evaluation from the emotion engine.

[0910] Step 9:

[0911] Server: Sends the final adjusted answer to the device.

[0912] Input: Adjusted answer.

[0913] Output: The answer is sent to the terminal.

[0914] Terminal: Display received responses in the chat box.

[0915] Specific operation: The device analyzes the received data and displays it in the chat box.

[0916] Through these processing steps, the system provides quick and appropriate answers to the user's questions, taking into account the user's emotional state in the process, thereby reducing the user's anxiety.

[0917] (Application example 2)

[0918] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0919] Existing real estate transaction support systems do not take into account the user's emotional state, which can lead to users receiving information with feelings of anxiety or distrust. Furthermore, information provided through the dialogue interface may not be adequately matched with the user's desired conditions or history, resulting in inappropriate information being provided. Furthermore, there are issues with insufficient efficiency and security in user authentication.

[0920] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for providing an interface accessed by the user, means for receiving input from the user and sending it to the server, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving an answer and presenting it to the user, means for recognizing the user's emotions and adjusting the answer content based on the results, means for comparing the analysis results with the user's history and desired conditions based on the user's emotional state and adding related information, and means for comparing the user's authentication information with a database and issuing an authentication token. This makes it possible to provide appropriate information to the user in a timely manner, taking into account the user's emotional state.

[0921] A "user-accessible interface" is the means by which a user accesses a system and enters or views information.

[0922] "User input" is data, such as text or voice commands, that a user provides through an interface.

[0923] A "server" is a computer system that receives input from a user, processes it, and provides the results to the user.

[0924] A "natural language processing engine" is a program that analyzes input from users, understands their intent, and generates appropriate responses.

[0925] An "emotion engine" is a program that analyzes user input and interaction data to recognize the user's emotional state.

[0926] An "authentication token" is a digital key that proves that a user is authenticated when accessing a system.

[0927] The "dashboard screen" is the main screen that is displayed when a user logs in to the system and allows the user to perform operations and check information.

[0928] A "chat box" is an interactive input field where users can freely enter questions or messages.

[0929] "Adjusting the answer content" refers to the act of optimizing the generated answer according to the user's emotional state and providing the most appropriate information for the user's situation.

[0930] "Analysis results" refers to information resulting from the analysis of user input by a natural language processing engine or emotion engine.

[0931] "History and desired conditions" refers to data such as information entered by the user in the past and desired conditions.

[0932] "Related information" is supplementary or additional information provided based on the user's question or situation.

[0933] This invention is applied to a real estate sales support system called "Smart Consulting Glasses." The smart glasses, which are used by real estate consultants when dealing with customers in brick-and-mortar stores, are used to understand the user's emotional state and provide more appropriate information. The purpose of this invention is to enable users to receive fair and efficient support for specific questions and inquiries through an interactive interface.

[0934] System configuration

[0935] Hardware and Software Configuration

[0936] Hardware: smart glasses, camera, display, microphone, server.

[0937] Software: Emotion Recognition model, Transformers library (for natural language processing), OpenCV (image processing framework), Speech-to-Text engine (audio to text conversion).

[0938] Overall system flow

[0939] 1. User authentication and initial setup:

[0940] The user puts on the smart glasses and logs in or registers.

[0941] The terminal accepts this operation and transmits the input information to the server.

[0942] The server checks the authentication information against a database, generates an authentication token, and sends it to the terminal.

[0943] The device receives the authentication token and displays the dashboard screen.

[0944] 2. User input and submit question:

[0945] Users use the smart glasses interface to input real estate questions and inquiries.

[0946] For example, ask a voice question such as, "Please tell me about mortgage interest rates."

[0947] The device converts the voice into text and sends the input data to the server.

[0948] 3. Analysis and Answer Generation:

[0949] A natural language processing engine analyzes the user's question, understands their intent, and generates the most appropriate answer.

[0950] For example, generate an answer like, "Current mortgage interest rates average around 2.5%, but this can vary depending on the terms."

[0951] 4. Emotion recognition and response adjustment:

[0952] The emotion engine analyzes the user's facial expressions from camera footage and recognizes their emotional state.

[0953] If the user is perceived as feeling anxious, the emotion engine will adjust its responses based on that information.

[0954] For example, provide additional information such as "We will also provide you with detailed contact information."

[0955] 5. Submitting and Presenting Your Answers:

[0956] The server sends the generated answer and the adjusted information to the display of the smart glasses.

[0957] The user checks the information displayed on the smart glasses display and considers their next action.

[0958] Specific examples

[0959] Scenarios when users ask questions

[0960] 1. User: "What are the mortgage interest rates?"

[0961] 2. Device: Converts speech into text and sends it to the server.

[0962] 3. Server: Analyzes the question using a natural language processing engine and generates an answer.

[0963] 4. Emotion engine: Recognizes anxiety from the user's facial expressions.

[0964] 5. Server: Generates answers and additional anxiety-reducing information and sends them to the device.

[0965] 6. Terminal: Shows answers and additional information.

[0966] Prompt Sentence Examples

[0967] Q: What are the interest rates for home loans?

[0968] Expression: He looks anxious.

[0969] This system can dramatically improve the quality of real estate consulting by recognizing users' anxieties and questions in real time and providing more appropriate and satisfying information.

[0970] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0971] Step 1:

[0972] User authentication and initial setup

[0973] Input: User login information (username, password)

[0974] Data processing / calculation: The user puts on the smart glasses and logs in or registers. The device accepts this operation, captures the entered login information, and sends it to the server. The server compares it with existing authentication information in a database and generates an authentication token if authentication is successful.

[0975] Output: Authentication token

[0976] Specific behavior:

[0977] The user enters their login information through the smart glasses.

[0978] The server generates an authentication token and sends it to the device.

[0979] The device receives the authentication token and displays the user's dashboard screen.

[0980] Step 2:

[0981] Enter and submit your question

[0982] Input: A spoken question asked by the user (e.g., "What are the mortgage interest rates?")

[0983] Data processing / computation: The user asks a question by voice through the smart glasses interface. The device uses a microphone to capture the voice and converts it into text using a speech-to-text engine. The converted text data is then sent to the server.

[0984] Output: Questions converted to text

[0985] Specific behavior:

[0986] The user asks aloud, "What are the interest rates for a mortgage?"

[0987] The device captures the audio and converts it into text.

[0988] Send a textual question to the server.

[0989] Step 3:

[0990] Question analysis and answer generation

[0991] Input: Textual question data

[0992] Data processing / calculation: The server passes the textual question data to a natural language processing engine for analysis. The natural language processing engine understands the intent of the question and generates the most appropriate answer.

[0993] Output: The generated answer (e.g., "Current mortgage interest rates average around 2.5%")

[0994] Specific behavior:

[0995] The server passes the text data to a natural language processing engine.

[0996] A natural language processing engine analyzes the question and generates an appropriate answer.

[0997] Step 4:

[0998] Emotion recognition and response adjustment

[0999] Input: Camera footage, generated answers

[1000] Data processing / computation: The emotion engine processes the camera footage, analyzes the user's facial expressions for each frame, and recognizes their emotional state. Based on the emotion, the server can add additional information or adjust the tone of the generated answer.

[1001] Output: Tailored response (e.g., "We will also provide you with further contact information")

[1002] Specific behavior:

[1003] The server passes the camera images from the smart glasses to the emotion engine.

[1004] The emotion engine analyzes the user's facial expressions and recognizes that they are feeling anxious.

[1005] The server appends additional anxiety-reducing information to the response.

[1006] Step 5:

[1007] Submitting and Presenting Answers

[1008] Input: Adjusted Answer

[1009] Data processing / calculation: The server sends the adjusted answer to the smart glasses display and displays it to the user. The user confirms the presented information and considers their next action.

[1010] Output: The answer is displayed

[1011] Specific behavior:

[1012] The server sends the adjusted response to the terminal.

[1013] The device displays the answer on the smart glasses display.

[1014] The above is the specific flow and operation of each processing step of the system for realizing the application example.

[1015] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1016] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1017] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1018] [Third embodiment]

[1019] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1020] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1021] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1022] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1023] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1024] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1025] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1026] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1027] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1028] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1029] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1030] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1031] This invention realizes a real estate buying and selling support system called "Smart Consulting." The purpose of this system is to provide fair and efficient support when users obtain information and support regarding real estate buying and selling.

[1032] System configuration

[1033] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[1034] Program processing

[1035] The operation of the system is described below.

[1036] 1. User authentication and initial setup

[1037] Users access "Smart Consult" through a web browser or smartphone app and first log in or register. The device accepts this operation and sends the entered information to the server. The server compares the information with information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard.

[1038] 2. Enter and submit your question

[1039] Users can input real estate-related questions or inquiries into the chat box. For example, if a user types a question like "What are the interest rates for a mortgage?", the device sends this input to the server. The server then passes the input question to a natural language processing engine for analysis.

[1040] 3. Question Analysis and Answer Generation

[1041] The natural language processing engine analyzes the intent of the user's question. Based on the results of this analysis, it generates the most appropriate answer. For example, in response to a question about mortgage interest rates, it generates the answer, "Current mortgage interest rates average around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1042] 4. Sending the answer and showing it to the user

[1043] The server sends the generated answer to the device, which displays it on the user's screen, allowing the user to review the information and ask further questions if necessary.

[1044] Specific examples

[1045] First-Time User Scenario

[1046] 1. User: Download the smartphone app and open it for the first time.

[1047] 2. Device: Display the new registration screen.

[1048] 3. User: Enter your name, email address, and password and submit.

[1049] 4. Device: Sends user information to the server.

[1050] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[1051] 6. Terminal: Displays the dashboard and guides you through the available functions.

[1052] Question-answering scenario

[1053] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[1054] 2. Terminal: Sends the entered question to the server.

[1055] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1056] 4. Server: Sends the generated answer to the device.

[1057] 5. Terminal: Display the answer on the user's screen.

[1058] 6. User: Check the displayed information and consider your next action.

[1059] This system provides users with information efficiently and fairly, helping to alleviate their concerns and support their decision-making. In particular, it is capable of providing detailed and accurate information quickly to support the major decision of buying or selling real estate.

[1060] The processing flow will be explained below.

[1061] Step 1:

[1062] Users access the system through a smartphone app or web browser, log in or register, and enter their first name, email address, and password, then click the submit button.

[1063] Step 2:

[1064] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[1065] Step 3:

[1066] If the authentication is successful, the server issues an authentication token and sends it to the terminal, which receives the token and displays the dashboard screen to the user.

[1067] Step 4:

[1068] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[1069] Step 5:

[1070] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[1071] Step 6:

[1072] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[1073] Step 7:

[1074] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1075] Step 8:

[1076] The server generates a response and sends it to the device, which displays it in the user's chat box. The user can then confirm the displayed information.

[1077] Step 9:

[1078] The user continues to ask questions as needed, for example, "Do you have any recommendations for properties with these criteria?" The device sends the new question to the server and repeats the process from step 5.

[1079] Step 10:

[1080] The server matches the user's history and preferences and adds relevant information, such as suggesting property listings in a particular area or price range based on the user's previous questions.

[1081] Step 11:

[1082] The server sends the relevant information to the device, which then presents it to the user, who then reviews the suggested information and considers their next course of action.

[1083] In this way, this system efficiently and fairly provides information in response to user questions and inquiries. Users can quickly obtain detailed information about real estate transactions, reducing their anxiety.

[1084] Example 1

[1085] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1086] When buying and selling real estate, it has been difficult for users to quickly and appropriately obtain the information they need. Conventional methods require consulting with experts, which takes time and costs money. Another issue is that it is difficult for users to efficiently obtain information that best suits their situation and desired conditions.

[1087] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1088] In this invention, the server includes a means for providing an interface for users to access, a means for receiving input from users and sending it to the server, a means for passing the input to a natural language processing engine for analysis and answer generation, a means for receiving the answer and presenting it to the user, and a means for comparing the user's authentication information with a database and issuing an authentication token. This allows users to easily ask questions or get advice about real estate, and to receive information efficiently and fairly.

[1089] "User" means any individual or entity that accesses the System and seeks information or assistance regarding real estate.

[1090] "Interface" refers to the screen and input means that users use to access and operate the system.

[1091] "Server" refers to a computer system that receives input from a user, analyzes and processes it, and returns the results to the user.

[1092] A "natural language processing engine" refers to an artificial intelligence technology that analyzes user input, understands intent, and generates appropriate answers.

[1093] "Authentication Token" refers to a digital certificate that indicates a user is authenticated when accessing a system.

[1094] "Database" refers to a system that manages and stores data such as user information, answers to questions, and history.

[1095] "Parsing" refers to the process by which a natural language processing engine understands a user's input and understands their intent.

[1096] "Answer generation" refers to the process by which a natural language processing engine creates an appropriate answer to a question.

[1097] The present invention is a system for users to obtain information and support regarding real estate transactions, and aims to provide efficient and fair support. This system is configured as follows.

[1098] System configuration

[1099] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[1100] Hardware and Software Configuration

[1101] User: Accesses the system via an internet connection using a smartphone or PC.

[1102] Terminal: A device that accepts user input and sends it to a server. Examples include smartphone apps and web browsers.

[1103] Server: Manages the database (e.g., MySQL or PostgreSQL) and uses a natural language processing engine (e.g., GPT-3 or BERT) to analyze user questions and generate answers.

[1104] Natural Language Processing Engine: Artificial intelligence techniques for understanding user input and understanding intent, such as GPT-3 and BERT.

[1105] Program processing

[1106] The system process is as follows:

[1107] User authentication and initial setup

[1108] 1. User: Access the system from a smartphone app or web browser and register or log in.

[1109] 2. Device: Sends the entered name, email address, and password to the server.

[1110] 3. Server: Compares with the database, and if authentication is successful, issues an authentication token and sends it to the terminal.

[1111] 4. Terminal: Receives the authentication token and displays the user's dashboard.

[1112] Enter and submit your question

[1113] 1. User: Type your real estate question into the chat box on the screen.

[1114] 2. Terminal: Sends a query to the server.

[1115] Parsing questions and generating answers

[1116] 1. Server: Passes the question to the natural language processing engine and requests analysis.

[1117] 2. Natural language processing engine: Analyzes the intent of the user's question and generates the most appropriate answer.

[1118] Example: To the question "What are mortgage interest rates?", the answer would be: "Current mortgage interest rates average around 2.5%. However, this can vary depending on your circumstances, so we recommend you inquire with your lender."

[1119] Sending the answer and showing it to the user

[1120] 1. Server: Sends the generated answer to the device.

[1121] 2. Terminal: Displays the received answer on the user's screen.

[1122] Specific examples

[1123] Below is an example of a prompt sentence to input to the generative AI model.

[1124] Prompt Sentence Examples

[1125] Q: A user asks, "What are the mortgage interest rates?" Generate a suitable answer to this question.

[1126] A: The current average interest rate for a home loan is around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution.

[1127] The system utilizes efficient natural language processing technology to provide users with prompt and appropriate information, thereby supporting the important decision-making process of buying and selling real estate, alleviating users' concerns and enabling them to obtain information efficiently.

[1128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1129] Step 1:

[1130] User: Access the system from a smartphone app or web browser and register or log in.

[1131] Input: The name, email address, and password entered by the user.

[1132] What happens: A user opens the app or browser, enters the required information, and clicks the submit button.

[1133] Output: The entered user information is passed to the terminal.

[1134] Step 2:

[1135] Terminal: Sends information entered by the user to the server.

[1136] Input: Name, email address, and password received from the user.

[1137] What it does: Input information is packaged in an appropriate format and sent to the server as an HTTP request.

[1138] Output: User information is passed to the server.

[1139] Step 3:

[1140] Server: Compares the received user information with a database.

[1141] Input: User information sent from the device.

[1142] How it works: The server compares the new user information with existing information in a database (e.g., MySQL or PostgreSQL) and authenticates them.

[1143] Output: If authentication is successful, an authentication token is generated.

[1144] Step 4:

[1145] Server: If authentication is successful, generate an authentication token and send it to the device.

[1146] Input: User information matching results.

[1147] What it does: Generates an authentication token and constructs an HTTP response to send it to the device.

[1148] Output: The authentication token is sent to the device.

[1149] Step 5:

[1150] Terminal: Receives the authentication token and displays the user's dashboard.

[1151] Input: The received authentication token.

[1152] What it does: Stores the authentication token and displays the dashboard screen to the user.

[1153] Output: The user's dashboard screen is displayed.

[1154] Step 6:

[1155] User: Type your real estate question into the chat box on the screen.

[1156] Input: The question the user types into the chat box.

[1157] Action: Enter a question and click the submit button.

[1158] Output: The entered question is sent to the terminal.

[1159] Step 7:

[1160] Terminal: Sends the entered question to the server.

[1161] Input: The question received from the user.

[1162] What it does: Packages the question into an appropriate format and sends it to the server as an HTTP request.

[1163] Output: The question is passed to the server.

[1164] Step 8:

[1165] Server: Passes the received question to the natural language processing engine and requests analysis.

[1166] Input: Question sent from terminal.

[1167] How it works: A question is fed into a generative AI model (such as GPT-3 or BERT), which analyzes it and generates an answer.

[1168] Output: The generated answer is sent back to the server.

[1169] Step 9:

[1170] Server: Sends the generated answer to the device.

[1171] Input: The answer returned by the natural language processing engine.

[1172] What it does: Constructs the answer as an HTTP response and sends it to the device.

[1173] Output: The answer is sent to the terminal.

[1174] Step 10:

[1175] Terminal: Displays the received answer on the user's screen.

[1176] Input: The answer sent by the server.

[1177] What it does: Displays the answer on the screen for the user to review.

[1178] Output: The answer is displayed on the user's screen.

[1179] These are the specific processing steps of the system, which allows users to get fast and accurate answers to their real estate questions.

[1180] (Application example 1)

[1181] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1182] Conventional real estate purchase and sale support systems have difficulty in providing users with the information they need quickly and appropriately, and a solution that provides efficient, fair, and detailed information is needed. In addition, there is a lack of means for users to resolve their questions and concerns in real time, so technology that can quickly support users in making decisions is needed.

[1183] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1184] In this invention, the server includes means for providing a display device accessed by a user, means for receiving input from the user and sending it to a processing device, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving the generated answer and presenting it to the user, and means for linking with a database for adding related information based on the analysis results, thereby enabling users to obtain real estate information in real time and make decisions quickly.

[1185] A "display device" is a device that allows a user to visually confirm information.

[1186] A "processor" is a device for receiving input from a user and analyzing and processing it.

[1187] A "natural language processing engine" is a system and software that analyzes text data, understands the user's intent, and generates appropriate answers.

[1188] A "generated answer" is information provided as a result of analysis by a natural language processing engine.

[1189] A "database" is a system that stores user history and related information and provides that information as needed.

[1190] "User history" refers to a record of searches and entries made by a user in the past, as well as any related information.

[1191] "Desired conditions" are specific requirements or conditions that a user specifies when providing information about a property.

[1192] "Authentication Token" means a piece of authentication information that uniquely identifies a user and is issued to the user when the user accesses a system.

[1193] "Surrounding environment information" refers to information about facilities and transportation methods around the real estate property.

[1194] "Additional information" is supplementary information that is deemed highly relevant based on the user's input and history.

[1195] This invention aims to realize a real estate buying and selling support system called "Smart Consulting Real Estate Assistant (Store Version)." The purpose of this system is to enable users to obtain real estate information in real time at a physical store and receive fair and efficient support.

[1196] System configuration

[1197] The system includes a display device accessed by a user, a means for transmitting input from the user to a processing device, a natural language processing engine for analysis and answer generation, a means for providing the generated answer, and a database for linking related information.

[1198] The hardware used includes tablets, smart glasses, and head-mounted displays, which are used as display devices for users to directly view information. Servers and databases are used to receive, process, and store user input. The software used includes natural language processing engines (e.g., Google Cloud Natural Language API, Amazon Comprehend), authentication systems (e.g., OAuth 2.0), and UI frameworks (e.g., React Native, Flutter).

[1199] Program processing

[1200] 1. User authentication and initial setup

[1201] The user accesses the system through a display device (tablet or smart glasses) and logs in or registers. The user's input information is sent to the server and checked against a database. If authentication is successful, an authentication token is issued and sent to the user's display device. At this stage, the user's dashboard is displayed, and available functions are explained.

[1202] 2. Enter and submit your question

[1203] The user uses the chat box to input questions or inquiries about real estate. For example, they can input, "Please tell me about the surrounding area." This input is sent from the display device to the server.

[1204] 3. Question Analysis and Answer Generation

[1205] The server receives the input question and passes it to a natural language processing engine, which analyzes the user's question and generates the most appropriate answer.

[1206] 4. Providing Additional Information

[1207] Based on the analysis results, related information is obtained from a database that links the user's history, desired conditions, and related information, such as information on nearby facilities, transportation, and the environment.

[1208] 5. View Answers

[1209] The server sends the generated answer to a display device and presents it to the user, who then checks the information and considers their next course of action.

[1210] This system is a powerful support tool that allows users to efficiently and fairly obtain real estate information in physical stores and make quick decisions.

[1211] Examples and prompts

[1212] In-store usage scenario

[1213] 1. Customer: Picks up the tablet and types, "I'd like to know about the surrounding area."

[1214] 2. Terminal: Sends a query to the server.

[1215] 3. Server: Analyzes the question using a natural language processing engine.

[1216] 4. Server: Based on the analysis results, obtain surrounding information from the database.

[1217] 5. Server: Sends the generated answer to the device.

[1218] 6. Terminal: Show the answer to the customer. For example, "There are schools, supermarkets, and train stations nearby."

[1219] 7. Visitors: Review the displayed information and explore properties that interest them further.

[1220] Example prompts for generative AI models

[1221] Sample prompt: "Please provide information about the surrounding area of ​​the property."

[1222] Example prompt: "What are the best mortgage terms?"

[1223] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1224] Step 1: User authentication and initial setup

[1225] 1. The user picks up a display device (tablet or smart glasses), accesses the system, and logs in or registers.

[1226] Input: Name, Email Address, Password

[1227] Processing: The input information is sent from the terminal to the server. The server checks the database to see if the user is registered. If the user is new, the new user information is saved in the database.

[1228] Output: An authentication token is issued and sent to the device.

[1229] Step 2: View the dashboard

[1230] 1. The device receives the authentication token and displays the user's dashboard.

[1231] Input: Authentication Token

[1232] Processing: The device receives the authentication token, checks the features the user has access to, and configures the dashboard.

[1233] Output: The dashboard screen is displayed.

[1234] Step 3: Enter and submit your question

[1235] 1. The user enters their real estate question or inquiry in the chat box.

[1236] Input: Questions such as "Tell me about the surrounding area"

[1237] Processing: The device sends the entered question to the server, which receives the question and prepares it for passing to the natural language processing engine.

[1238] Output: The question data is passed to a natural language processing engine.

[1239] Step 4: Parsing the question and generating an answer

[1240] 1. The server passes the question to a natural language processing engine for analysis and answer generation.

[1241] Input: User question data

[1242] Processing: A natural language processing engine (e.g., Google Cloud Natural Language API, Amazon Comprehend) analyzes the question and understands the user's intent. Based on the analysis results, it generates the most appropriate answer.

[1243] Output: The generated answer

[1244] Step 5: Obtain additional information

[1245] 1. Based on the analysis results, the server retrieves relevant information from the database.

[1246] Input: Analysis results, user history and desired conditions

[1247] Processing: The server connects to the database to search for and retrieve relevant information (such as information about the surrounding environment) based on the user's history and desired conditions.

[1248] Output: Additional relevant information

[1249] Step 6: Submit and view your answers and additional information

[1250] 1. The server sends the generated answer and any additional relevant information to the terminal.

[1251] Input: Generated answers, related information

[1252] Processing: The server aggregates the generated answers and related information and sends them to the terminal, which receives them and displays them to the user.

[1253] Output: Answers and related information displayed on the user's tablet or smart glasses

[1254] Step 7: User confirmation and further action

[1255] 1. The user reviews the displayed information and considers their next question or action.

[1256] Input: Displayed answers and related information

[1257] Processing: If the user enters an additional question, process the new input again according to steps 3 through 6.

[1258] Output: If a new question is input, a continuous question-answering cycle begins.

[1259] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1260] This invention provides more appropriate support to users by combining a real estate buying and selling support system called "Smart Consulting" with an emotion engine that recognizes user emotions. The system aims to provide fair, efficient, and emotion-responsive support when users obtain information and support related to real estate buying and selling.

[1261] System configuration

[1262] The system includes an interface accessed by the user, a means for sending user input to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, a means for comparing the user's authentication information with a database and issuing an authentication token, and an emotion engine for recognizing the user's emotions.

[1263] Program processing

[1264] The operation of the system is described below.

[1265] 1. User authentication and initial setup

[1266] The user accesses the interface and logs in or registers. The device accepts this operation and sends the entered information to the server. The server compares the information with the information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard screen.

[1267] 2. Enter and submit your question

[1268] The user enters a real estate question or inquiry into the chat box. For example, they might type, "Please tell me about mortgage interest rates." The device then sends this input to the server, which then passes the input data to a natural language processing engine for analysis.

[1269] 3. Question Analysis and Answer Generation

[1270] The natural language processing engine analyzes the intent of the user's question and generates the most appropriate answer based on the results of this analysis. For example, it creates an answer such as, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1271] 4. Recognizing emotions and adjusting responses

[1272] The emotion engine analyzes the user's input text and interaction data to assess the user's emotional state. For example, it may recognize from the user's language and frequent questions that the user is feeling anxious. Based on this, the emotion engine can adjust the content and tone of its responses and provide additional information to ease the user's anxiety.

[1273] 5. Sending the answer and showing it to the user

[1274] The server sends the generated answers and the results of the emotion engine adjustments to the device, which displays the answers in the user's chat box. The user can review this information and continue asking further questions if necessary.

[1275] Specific examples

[1276] First-Time User Scenario

[1277] 1. User: Download the smartphone app and open it for the first time.

[1278] 2. Device: Display the new registration screen.

[1279] 3. User: Enter your name, email address, and password and submit.

[1280] 4. Device: Sends user information to the server.

[1281] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[1282] 6. Terminal: Displays the dashboard and guides you through the available functions.

[1283] Question-answering scenario

[1284] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[1285] 2. Terminal: Sends the entered question to the server.

[1286] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1287] 4. Emotion Engine: Analyzes user input, recognizes when the user is feeling anxious, and generates corresponding countermeasures.

[1288] 5. Server: Sends the generated answer and adjusted information to the terminal.

[1289] 6. Device: The answer is displayed on the user's screen. The user checks the displayed information and considers their next action.

[1290] This system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, allowing it to provide more attentive support. Users can not only quickly obtain detailed information about real estate sales and purchases, but also reduce anxiety during the process.

[1291] The processing flow will be explained below.

[1292] Step 1:

[1293] Users access the system through a smartphone app or web browser to register or log in. They enter their name, email address, and password and click the "Submit" button.

[1294] Step 2:

[1295] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[1296] Step 3:

[1297] If authentication is successful, the server issues an authentication token and sends it to the device. The device receives this token and displays the user's dashboard screen.

[1298] Step 4:

[1299] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[1300] Step 5:

[1301] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[1302] Step 6:

[1303] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[1304] Step 7:

[1305] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1306] Step 8:

[1307] The emotion engine analyzes user input text and interaction data to assess the user's emotional state. For example, it may recognize that the user is feeling anxious based on their language and frequent questions.

[1308] Step 9:

[1309] Based on the analysis, the sentiment engine adjusts the tone and content of the generated answers, for example, providing a more confident response to a user who is feeling anxious, with additional advice and resources.

[1310] Step 10:

[1311] The server sends the final answer and the adjustment results of the emotion engine to the device, which receives them and displays them in the user's chat box.

[1312] Step 11:

[1313] The user checks the displayed information and continues to ask questions if necessary. For example, enter the question again, "Do you have any recommended properties that meet these criteria?" The device then sends the new question to the server and repeats the process from step 5.

[1314] The above is the specific processing flow of the "Smart Consulting" system. In this way, this system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, making it possible to provide more detailed support. Not only can users quickly obtain detailed information about real estate sales and purchases, but they can also reduce their anxiety during the process.

[1315] Example 2

[1316] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1317] Conventional real estate buying and selling support systems provide efficient and accurate answers to user input, but they do not take into account the user's emotional state, which means that the system does not fully resolve the user's anxieties or questions.In addition, they do not suggest related information based on the user's history or desired conditions, which means that user convenience is not improved.

[1318] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1319] In this invention, the server includes a means for analyzing user input using a natural language processing engine and generating a response, a means for evaluating the user's emotional state based on the analysis results and adjusting the tone and content of the response, and a means for verifying the user's authentication information against a database and issuing an authentication token. This makes it possible to provide emotionally responsive support to the user and alleviate their anxieties and doubts. Furthermore, by suggesting related information based on the user's history and desired conditions, user convenience is improved.

[1320] "Interface" refers to the screen or operating section that allows users to access the system and input information.

[1321] A "natural language processing engine" refers to an algorithm or program that analyzes user input, understands its intent, and generates an answer.

[1322] An "emotion engine" refers to an algorithm or program that analyzes user input data and interactions and assesses the user's emotional state.

[1323] An "authentication token" is a temporary identification code issued when a user logs in to a system, and is used to verify the user's authentication status.

[1324] "User history" refers to the record of the user's past operations and inquiries.

[1325] "Desired conditions" refers to specific requests or conditions that a user specifies to the system.

[1326] "Tone of the answer" refers to the expression and atmosphere of the generated answer, and is a factor that determines how it is conveyed to the user.

[1327] "Related information" refers to additional useful data or suggestions provided in response to a user's question or input.

[1328] "User authentication" refers to the process of verifying that a user is a legitimate user when logging into a system.

[1329] MODE FOR CARRYING OUT THE INVENTION

[1330] The present invention provides a real estate buying and selling support system that provides more appropriate support by combining an emotion engine that recognizes the user's emotions. The system configuration and operation are described in detail below.

[1331] System Configuration

[1332] This system is configured using the following hardware and software.

[1333] User device: A device such as a PC or smartphone used by a user.

[1334] Server: A server that performs data processing, authentication, natural language processing, and emotion recognition. Specifically, this includes database servers, application servers, etc.

[1335] Database: Stores user registration information, authentication information, past interactions, historical information, etc.

[1336] Natural language processing engines: Examples include Google BERT and OpenAI GPT-3.

[1337] Emotion engine: A program for analyzing user input text and interaction data.

[1338] Data processing and calculation

[1339] User authentication

[1340] A user accesses the interface and logs in or registers.

[1341] Terminal: The entered user information is sent to the server in JSON format.

[1342] Server: Compares the received information with the database, generates an authentication token (such as a JWT), and sends it to the device.

[1343] Enter and submit your question

[1344] The user types a question into the chat box.

[1345] Example: "What are the mortgage interest rates?"

[1346] Terminal: Sends the entered question to the server.

[1347] Question analysis and answer generation

[1348] Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1349] The natural language processing engine uses Google BERT and OpenAI GPT-3 to analyze the intent of the question and generate appropriate answers.

[1350] Example answer: "Current mortgage interest rates average around 2.5%. However, this varies depending on the terms, so we recommend checking with your financial institution."

[1351] Recognizing emotions and adjusting responses

[1352] Server: Passes the analysis results and user input to the emotion engine.

[1353] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[1354] Example: A user's frequent questions and negative language indicate anxiety.

[1355] Server: Adjusts the tone and content of the response based on the evaluation results from the emotion engine.

[1356] Example: To ease concerns, additional information is added, such as, "Don't worry. Current mortgage interest rates average around 2.5%. We recommend checking with your financial institution for details."

[1357] Providing an answer

[1358] Server: Sends the adjusted answer to the device.

[1359] Terminal: Display received responses in the chat box.

[1360] A key feature of this system is that it adjusts responses based on the user's emotional state. As a result, users not only receive detailed information about real estate transactions, but also reduce any anxiety or doubts they may have during the process. It also suggests related information based on the user's history and desired conditions, improving user convenience and satisfaction.

[1361] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1362] Step 1:

[1363] Users: Access the interface and register or log in.

[1364] Enter your name, email address, and password.

[1365] Output: The user information is sent to the server.

[1366] Terminal: Sends the entered information to the server.

[1367] Specific operation: The terminal converts the input data into JSON format and sends it to the server as an API request.

[1368] Step 2:

[1369] Server: Compares the received user information with a database and performs authentication.

[1370] Input: User information in JSON format.

[1371] Output: An authentication token or an error message.

[1372] What happens: The server runs an SQL query to verify the user information and, if there is a match, generates an authentication token (such as a JWT).

[1373] Step 3:

[1374] Server: If authentication is successful, it sends an authentication token to the device. If authentication fails, it sends an error message.

[1375] Input: An authentication token or an error message.

[1376] Output: An authentication token or an error message is sent to the terminal.

[1377] Terminal: Save the received authentication token and display the dashboard screen.

[1378] Specific operation: The device stores the authentication token in a cookie or session storage.

[1379] Step 4:

[1380] User: Type your real estate question in the chat box.

[1381] Input: A question like "What are the mortgage interest rates?"

[1382] Output: The question is sent to the system.

[1383] Terminal: Sends the entered question to the server.

[1384] Specific operation: The device converts the question into JSON format and sends it to the server as an API request.

[1385] Step 5:

[1386] Server: Passes question data to a natural language processing engine for analysis and answer generation.

[1387] Input: User question data.

[1388] Output: The answer from the natural language processing engine.

[1389] Specific operation: The server sends an API request to a natural language processing engine (e.g., OpenAI GPT-3) and receives the analysis results.

[1390] Step 6:

[1391] Server: Passes the analysis results to the emotion engine to evaluate the user's emotional state.

[1392] Input: Analysis results from the natural language processing engine and user input data.

[1393] Output: Emotion evaluation results from the emotion engine.

[1394] Specific operation: The server sends the analysis results and the user's input data to the emotion engine.

[1395] Step 7:

[1396] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[1397] Input: Analysis results and user input data.

[1398] Output: Emotion evaluation result (e.g., anxiety, relief, etc.).

[1399] Specific behavior: The emotion engine analyzes the user's text and operation history to evaluate their emotional state.

[1400] Step 8:

[1401] Server: Adjust the tone and content of the response based on the sentiment assessment results.

[1402] Input: Emotion assessment results.

[1403] Output: The adjusted answer.

[1404] Specific behavior: The server appropriately adjusts the tone of the response based on the evaluation from the emotion engine.

[1405] Step 9:

[1406] Server: Sends the final adjusted answer to the device.

[1407] Input: Adjusted answer.

[1408] Output: The answer is sent to the terminal.

[1409] Terminal: Display received responses in the chat box.

[1410] Specific operation: The device analyzes the received data and displays it in the chat box.

[1411] Through these processing steps, the system provides quick and appropriate answers to the user's questions, taking into account the user's emotional state in the process, thereby reducing the user's anxiety.

[1412] (Application example 2)

[1413] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1414] Existing real estate transaction support systems do not take into account the user's emotional state, which can lead to users receiving information with feelings of anxiety or distrust. Furthermore, information provided through the dialogue interface may not be adequately matched with the user's desired conditions or history, resulting in inappropriate information being provided. Furthermore, there are issues with insufficient efficiency and security in user authentication.

[1415] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for providing an interface accessed by the user, means for receiving input from the user and sending it to the server, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving an answer and presenting it to the user, means for recognizing the user's emotions and adjusting the answer content based on the results, means for comparing the analysis results with the user's history and desired conditions based on the user's emotional state and adding related information, and means for comparing the user's authentication information with a database and issuing an authentication token. This makes it possible to provide appropriate information to the user in a timely manner, taking into account the user's emotional state.

[1416] A "user-accessible interface" is the means by which a user accesses a system and enters or views information.

[1417] "User input" is data, such as text or voice commands, that a user provides through an interface.

[1418] A "server" is a computer system that receives input from a user, processes it, and provides the results to the user.

[1419] A "natural language processing engine" is a program that analyzes input from users, understands their intent, and generates appropriate responses.

[1420] An "emotion engine" is a program that analyzes user input and interaction data to recognize the user's emotional state.

[1421] An "authentication token" is a digital key that proves that a user is authenticated when accessing a system.

[1422] The "dashboard screen" is the main screen that is displayed when a user logs in to the system and allows the user to perform operations and check information.

[1423] A "chat box" is an interactive input field where users can freely enter questions or messages.

[1424] "Adjusting the answer content" refers to the act of optimizing the generated answer according to the user's emotional state and providing the most appropriate information for the user's situation.

[1425] "Analysis results" refers to information resulting from the analysis of user input by a natural language processing engine or emotion engine.

[1426] "History and desired conditions" refers to data such as information entered by the user in the past and desired conditions.

[1427] "Related information" is supplementary or additional information provided based on the user's question or situation.

[1428] This invention is applied to a real estate sales support system called "Smart Consulting Glasses." The smart glasses, which are used by real estate consultants when dealing with customers in brick-and-mortar stores, are used to understand the user's emotional state and provide more appropriate information. The purpose of this invention is to enable users to receive fair and efficient support for specific questions and inquiries through an interactive interface.

[1429] System configuration

[1430] Hardware and Software Configuration

[1431] Hardware: smart glasses, camera, display, microphone, server.

[1432] Software: Emotion Recognition model, Transformers library (for natural language processing), OpenCV (image processing framework), Speech-to-Text engine (audio to text conversion).

[1433] Overall system flow

[1434] 1. User authentication and initial setup:

[1435] The user puts on the smart glasses and logs in or registers.

[1436] The terminal accepts this operation and transmits the input information to the server.

[1437] The server checks the authentication information against a database, generates an authentication token, and sends it to the terminal.

[1438] The device receives the authentication token and displays the dashboard screen.

[1439] 2. User input and submit question:

[1440] Users use the smart glasses interface to input real estate questions and inquiries.

[1441] For example, ask a voice question such as, "Please tell me about mortgage interest rates."

[1442] The device converts the voice into text and sends the input data to the server.

[1443] 3. Analysis and Answer Generation:

[1444] A natural language processing engine analyzes the user's question, understands their intent, and generates the most appropriate answer.

[1445] For example, generate an answer like, "Current mortgage interest rates average around 2.5%, but this can vary depending on the terms."

[1446] 4. Emotion recognition and response adjustment:

[1447] The emotion engine analyzes the user's facial expressions from camera footage and recognizes their emotional state.

[1448] If the user is perceived as feeling anxious, the emotion engine will adjust its responses based on that information.

[1449] For example, provide additional information such as "We will also provide you with detailed contact information."

[1450] 5. Submitting and Presenting Your Answers:

[1451] The server sends the generated answer and the adjusted information to the display of the smart glasses.

[1452] The user checks the information displayed on the smart glasses display and considers their next action.

[1453] Specific examples

[1454] Scenarios when users ask questions

[1455] 1. User: "What are the mortgage interest rates?"

[1456] 2. Device: Converts speech into text and sends it to the server.

[1457] 3. Server: Analyzes the question using a natural language processing engine and generates an answer.

[1458] 4. Emotion engine: Recognizes anxiety from the user's facial expressions.

[1459] 5. Server: Generates answers and additional anxiety-reducing information and sends them to the device.

[1460] 6. Terminal: Shows answers and additional information.

[1461] Prompt Sentence Examples

[1462] Q: What are the interest rates for home loans?

[1463] Expression: He looks anxious.

[1464] This system can dramatically improve the quality of real estate consulting by recognizing users' anxieties and questions in real time and providing more appropriate and satisfying information.

[1465] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1466] Step 1:

[1467] User authentication and initial setup

[1468] Input: User login information (username, password)

[1469] Data processing / calculation: The user puts on the smart glasses and logs in or registers. The device accepts this operation, captures the entered login information, and sends it to the server. The server compares it with existing authentication information in a database and generates an authentication token if authentication is successful.

[1470] Output: Authentication token

[1471] Specific behavior:

[1472] The user enters their login information through the smart glasses.

[1473] The server generates an authentication token and sends it to the device.

[1474] The device receives the authentication token and displays the user's dashboard screen.

[1475] Step 2:

[1476] Enter and submit your question

[1477] Input: A spoken question asked by the user (e.g., "What are the mortgage interest rates?")

[1478] Data processing / computation: The user asks a question by voice through the smart glasses interface. The device uses a microphone to capture the voice and converts it into text using a speech-to-text engine. The converted text data is then sent to the server.

[1479] Output: Questions converted to text

[1480] Specific behavior:

[1481] The user asks aloud, "What are the interest rates for a mortgage?"

[1482] The device captures the audio and converts it into text.

[1483] Send a textual question to the server.

[1484] Step 3:

[1485] Question analysis and answer generation

[1486] Input: Textual question data

[1487] Data processing / calculation: The server passes the textual question data to a natural language processing engine for analysis. The natural language processing engine understands the intent of the question and generates the most appropriate answer.

[1488] Output: The generated answer (e.g., "Current mortgage interest rates average around 2.5%")

[1489] Specific behavior:

[1490] The server passes the text data to a natural language processing engine.

[1491] A natural language processing engine analyzes the question and generates an appropriate answer.

[1492] Step 4:

[1493] Emotion recognition and response adjustment

[1494] Input: Camera footage, generated answers

[1495] Data processing / computation: The emotion engine processes the camera footage, analyzes the user's facial expressions for each frame, and recognizes their emotional state. Based on the emotion, the server can add additional information or adjust the tone of the generated answer.

[1496] Output: Tailored response (e.g., "We will also provide you with further contact information")

[1497] Specific behavior:

[1498] The server passes the camera images from the smart glasses to the emotion engine.

[1499] The emotion engine analyzes the user's facial expressions and recognizes that they are feeling anxious.

[1500] The server appends additional anxiety-reducing information to the response.

[1501] Step 5:

[1502] Submitting and Presenting Answers

[1503] Input: Adjusted Answer

[1504] Data processing / calculation: The server sends the adjusted answer to the smart glasses display and displays it to the user. The user confirms the presented information and considers their next action.

[1505] Output: The answer is displayed

[1506] Specific behavior:

[1507] The server sends the adjusted response to the terminal.

[1508] The device displays the answer on the smart glasses display.

[1509] The above is the specific flow and operation of each processing step of the system for realizing the application example.

[1510] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1511] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1512] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1513] [Fourth embodiment]

[1514] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1515] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1516] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1517] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1518] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1519] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1520] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1521] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1522] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1523] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1524] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1525] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1526] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1527] This invention realizes a real estate buying and selling support system called "Smart Consulting." The purpose of this system is to provide fair and efficient support when users obtain information and support regarding real estate buying and selling.

[1528] System configuration

[1529] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[1530] Program processing

[1531] The operation of the system is described below.

[1532] 1. User authentication and initial setup

[1533] Users access "Smart Consult" through a web browser or smartphone app and first log in or register. The device accepts this operation and sends the entered information to the server. The server compares the information with information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard.

[1534] 2. Enter and submit your question

[1535] Users can input real estate-related questions or inquiries into the chat box. For example, if a user types a question like "What are the interest rates for a mortgage?", the device sends this input to the server. The server then passes the input question to a natural language processing engine for analysis.

[1536] 3. Question Analysis and Answer Generation

[1537] The natural language processing engine analyzes the intent of the user's question. Based on the results of this analysis, it generates the most appropriate answer. For example, in response to a question about mortgage interest rates, it generates the answer, "Current mortgage interest rates average around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1538] 4. Sending the answer and showing it to the user

[1539] The server sends the generated answer to the device, which displays it on the user's screen, allowing the user to review the information and ask further questions if necessary.

[1540] Specific examples

[1541] First-Time User Scenario

[1542] 1. User: Download the smartphone app and open it for the first time.

[1543] 2. Device: Display the new registration screen.

[1544] 3. User: Enter your name, email address, and password and submit.

[1545] 4. Device: Sends user information to the server.

[1546] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[1547] 6. Terminal: Displays the dashboard and guides you through the available functions.

[1548] Question-answering scenario

[1549] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[1550] 2. Terminal: Sends the entered question to the server.

[1551] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1552] 4. Server: Sends the generated answer to the device.

[1553] 5. Terminal: Display the answer on the user's screen.

[1554] 6. User: Check the displayed information and consider your next action.

[1555] This system provides users with information efficiently and fairly, helping to alleviate their concerns and support their decision-making. In particular, it is capable of providing detailed and accurate information quickly to support the major decision of buying or selling real estate.

[1556] The processing flow will be explained below.

[1557] Step 1:

[1558] Users access the system through a smartphone app or web browser, log in or register, and enter their first name, email address, and password, then click the submit button.

[1559] Step 2:

[1560] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[1561] Step 3:

[1562] If the authentication is successful, the server issues an authentication token and sends it to the terminal, which receives the token and displays the dashboard screen to the user.

[1563] Step 4:

[1564] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[1565] Step 5:

[1566] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[1567] Step 6:

[1568] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[1569] Step 7:

[1570] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1571] Step 8:

[1572] The server generates a response and sends it to the device, which displays it in the user's chat box. The user can then confirm the displayed information.

[1573] Step 9:

[1574] The user continues to ask questions as needed, for example, "Do you have any recommendations for properties with these criteria?" The device sends the new question to the server and repeats the process from step 5.

[1575] Step 10:

[1576] The server matches the user's history and preferences and adds relevant information, such as suggesting property listings in a particular area or price range based on the user's previous questions.

[1577] Step 11:

[1578] The server sends the relevant information to the device, which then presents it to the user, who then reviews the suggested information and considers their next course of action.

[1579] In this way, this system efficiently and fairly provides information in response to user questions and inquiries. Users can quickly obtain detailed information about real estate transactions, reducing their anxiety.

[1580] Example 1

[1581] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1582] When buying and selling real estate, it has been difficult for users to quickly and appropriately obtain the information they need. Conventional methods require consulting with experts, which takes time and costs money. Another issue is that it is difficult for users to efficiently obtain information that best suits their situation and desired conditions.

[1583] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1584] In this invention, the server includes a means for providing an interface for users to access, a means for receiving input from users and sending it to the server, a means for passing the input to a natural language processing engine for analysis and answer generation, a means for receiving the answer and presenting it to the user, and a means for comparing the user's authentication information with a database and issuing an authentication token. This allows users to easily ask questions or get advice about real estate, and to receive information efficiently and fairly.

[1585] "User" means any individual or entity that accesses the System and seeks information or assistance regarding real estate.

[1586] "Interface" refers to the screen and input means that users use to access and operate the system.

[1587] "Server" refers to a computer system that receives input from a user, analyzes and processes it, and returns the results to the user.

[1588] A "natural language processing engine" refers to an artificial intelligence technology that analyzes user input, understands intent, and generates appropriate answers.

[1589] "Authentication Token" refers to a digital certificate that indicates a user is authenticated when accessing a system.

[1590] "Database" refers to a system that manages and stores data such as user information, answers to questions, and history.

[1591] "Parsing" refers to the process by which a natural language processing engine understands a user's input and understands their intent.

[1592] "Answer generation" refers to the process by which a natural language processing engine creates an appropriate answer to a question.

[1593] The present invention is a system for users to obtain information and support regarding real estate transactions, and aims to provide efficient and fair support. This system is configured as follows.

[1594] System configuration

[1595] The system includes an interface accessed by the user, a means for sending input from the user to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, and a means for comparing the user's authentication information with a database and issuing an authentication token.

[1596] Hardware and Software Configuration

[1597] User: Accesses the system via an internet connection using a smartphone or PC.

[1598] Terminal: A device that accepts user input and sends it to a server. Examples include smartphone apps and web browsers.

[1599] Server: Manages the database (e.g., MySQL or PostgreSQL) and uses a natural language processing engine (e.g., GPT-3 or BERT) to analyze user questions and generate answers.

[1600] Natural Language Processing Engine: Artificial intelligence techniques for understanding user input and understanding intent, such as GPT-3 and BERT.

[1601] Program processing

[1602] The system process is as follows:

[1603] User authentication and initial setup

[1604] 1. User: Access the system from a smartphone app or web browser and register or log in.

[1605] 2. Device: Sends the entered name, email address, and password to the server.

[1606] 3. Server: Compares with the database, and if authentication is successful, issues an authentication token and sends it to the terminal.

[1607] 4. Terminal: Receives the authentication token and displays the user's dashboard.

[1608] Enter and submit your question

[1609] 1. User: Type your real estate question into the chat box on the screen.

[1610] 2. Terminal: Sends a query to the server.

[1611] Parsing questions and generating answers

[1612] 1. Server: Passes the question to the natural language processing engine and requests analysis.

[1613] 2. Natural language processing engine: Analyzes the intent of the user's question and generates the most appropriate answer.

[1614] Example: To the question "What are mortgage interest rates?", the answer would be: "Current mortgage interest rates average around 2.5%. However, this can vary depending on your circumstances, so we recommend you inquire with your lender."

[1615] Sending the answer and showing it to the user

[1616] 1. Server: Sends the generated answer to the device.

[1617] 2. Terminal: Displays the received answer on the user's screen.

[1618] Specific examples

[1619] Below is an example of a prompt sentence to input to the generative AI model.

[1620] Prompt Sentence Examples

[1621] Q: A user asks, "What are the mortgage interest rates?" Generate a suitable answer to this question.

[1622] A: The current average interest rate for a home loan is around 2.5%. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution.

[1623] The system utilizes efficient natural language processing technology to provide users with prompt and appropriate information, thereby supporting the important decision-making process of buying and selling real estate, alleviating users' concerns and enabling them to obtain information efficiently.

[1624] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1625] Step 1:

[1626] User: Access the system from a smartphone app or web browser and register or log in.

[1627] Input: The name, email address, and password entered by the user.

[1628] What happens: A user opens the app or browser, enters the required information, and clicks the submit button.

[1629] Output: The entered user information is passed to the terminal.

[1630] Step 2:

[1631] Terminal: Sends information entered by the user to the server.

[1632] Input: Name, email address, and password received from the user.

[1633] What it does: Input information is packaged in an appropriate format and sent to the server as an HTTP request.

[1634] Output: User information is passed to the server.

[1635] Step 3:

[1636] Server: Compares the received user information with a database.

[1637] Input: User information sent from the device.

[1638] How it works: The server compares the new user information with existing information in a database (e.g., MySQL or PostgreSQL) and authenticates them.

[1639] Output: If authentication is successful, an authentication token is generated.

[1640] Step 4:

[1641] Server: If authentication is successful, generate an authentication token and send it to the device.

[1642] Input: User information matching results.

[1643] What it does: Generates an authentication token and constructs an HTTP response to send it to the device.

[1644] Output: The authentication token is sent to the device.

[1645] Step 5:

[1646] Terminal: Receives the authentication token and displays the user's dashboard.

[1647] Input: The received authentication token.

[1648] What it does: Stores the authentication token and displays the dashboard screen to the user.

[1649] Output: The user's dashboard screen is displayed.

[1650] Step 6:

[1651] User: Type your real estate question into the chat box on the screen.

[1652] Input: The question the user types into the chat box.

[1653] Action: Enter a question and click the submit button.

[1654] Output: The entered question is sent to the terminal.

[1655] Step 7:

[1656] Terminal: Sends the entered question to the server.

[1657] Input: The question received from the user.

[1658] What it does: Packages the question into an appropriate format and sends it to the server as an HTTP request.

[1659] Output: The question is passed to the server.

[1660] Step 8:

[1661] Server: Passes the received question to the natural language processing engine and requests analysis.

[1662] Input: Question sent from terminal.

[1663] How it works: A question is fed into a generative AI model (such as GPT-3 or BERT), which analyzes it and generates an answer.

[1664] Output: The generated answer is sent back to the server.

[1665] Step 9:

[1666] Server: Sends the generated answer to the device.

[1667] Input: The answer returned by the natural language processing engine.

[1668] What it does: Constructs the answer as an HTTP response and sends it to the device.

[1669] Output: The answer is sent to the terminal.

[1670] Step 10:

[1671] Terminal: Displays the received answer on the user's screen.

[1672] Input: The answer sent by the server.

[1673] What it does: Displays the answer on the screen for the user to review.

[1674] Output: The answer is displayed on the user's screen.

[1675] These are the specific processing steps of the system, which allows users to get fast and accurate answers to their real estate questions.

[1676] (Application example 1)

[1677] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1678] Conventional real estate purchase and sale support systems have difficulty in providing users with the information they need quickly and appropriately, and a solution that provides efficient, fair, and detailed information is needed. In addition, there is a lack of means for users to resolve their questions and concerns in real time, so technology that can quickly support users in making decisions is needed.

[1679] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1680] In this invention, the server includes means for providing a display device accessed by a user, means for receiving input from the user and sending it to a processing device, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving the generated answer and presenting it to the user, and means for linking with a database for adding related information based on the analysis results, thereby enabling users to obtain real estate information in real time and make decisions quickly.

[1681] A "display device" is a device that allows a user to visually confirm information.

[1682] A "processor" is a device for receiving input from a user and analyzing and processing it.

[1683] A "natural language processing engine" is a system and software that analyzes text data, understands the user's intent, and generates appropriate answers.

[1684] A "generated answer" is information provided as a result of analysis by a natural language processing engine.

[1685] A "database" is a system that stores user history and related information and provides that information as needed.

[1686] "User history" refers to a record of searches and entries made by a user in the past, as well as any related information.

[1687] "Desired conditions" are specific requirements or conditions that a user specifies when providing information about a property.

[1688] "Authentication Token" means a piece of authentication information that uniquely identifies a user and is issued to the user when the user accesses a system.

[1689] "Surrounding environment information" refers to information about facilities and transportation methods around the real estate property.

[1690] "Additional information" is supplementary information that is deemed highly relevant based on the user's input and history.

[1691] This invention aims to realize a real estate buying and selling support system called "Smart Consulting Real Estate Assistant (Store Version)." The purpose of this system is to enable users to obtain real estate information in real time at a physical store and receive fair and efficient support.

[1692] System configuration

[1693] The system includes a display device accessed by a user, a means for transmitting input from the user to a processing device, a natural language processing engine for analysis and answer generation, a means for providing the generated answer, and a database for linking related information.

[1694] The hardware used includes tablets, smart glasses, and head-mounted displays, which are used as display devices for users to directly view information. Servers and databases are used to receive, process, and store user input. The software used includes natural language processing engines (e.g., Google Cloud Natural Language API, Amazon Comprehend), authentication systems (e.g., OAuth 2.0), and UI frameworks (e.g., React Native, Flutter).

[1695] Program processing

[1696] 1. User authentication and initial setup

[1697] The user accesses the system through a display device (tablet or smart glasses) and logs in or registers. The user's input information is sent to the server and checked against a database. If authentication is successful, an authentication token is issued and sent to the user's display device. At this stage, the user's dashboard is displayed, and available functions are explained.

[1698] 2. Enter and submit your question

[1699] The user uses the chat box to input questions or inquiries about real estate. For example, they can input, "Please tell me about the surrounding area." This input is sent from the display device to the server.

[1700] 3. Question Analysis and Answer Generation

[1701] The server receives the input question and passes it to a natural language processing engine, which analyzes the user's question and generates the most appropriate answer.

[1702] 4. Providing Additional Information

[1703] Based on the analysis results, related information is obtained from a database that links the user's history, desired conditions, and related information, such as information on nearby facilities, transportation, and the environment.

[1704] 5. View Answers

[1705] The server sends the generated answer to a display device and presents it to the user, who then checks the information and considers their next course of action.

[1706] This system is a powerful support tool that allows users to efficiently and fairly obtain real estate information in physical stores and make quick decisions.

[1707] Examples and prompts

[1708] In-store usage scenario

[1709] 1. Customer: Picks up the tablet and types, "I'd like to know about the surrounding area."

[1710] 2. Terminal: Sends a query to the server.

[1711] 3. Server: Analyzes the question using a natural language processing engine.

[1712] 4. Server: Based on the analysis results, obtain surrounding information from the database.

[1713] 5. Server: Sends the generated answer to the device.

[1714] 6. Terminal: Show the answer to the customer. For example, "There are schools, supermarkets, and train stations nearby."

[1715] 7. Visitors: Review the displayed information and explore properties that interest them further.

[1716] Example prompts for generative AI models

[1717] Sample prompt: "Please provide information about the surrounding area of ​​the property."

[1718] Example prompt: "What are the best mortgage terms?"

[1719] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1720] Step 1: User authentication and initial setup

[1721] 1. The user picks up a display device (tablet or smart glasses), accesses the system, and logs in or registers.

[1722] Input: Name, Email Address, Password

[1723] Processing: The input information is sent from the terminal to the server. The server checks the database to see if the user is registered. If the user is new, the new user information is saved in the database.

[1724] Output: An authentication token is issued and sent to the device.

[1725] Step 2: View the dashboard

[1726] 1. The device receives the authentication token and displays the user's dashboard.

[1727] Input: Authentication Token

[1728] Processing: The device receives the authentication token, checks the features the user has access to, and configures the dashboard.

[1729] Output: The dashboard screen is displayed.

[1730] Step 3: Enter and submit your question

[1731] 1. The user enters their real estate question or inquiry in the chat box.

[1732] Input: Questions such as "Tell me about the surrounding area"

[1733] Processing: The device sends the entered question to the server, which receives the question and prepares it for passing to the natural language processing engine.

[1734] Output: The question data is passed to a natural language processing engine.

[1735] Step 4: Parsing the question and generating an answer

[1736] 1. The server passes the question to a natural language processing engine for analysis and answer generation.

[1737] Input: User question data

[1738] Processing: A natural language processing engine (e.g., Google Cloud Natural Language API, Amazon Comprehend) analyzes the question and understands the user's intent. Based on the analysis results, it generates the most appropriate answer.

[1739] Output: The generated answer

[1740] Step 5: Obtain additional information

[1741] 1. Based on the analysis results, the server retrieves relevant information from the database.

[1742] Input: Analysis results, user history and desired conditions

[1743] Processing: The server connects to the database to search for and retrieve relevant information (such as information about the surrounding environment) based on the user's history and desired conditions.

[1744] Output: Additional relevant information

[1745] Step 6: Submit and view your answers and additional information

[1746] 1. The server sends the generated answer and any additional relevant information to the terminal.

[1747] Input: Generated answers, related information

[1748] Processing: The server aggregates the generated answers and related information and sends them to the terminal, which receives them and displays them to the user.

[1749] Output: Answers and related information displayed on the user's tablet or smart glasses

[1750] Step 7: User confirmation and further action

[1751] 1. The user reviews the displayed information and considers their next question or action.

[1752] Input: Displayed answers and related information

[1753] Processing: If the user enters an additional question, process the new input again according to steps 3 through 6.

[1754] Output: If a new question is input, a continuous question-answering cycle begins.

[1755] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1756] This invention provides more appropriate support to users by combining a real estate buying and selling support system called "Smart Consulting" with an emotion engine that recognizes user emotions. The system aims to provide fair, efficient, and emotion-responsive support when users obtain information and support related to real estate buying and selling.

[1757] System configuration

[1758] The system includes an interface accessed by the user, a means for sending user input to a server, a means for analyzing the input using a natural language processing engine and generating an answer, a means for presenting the generated answer to the user, a means for comparing the analysis results with the user's history and desired conditions and adding related information, a means for comparing the user's authentication information with a database and issuing an authentication token, and an emotion engine for recognizing the user's emotions.

[1759] Program processing

[1760] The operation of the system is described below.

[1761] 1. User authentication and initial setup

[1762] The user accesses the interface and logs in or registers. The device accepts this operation and sends the entered information to the server. The server compares the information with the information in the database, and if authentication is successful, issues an authentication token and sends it to the device. The device receives the authentication token and displays the user's dashboard screen.

[1763] 2. Enter and submit your question

[1764] The user enters a real estate question or inquiry into the chat box. For example, they might type, "Please tell me about mortgage interest rates." The device then sends this input to the server, which then passes the input data to a natural language processing engine for analysis.

[1765] 3. Question Analysis and Answer Generation

[1766] The natural language processing engine analyzes the intent of the user's question and generates the most appropriate answer based on the results of this analysis. For example, it creates an answer such as, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1767] 4. Recognizing emotions and adjusting responses

[1768] The emotion engine analyzes the user's input text and interaction data to assess the user's emotional state. For example, it may recognize from the user's language and frequent questions that the user is feeling anxious. Based on this, the emotion engine can adjust the content and tone of its responses and provide additional information to ease the user's anxiety.

[1769] 5. Sending the answer and showing it to the user

[1770] The server sends the generated answers and the results of the emotion engine adjustments to the device, which displays the answers in the user's chat box. The user can review this information and continue asking further questions if necessary.

[1771] Specific examples

[1772] First-Time User Scenario

[1773] 1. User: Download the smartphone app and open it for the first time.

[1774] 2. Device: Display the new registration screen.

[1775] 3. User: Enter your name, email address, and password and submit.

[1776] 4. Device: Sends user information to the server.

[1777] 5. Server: Stores the information in a database, issues an authentication token, and sends it to the device.

[1778] 6. Terminal: Displays the dashboard and guides you through the available functions.

[1779] Question-answering scenario

[1780] 1. User: Type "What are the mortgage interest rates?" into the chat box.

[1781] 2. Terminal: Sends the entered question to the server.

[1782] 3. Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1783] 4. Emotion Engine: Analyzes user input, recognizes when the user is feeling anxious, and generates corresponding countermeasures.

[1784] 5. Server: Sends the generated answer and adjusted information to the terminal.

[1785] 6. Device: The answer is displayed on the user's screen. The user checks the displayed information and considers their next action.

[1786] This system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, allowing it to provide more attentive support. Users can not only quickly obtain detailed information about real estate sales and purchases, but also reduce anxiety during the process.

[1787] The processing flow will be explained below.

[1788] Step 1:

[1789] Users access the system through a smartphone app or web browser to register or log in. They enter their name, email address, and password and click the "Submit" button.

[1790] Step 2:

[1791] The device sends the entered user information to the server, which then checks it against existing information in its database and, if it matches, allows the user to log in; if it doesn't, it saves the user's information in the database as a new user.

[1792] Step 3:

[1793] If authentication is successful, the server issues an authentication token and sends it to the device. The device receives this token and displays the user's dashboard screen.

[1794] Step 4:

[1795] Users can enter their questions or inquiries into the chat box on the dashboard screen. For example, they can type, "Please tell me about mortgage interest rates."

[1796] Step 5:

[1797] The device captures the user's input and sends it to a server, which receives the input and passes it to a natural language processing engine.

[1798] Step 6:

[1799] The server's natural language processing engine analyzes the user's question, specifically by breaking down the text of the question and running a process to understand its meaning.

[1800] Step 7:

[1801] The natural language processing engine generates an appropriate answer based on the analysis results, for example, "Current mortgage interest rates are around 2.5% on average. However, this may vary depending on the conditions, so we recommend that you inquire with your financial institution."

[1802] Step 8:

[1803] The emotion engine analyzes user input text and interaction data to assess the user's emotional state. For example, it may recognize that the user is feeling anxious based on their language and frequent questions.

[1804] Step 9:

[1805] Based on the analysis, the sentiment engine adjusts the tone and content of the generated answers, for example, providing a more confident response to a user who is feeling anxious, with additional advice and resources.

[1806] Step 10:

[1807] The server sends the final answer and the adjustment results of the emotion engine to the device, which receives them and displays them in the user's chat box.

[1808] Step 11:

[1809] The user checks the displayed information and continues to ask questions if necessary. For example, enter the question again, "Do you have any recommended properties that meet these criteria?" The device then sends the new question to the server and repeats the process from step 5.

[1810] The above is the specific processing flow of the "Smart Consulting" system. In this way, this system not only provides efficient and fair information in response to users' questions and inquiries, but also adjusts its response according to the user's emotional state, making it possible to provide more detailed support. Not only can users quickly obtain detailed information about real estate sales and purchases, but they can also reduce their anxiety during the process.

[1811] Example 2

[1812] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1813] Conventional real estate buying and selling support systems provide efficient and accurate answers to user input, but they do not take into account the user's emotional state, which means that the system does not fully resolve the user's anxieties or questions.In addition, they do not suggest related information based on the user's history or desired conditions, which means that user convenience is not improved.

[1814] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1815] In this invention, the server includes a means for analyzing user input using a natural language processing engine and generating a response, a means for evaluating the user's emotional state based on the analysis results and adjusting the tone and content of the response, and a means for verifying the user's authentication information against a database and issuing an authentication token. This makes it possible to provide emotionally responsive support to the user and alleviate their anxieties and doubts. Furthermore, by suggesting related information based on the user's history and desired conditions, user convenience is improved.

[1816] "Interface" refers to the screen or operating section that allows users to access the system and input information.

[1817] A "natural language processing engine" refers to an algorithm or program that analyzes user input, understands its intent, and generates an answer.

[1818] An "emotion engine" refers to an algorithm or program that analyzes user input data and interactions and assesses the user's emotional state.

[1819] An "authentication token" is a temporary identification code issued when a user logs in to a system, and is used to verify the user's authentication status.

[1820] "User history" refers to the record of the user's past operations and inquiries.

[1821] "Desired conditions" refers to specific requests or conditions that a user specifies to the system.

[1822] "Tone of the answer" refers to the expression and atmosphere of the generated answer, and is a factor that determines how it is conveyed to the user.

[1823] "Related information" refers to additional useful data or suggestions provided in response to a user's question or input.

[1824] "User authentication" refers to the process of verifying that a user is a legitimate user when logging into a system.

[1825] MODE FOR CARRYING OUT THE INVENTION

[1826] The present invention provides a real estate buying and selling support system that provides more appropriate support by combining an emotion engine that recognizes the user's emotions. The system configuration and operation are described in detail below.

[1827] System Configuration

[1828] This system is configured using the following hardware and software.

[1829] User device: A device such as a PC or smartphone used by a user.

[1830] Server: A server that performs data processing, authentication, natural language processing, and emotion recognition. Specifically, this includes database servers, application servers, etc.

[1831] Database: Stores user registration information, authentication information, past interactions, historical information, etc.

[1832] Natural language processing engines: Examples include Google BERT and OpenAI GPT-3.

[1833] Emotion engine: A program for analyzing user input text and interaction data.

[1834] Data processing and calculation

[1835] User authentication

[1836] A user accesses the interface and logs in or registers.

[1837] Terminal: The entered user information is sent to the server in JSON format.

[1838] Server: Compares the received information with the database, generates an authentication token (such as a JWT), and sends it to the device.

[1839] Enter and submit your question

[1840] The user types a question into the chat box.

[1841] Example: "What are the mortgage interest rates?"

[1842] Terminal: Sends the entered question to the server.

[1843] Question analysis and answer generation

[1844] Server: Passes the question to a natural language processing engine for analysis and answer generation.

[1845] The natural language processing engine uses Google BERT and OpenAI GPT-3 to analyze the intent of the question and generate appropriate answers.

[1846] Example answer: "Current mortgage interest rates average around 2.5%. However, this varies depending on the terms, so we recommend checking with your financial institution."

[1847] Recognizing emotions and adjusting responses

[1848] Server: Passes the analysis results and user input to the emotion engine.

[1849] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[1850] Example: A user's frequent questions and negative language indicate anxiety.

[1851] Server: Adjusts the tone and content of the response based on the evaluation results from the emotion engine.

[1852] Example: To ease concerns, additional information is added, such as, "Don't worry. Current mortgage interest rates average around 2.5%. We recommend checking with your financial institution for details."

[1853] Providing an answer

[1854] Server: Sends the adjusted answer to the device.

[1855] Terminal: Display received responses in the chat box.

[1856] A key feature of this system is that it adjusts responses based on the user's emotional state. As a result, users not only receive detailed information about real estate transactions, but also reduce any anxiety or doubts they may have during the process. It also suggests related information based on the user's history and desired conditions, improving user convenience and satisfaction.

[1857] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1858] Step 1:

[1859] Users: Access the interface and register or log in.

[1860] Enter your name, email address, and password.

[1861] Output: The user information is sent to the server.

[1862] Terminal: Sends the entered information to the server.

[1863] Specific operation: The terminal converts the input data into JSON format and sends it to the server as an API request.

[1864] Step 2:

[1865] Server: Compares the received user information with a database and performs authentication.

[1866] Input: User information in JSON format.

[1867] Output: An authentication token or an error message.

[1868] What happens: The server runs an SQL query to verify the user information and, if there is a match, generates an authentication token (such as a JWT).

[1869] Step 3:

[1870] Server: If authentication is successful, it sends an authentication token to the device. If authentication fails, it sends an error message.

[1871] Input: An authentication token or an error message.

[1872] Output: An authentication token or an error message is sent to the terminal.

[1873] Terminal: Save the received authentication token and display the dashboard screen.

[1874] Specific operation: The device stores the authentication token in a cookie or session storage.

[1875] Step 4:

[1876] User: Type your real estate question in the chat box.

[1877] Input: A question like "What are the mortgage interest rates?"

[1878] Output: The question is sent to the system.

[1879] Terminal: Sends the entered question to the server.

[1880] Specific operation: The device converts the question into JSON format and sends it to the server as an API request.

[1881] Step 5:

[1882] Server: Passes question data to a natural language processing engine for analysis and answer generation.

[1883] Input: User question data.

[1884] Output: The answer from the natural language processing engine.

[1885] Specific operation: The server sends an API request to a natural language processing engine (e.g., OpenAI GPT-3) and receives the analysis results.

[1886] Step 6:

[1887] Server: Passes the analysis results to the emotion engine to evaluate the user's emotional state.

[1888] Input: Analysis results from the natural language processing engine and user input data.

[1889] Output: Emotion evaluation results from the emotion engine.

[1890] Specific operation: The server sends the analysis results and the user's input data to the emotion engine.

[1891] Step 7:

[1892] Emotion engine: Evaluates the user's emotional state and determines whether they are anxious or suspicious.

[1893] Input: Analysis results and user input data.

[1894] Output: Emotion evaluation result (e.g., anxiety, relief, etc.).

[1895] Specific behavior: The emotion engine analyzes the user's text and operation history to evaluate their emotional state.

[1896] Step 8:

[1897] Server: Adjust the tone and content of the response based on the sentiment assessment results.

[1898] Input: Emotion assessment results.

[1899] Output: The adjusted answer.

[1900] Specific behavior: The server appropriately adjusts the tone of the response based on the evaluation from the emotion engine.

[1901] Step 9:

[1902] Server: Sends the final adjusted answer to the device.

[1903] Input: Adjusted answer.

[1904] Output: The answer is sent to the terminal.

[1905] Terminal: Display received responses in the chat box.

[1906] Specific operation: The device analyzes the received data and displays it in the chat box.

[1907] Through these processing steps, the system provides quick and appropriate answers to the user's questions, taking into account the user's emotional state in the process, thereby reducing the user's anxiety.

[1908] (Application example 2)

[1909] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1910] Existing real estate transaction support systems do not take into account the user's emotional state, which can lead to users receiving information with feelings of anxiety or distrust. Furthermore, information provided through the dialogue interface may not be adequately matched with the user's desired conditions or history, resulting in inappropriate information being provided. Furthermore, there are issues with insufficient efficiency and security in user authentication.

[1911] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for providing an interface accessed by the user, means for receiving input from the user and sending it to the server, means for passing the input to a natural language processing engine for analysis and answer generation, means for receiving an answer and presenting it to the user, means for recognizing the user's emotions and adjusting the answer content based on the results, means for comparing the analysis results with the user's history and desired conditions based on the user's emotional state and adding related information, and means for comparing the user's authentication information with a database and issuing an authentication token. This makes it possible to provide appropriate information to the user in a timely manner, taking into account the user's emotional state.

[1912] A "user-accessible interface" is the means by which a user accesses a system and enters or views information.

[1913] "User input" is data, such as text or voice commands, that a user provides through an interface.

[1914] A "server" is a computer system that receives input from a user, processes it, and provides the results to the user.

[1915] A "natural language processing engine" is a program that analyzes input from users, understands their intent, and generates appropriate responses.

[1916] An "emotion engine" is a program that analyzes user input and interaction data to recognize the user's emotional state.

[1917] An "authentication token" is a digital key that proves that a user is authenticated when accessing a system.

[1918] The "dashboard screen" is the main screen that is displayed when a user logs in to the system and allows the user to perform operations and check information.

[1919] A "chat box" is an interactive input field where users can freely enter questions or messages.

[1920] "Adjusting the answer content" refers to the act of optimizing the generated answer according to the user's emotional state and providing the most appropriate information for the user's situation.

[1921] "Analysis results" refers to information resulting from the analysis of user input by a natural language processing engine or emotion engine.

[1922] "History and desired conditions" refers to data such as information entered by the user in the past and desired conditions.

[1923] "Related information" is supplementary or additional information provided based on the user's question or situation.

[1924] This invention is applied to a real estate sales support system called "Smart Consulting Glasses." The smart glasses, which are used by real estate consultants when dealing with customers in brick-and-mortar stores, are used to understand the user's emotional state and provide more appropriate information. The purpose of this invention is to enable users to receive fair and efficient support for specific questions and inquiries through an interactive interface.

[1925] System configuration

[1926] Hardware and Software Configuration

[1927] Hardware: smart glasses, camera, display, microphone, server.

[1928] Software: Emotion Recognition model, Transformers library (for natural language processing), OpenCV (image processing framework), Speech-to-Text engine (audio to text conversion).

[1929] Overall system flow

[1930] 1. User authentication and initial setup:

[1931] The user puts on the smart glasses and logs in or registers.

[1932] The terminal accepts this operation and transmits the input information to the server.

[1933] The server checks the authentication information against a database, generates an authentication token, and sends it to the terminal.

[1934] The device receives the authentication token and displays the dashboard screen.

[1935] 2. User input and submit question:

[1936] Users use the smart glasses interface to input real estate questions and inquiries.

[1937] For example, ask a voice question such as, "Please tell me about mortgage interest rates."

[1938] The device converts the voice into text and sends the input data to the server.

[1939] 3. Analysis and Answer Generation:

[1940] A natural language processing engine analyzes the user's question, understands their intent, and generates the most appropriate answer.

[1941] For example, generate an answer like, "Current mortgage interest rates average around 2.5%, but this can vary depending on the terms."

[1942] 4. Emotion recognition and response adjustment:

[1943] The emotion engine analyzes the user's facial expressions from camera footage and recognizes their emotional state.

[1944] If the user is perceived as feeling anxious, the emotion engine will adjust its responses based on that information.

[1945] For example, provide additional information such as "We will also provide you with detailed contact information."

[1946] 5. Submitting and Presenting Your Answers:

[1947] The server sends the generated answer and the adjusted information to the display of the smart glasses.

[1948] The user checks the information displayed on the smart glasses display and considers their next action.

[1949] Specific examples

[1950] Scenarios when users ask questions

[1951] 1. User: "What are the mortgage interest rates?"

[1952] 2. Device: Converts speech into text and sends it to the server.

[1953] 3. Server: Analyzes the question using a natural language processing engine and generates an answer.

[1954] 4. Emotion engine: Recognizes anxiety from the user's facial expressions.

[1955] 5. Server: Generates answers and additional anxiety-reducing information and sends them to the device.

[1956] 6. Terminal: Shows answers and additional information.

[1957] Prompt Sentence Examples

[1958] Q: What are the interest rates for home loans?

[1959] Expression: He looks anxious.

[1960] This system can dramatically improve the quality of real estate consulting by recognizing users' anxieties and questions in real time and providing more appropriate and satisfying information.

[1961] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1962] Step 1:

[1963] User authentication and initial setup

[1964] Input: User login information (username, password)

[1965] Data processing / calculation: The user puts on the smart glasses and logs in or registers. The device accepts this operation, captures the entered login information, and sends it to the server. The server compares it with existing authentication information in a database and generates an authentication token if authentication is successful.

[1966] Output: Authentication token

[1967] Specific behavior:

[1968] The user enters their login information through the smart glasses.

[1969] The server generates an authentication token and sends it to the device.

[1970] The device receives the authentication token and displays the user's dashboard screen.

[1971] Step 2:

[1972] Enter and submit your question

[1973] Input: A spoken question asked by the user (e.g., "What are the mortgage interest rates?")

[1974] Data processing / computation: The user asks a question by voice through the smart glasses interface. The device uses a microphone to capture the voice and converts it into text using a speech-to-text engine. The converted text data is then sent to the server.

[1975] Output: Questions converted to text

[1976] Specific behavior:

[1977] The user asks aloud, "What are the interest rates for a mortgage?"

[1978] The device captures the audio and converts it into text.

[1979] Send a textual question to the server.

[1980] Step 3:

[1981] Question analysis and answer generation

[1982] Input: Textual question data

[1983] Data processing / calculation: The server passes the textual question data to a natural language processing engine for analysis. The natural language processing engine understands the intent of the question and generates the most appropriate answer.

[1984] Output: The generated answer (e.g., "Current mortgage interest rates average around 2.5%")

[1985] Specific behavior:

[1986] The server passes the text data to a natural language processing engine.

[1987] A natural language processing engine analyzes the question and generates an appropriate answer.

[1988] Step 4:

[1989] Emotion recognition and response adjustment

[1990] Input: Camera footage, generated answers

[1991] Data processing / computation: The emotion engine processes the camera footage, analyzes the user's facial expressions for each frame, and recognizes their emotional state. Based on the emotion, the server can add additional information or adjust the tone of the generated answer.

[1992] Output: Tailored response (e.g., "We will also provide you with further contact information")

[1993] Specific behavior:

[1994] The server passes the camera images from the smart glasses to the emotion engine.

[1995] The emotion engine analyzes the user's facial expressions and recognizes that they are feeling anxious.

[1996] The server appends additional anxiety-reducing information to the response.

[1997] Step 5:

[1998] Submitting and Presenting Answers

[1999] Input: Adjusted Answer

[2000] Data processing / calculation: The server sends the adjusted answer to the smart glasses display and displays it to the user. The user confirms the presented information and considers their next action.

[2001] Output: The answer is displayed

[2002] Specific behavior:

[2003] The server sends the adjusted response to the terminal.

[2004] The device displays the answer on the smart glasses display.

[2005] The above is the specific flow and operation of each processing step of the system for realizing the application example.

[2006] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2007] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2008] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2009] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2010] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2011] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2012] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2013] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2014] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2015] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2016] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2017] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2018] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2019] 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.

[2020] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2021] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2022] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2023] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2024] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2025] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2026] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2027] The following is further disclosed regarding the above embodiment.

[2028] (Claim 1)

[2029] a means for providing an interface for user access;

[2030] a means for receiving input from a user and transmitting it to a server;

[2031] a means for passing input to a natural language processing engine for analysis and answer generation;

[2032] a means of receiving and presenting the answers to the user;

[2033] A system including:

[2034] (Claim 2)

[2035] Based on the analysis results, a method for matching the user's history and desired conditions and adding related information;

[2036] The system of claim 1 further comprising:

[2037] (Claim 3)

[2038] A means of verifying the user's authentication information against a database and issuing an authentication token;

[2039] The system of claim 1 further comprising:

[2040] "Example 1"

[2041] (Claim 1)

[2042] a means for providing an interface for user access;

[2043] a means for receiving input from a user and transmitting it to a server;

[2044] a means for passing input to a natural language processing engine for analysis and answer generation;

[2045] a means of receiving and presenting the answers to the user;

[2046] A means of verifying the user's authentication information against a database and issuing an authentication token;

[2047] A system including:

[2048] (Claim 2)

[2049] Based on the analysis results, a method for matching the user's history and desired conditions and adding related information;

[2050] 10. The system of claim 1, comprising:

[2051] (Claim 3)

[2052] A means of analyzing the intent of a user's question and generating an appropriate answer using a natural language processing engine;

[2053] means for transmitting the generated answer to a server and presenting it to the user;

[2054] 10. The system of claim 1, comprising:

[2055] "Application Example 1"

[2056] (Claim 1)

[2057] means for providing a display device for user access;

[2058] means for receiving input from a user and transmitting it to a processing unit;

[2059] a means for passing input to a natural language processing engine for analysis and answer generation;

[2060] a means for receiving the generated answer and presenting it to the user;

[2061] a means for linking with a database to add relevant information based on the analysis results;

[2062] A system including:

[2063] (Claim 2)

[2064] A means of matching user history, desired conditions and related information and adding related information;

[2065] a display device that allows a user to obtain real-time information about the property;

[2066] The system of claim 1 further comprising:

[2067] (Claim 3)

[2068] A means of verifying the user's authentication information against a database and issuing an authentication token;

[2069] A means of linking to databases to provide environmental information and additional data;

[2070] The system of claim 1 further comprising:

[2071] "Example 2: Combining Emotion Engines"

[2072] (Claim 1)

[2073] a means for providing an interface for user access;

[2074] a means for receiving input from a user and transmitting it to a server;

[2075] a means for passing input to a natural language processing engine for analysis and answer generation;

[2076] Based on the analysis results, a means of assessing the user's emotional state and adjusting the tone and content of the response;

[2077] a means for presenting the tailored answer to the user;

[2078] A system including:

[2079] (Claim 2)

[2080] Based on the analysis results, a method for matching the user's history and desired conditions and adding related information;

[2081] The system of claim 1 further comprising:

[2082] (Claim 3)

[2083] A means of verifying the user's authentication information against a database and issuing an authentication token;

[2084] The system of claim 1 further comprising:

[2085] "Application example 2 when combining emotion engines"

[2086] (Claim 1)

[2087] a means for providing an interface for user access;

[2088] a means for receiving input from a user and transmitting it to a server;

[2089] a means for passing input to a natural language processing engine for analysis and answer generation;

[2090] a means of receiving and presenting the answers to the user;

[2091] A means of recognizing user sentiment and adjusting responses based on that sentiment; and

[2092] A system including:

[2093] (Claim 2)

[2094] Based on the analysis results and the user's emotional state, a means of matching the user's history and desired conditions and adding relevant information;

[2095] The system of claim 1 further comprising:

[2096] (Claim 3)

[2097] A means of verifying the user's authentication information against a database and issuing an authentication token;

[2098] The system of claim 1 further comprising: [Explanation of symbols]

[2099] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for providing an interface for user access; a means for receiving input from a user and transmitting it to a server; a means for passing input to a natural language processing engine for analysis and answer generation; a means of receiving and presenting the answers to the user; A system including:

2. Based on the analysis results, a method for matching the user's history and desired conditions and adding related information; The system of claim 1 further comprising:

3. A means of verifying the user's authentication information against a database and issuing an authentication token; The system of claim 1 further comprising:

Images