system

Abstract

The system provides a computing device that receives and analyzes user input conditions, searches for property information in a database based on these conditions, and generates a list of relevant properties. [Solution] A system comprising: a computing device means for receiving condition input from a user and analyzing the conditions; a computing device means for searching a database for property information based on the conditions and generating a list of relevant properties; a communication means for notifying the user's terminal of the property list; a computing device means for analyzing agent information related to property selection and evaluating its reliability; a display means for selecting an agent based on the evaluation and presenting it to the user along with the relevant agent information; a display screen means for integrating and managing property information and agent information in response to user operations; and a computing device means for providing personalized advice to the user and managing their action schedule.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The conventional process of searching for properties and selecting a real estate agent is laborious and time-consuming. Especially in urban areas where quick property selection is required, inefficiency has been an issue. Also, it is difficult to find properties that meet the user's desired conditions and to select an agent with guaranteed reliability, and there has been a need to improve the user experience.

Means for Solving the Problems

[0005] This invention provides a system that includes a computing device means for receiving and analyzing user condition input, searches for property information from a database based on this input, and generates a list of relevant properties. Furthermore, it includes a communication means for notifying the user's terminal of the property list, and selects and presents the most suitable agent to the user by analyzing agent information and evaluating reliability. It also includes a display screen means for integrating property information and agent information, and achieves efficient property search and agent selection through a computing device means for managing personalized advice and action schedules for the user.

[0006] "User input of conditions" refers to users providing the platform with their desired requirements and constraints when searching for properties.

[0007] "Computing device means" refers to a device that has processing capabilities, analyzes information from users, and performs property information searches and agent information evaluations.

[0008] A "database" refers to a collection of information where property information is systematically stored and can be quickly accessed as needed.

[0009] A "property list" refers to a list of property information selected based on the user's criteria.

[0010] "Communication methods" refer to technologies and systems used to send information from one point to another.

[0011] "Agent information" refers to data such as transaction records and reviews related to real estate agents.

[0012] "Assessing reliability" refers to the process of calculating the degree of reliability of a given object based on past data and criteria.

[0013] "Display means" refers to devices or interfaces used to visually present information to users.

[0014] "Personalized advice" refers to specific and individual proposals provided based on the user's individual data and actions.

[0015] "Managing an action schedule" refers to effectively organizing and adjusting the schedule related to the user's property inspection and the like.

Brief Description of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiment for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The system according to the present invention is built through the interaction of a user, a server, and a terminal. It is designed to enable users to quickly find the most suitable property and select a reliable real estate agent. A specific embodiment is described below.

[0038] First, the user enters their desired conditions through the terminal's user interface. These conditions include a wide range of information such as budget, location, floor plan, and property type. The terminal sends this information to a server where it is analyzed.

[0039] The server uses an AI algorithm to analyze the received conditions. Based on this analysis, the server searches a real estate database and extracts property information that matches the conditions. This creates a list of properties that best suit the user's desired conditions. For example, if a user enters "1LDK apartment in Tokyo, under 100,000 yen per month," the server will collect property information that meets these conditions and prepare it as a list.

[0040] Furthermore, the server also analyzes agent information. It evaluates the agent's reliability based on their past transaction data and reviews, and uses the results to select the most suitable agent for the user. The selected agent information, along with property information, is sent to the terminal and presented to the user.

[0041] The device screen displays integrated property and agent information, making it easy for users to compare and consider options. Personalized advice is also provided to users. For example, based on the user's past choices and activity history, suggestions are made to recommend viewing specific properties or to facilitate contact with agents.

[0042] Ultimately, the server manages the user's activity schedule and promptly notifies the user's device of timely reminders for viewings and signing contracts. Through this implementation, users can efficiently and rationally proceed with property searches and agent selection.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] Users fill in their desired property criteria on a terminal's input form. This includes information such as budget, preferred area, and floor plan. After the user finishes entering the information, they click the submit button, and the data is sent to the server.

[0046] Step 2:

[0047] The terminal sends the conditional data received from the user to the server. The transmitted data is processed within the server and prepared to proceed to the analysis process.

[0048] Step 3:

[0049] The server uses an AI algorithm to analyze the received data. Based on the analysis, points are assigned according to the user's criteria, and a search of the real estate database is initiated using this information.

[0050] Step 4:

[0051] The server executes an SQL query against the real estate database to search for properties that meet the user's criteria. The property information obtained from this search is collected and organized in a list format.

[0052] Step 5:

[0053] Based on the property list generated by the server, the notification system activates and prepares to send the property list to the user's terminal. During this process, arrangements are also made to send push notifications to users of new properties.

[0054] Step 6:

[0055] The server further evaluates the reliability of agents based on their past transaction history and user reviews. Based on this evaluation, it selects highly reliable agents.

[0056] Step 7:

[0057] On the terminal, property information and agent information sent from the server are displayed on the screen. Users can check the information on this screen and register favorites or make inquiries.

[0058] Step 8:

[0059] The server analyzes the user's conditions and behavioral history to generate personalized advice. For example, it might suggest viewing specific properties or prepare reminders for the necessary procedures leading up to a contract.

[0060] Step 9:

[0061] The device receives notifications from the server and displays schedule management and reminders to the user. This allows the user to understand the appropriate timing for their next action.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In today's real estate market, a challenge exists in that it is difficult for users to quickly find the optimal property and select a reliable intermediary. With traditional methods, information is scattered, making it difficult for users to choose from a vast amount of information that suits their needs. Furthermore, there is a lack of objective indicators to individually assess the reliability of each intermediary, making it difficult to proceed with transactions with peace of mind.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching for target information from a storage device based on the conditions and generating a list of corresponding targets; and means for receiving external information and continuously updating the latest information that matches the user's desired conditions. This enables the user to efficiently and quickly find the most suitable property and select a reliable intermediary.

[0067] "Information processing means" refers to a device or system for analyzing user input and performing data retrieval and evaluation based on specified conditions.

[0068] A "storage device" is a digital or physical medium used to store information and to allow that information to be retrieved as needed.

[0069] "Communication means" refers to technologies or devices for sending and receiving information between a server and a user's mobile device or other network.

[0070] "Display means" refers to a display or other visualization technology used to visually present information to a user.

[0071] "Display screen means" refers to a display and its control system for users to visually confirm information and interact with it.

[0072] "Means of providing advice" refers to technologies or algorithms for generating and presenting personalized recommendations and advice to users.

[0073] A "means for managing action plans" refers to a system that manages users' schedules and tasks and provides reminders and notifications at the necessary times.

[0074] "Means of continuously updating the latest information" refers to technologies or systems that constantly receive external data and provide the most up-to-date information that matches the user's requirements.

[0075] This invention achieves efficient information provision and decision support by constructing a system in which the user, server, and terminal work in cooperation with each other. Specifically, the user inputs their desired conditions through an interface on the terminal, and the server processes them based on that input.

[0076] Users enter detailed criteria such as region, budget, and floor plan into a terminal. This information is sent to the server in real time. The server analyzes the received data using AI models built in Python and libraries such as TENSORFLOW®. Through this analysis, the server continuously extracts and updates the latest property information that matches the user's desired conditions from the real estate database. The server also analyzes the transaction history of intermediaries and user evaluation data to assess the reliability of the intermediaries.

[0077] The results generated on the server are sent to the terminal and presented to the user. The user interface on the terminal displays property information along with information on reliable intermediaries, all integrated together. In addition, personalized advice is provided based on the user's past activity history and choices, such as recommendations for viewings and suggestions for contacting intermediaries. Furthermore, the server manages the user's schedule and notifies the terminal of reminders for relevant important appointments.

[0078] Throughout the entire process, this system efficiently and rationally supports user decision-making and provides optimal information, significantly simplifying the property selection and intermediary selection processes.

[0079] For example, if a user sets conditions such as "within Tokyo's 23 wards, rent under 100,000 yen, 2LDK," the server will immediately list properties that meet these conditions and present them along with reliable intermediary information.

[0080] An example of a prompt might be, "Please tell me how to set up a real estate search system to find a rental property within my budget in a major city. Ideally, I'd like a 3LDK property suitable for a family." By inputting this prompt into the generating AI model, you can obtain a detailed explanation of the support the system will provide.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user enters their preferences, including region, budget, floor plan, and property type, into the terminal. The entered data is formatted by the user interface and prepared for transmission. The terminal converts the data received through the input form into JSON format and prepares it for transmission to the server.

[0084] Step 2:

[0085] The terminal sends the formatted input data to the server. The terminal uses HTTP requests to send the data to the server and confirms that the transfer was successful. The transmission is performed in real time and is designed to respond quickly to user requests.

[0086] Step 3:

[0087] The server analyzes the conditional data received from the terminal. It uses AI algorithms based on Python and TensorFlow to analyze the data. Based on the analysis results, the server filters and selects property data that matches the conditions and determines the guidelines for database searches.

[0088] Step 4:

[0089] The server searches the real estate database for property information that matches the criteria based on the analysis results. The search process uses SQL queries to access the database and extract information quickly and accurately. The server generates a list of matching properties and stores this list in a cache.

[0090] Step 5:

[0091] The server analyzes past transaction history and user reviews to evaluate the intermediary's information. In this step, AI models are used to quantify reliability and rank the intermediaries based on certain criteria.

[0092] Step 6:

[0093] The server integrates property information and reliable intermediary information and sends it to the user's terminal. The integrated data is formatted in JSON format and sent in a format that is easy for the user to understand. Once the transmission is complete, the server confirms that the results have been received by the terminal.

[0094] Step 7:

[0095] The terminal analyzes property and intermediary information received from the server and displays it to the user. The terminal provides the received data in a visually clear and interactive format on the interface. Furthermore, it provides the user with personalized property viewing recommendations and suggestions for contacting intermediaries based on their past selection history.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In existing physical stores, there is a problem in that it is difficult for customers to quickly find the products they want. Furthermore, obtaining detailed information and expert advice about products can be time-consuming and require considerable effort. Additionally, there is a challenge in that customers have limited easy access to trusted experts.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes an information processing device means for receiving condition input from a user and analyzing the conditions; an information processing device means for searching for product information from an information storage device based on the conditions and generating a list of relevant products; and a display means for selecting an expert based on the evaluation and presenting it to the user along with the expert's information. This enables customers to quickly obtain product information that matches their desired conditions and receive advice from reliable experts in real time at a physical store.

[0101] An "information processing device" is a computing device that receives and analyzes input information from users. It is used for information management and calculations.

[0102] An "information storage device" is a data storage device that stores data such as product information and expert information, and allows for searching and retrieval as needed.

[0103] "Communication means" refers to a network interface used to send and receive data to and from a user's terminal. It enables information exchange with remote locations.

[0104] "Display means" refers to the components of devices and software used to visually present information to the user. Screens and display devices fall into this category.

[0105] A "display screen means" is an interface for displaying information in response to user actions. It allows for the integrated visual management of multiple pieces of information.

[0106] "Programming means for portable terminals" refers to application software that runs on a portable device. It is a series of processes programmed to achieve a specific function.

[0107] An "expert" refers to someone who possesses extensive knowledge and experience in a particular product or field, and who can provide reliable advice to customers.

[0108] The system for realizing this invention is constructed to provide product information quickly and efficiently in physical stores. The main components of the system are an information processing device, an information storage device, communication means, display means, display screen means, and a program for a portable terminal.

[0109] First, the user enters the desired product criteria using a portable terminal installed in the store, such as a tablet or smart glasses. This input is sent to an information processing device, where the criteria are analyzed. The information processing device then searches for product information from the information storage device based on the criteria. The information storage device stores data on all products in the store.

[0110] After the information processing device obtains search results, it notifies the user terminal of the results via communication means. The display means provides an effective shopping experience by presenting the user with a real-time list of products and expert information familiar with the relevant products. The display screen means comprehensively manages information in response to user operations, organizing necessary information for easy reference.

[0111] The server uses a program for mobile devices to provide users with personalized advice and manage their planned activities. This allows users to receive appropriate product information along with advice from trusted experts when they visit the store.

[0112] For example, if a user enters criteria such as "blue T-shirt, size M, under 2000 yen," the system will generate product information matching these criteria, along with a list of experts providing detailed information about those products, in real time. Based on this information, the user can find the product in the store and make a purchase smoothly.

[0113] Examples of prompts to input into a generative AI model are as follows:

[0114] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user uses a portable device to enter the specifications of the desired product. This includes category, budget, color, size, etc. This input data is then transmitted by the device to an information processing unit.

[0118] Step 2:

[0119] The server analyzes the user conditions received. In this process, an AI algorithm is used to analyze each condition and identify matching keywords and ranges. Based on the analysis, a generative AI model is executed, and a query is generated in the database.

[0120] Step 3:

[0121] The server uses the generated query to search for relevant product information from the information storage device. This process involves performing a database search and generating a list of products that match the criteria. The search results are temporarily stored on the server.

[0122] Step 4:

[0123] The server selects suitable product information from the search results and transmits it to the terminal using a communication method. Simultaneously, it also verifies information about product experts and selects highly reliable information.

[0124] Step 5:

[0125] The terminal displays the received product list and expert information on its screen. Using a display screen, the product list and expert information are presented to the user in an easy-to-read format. The user can then refer to this information and proceed with their shopping.

[0126] Step 6:

[0127] The server generates personalized advice based on the user's selection history and behavioral patterns, and sends it back to the device to manage their planned actions. The user can then plan their next actions based on the suggested information.

[0128] Examples of prompts to input into a generative AI model are as follows:

[0129] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0130] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0131] The system according to the present invention is built through the interaction of a user, a server, a terminal, and an emotion engine, and is designed to efficiently search for properties that match the user's desired conditions. It provides a better user experience by searching for property information from a database, analyzing agent information, and personalizing the service while considering the user's emotional state.

[0132] First, the user enters their desired property criteria through the terminal's interface. This input data is sent from the terminal to the server. An AI algorithm on the server analyzes the received criteria and searches the real estate database based on them. A list of properties that match the user's criteria is generated as a search result.

[0133] The server simultaneously uses an emotion engine to collect and analyze user emotion data. For example, it identifies the points that users consider important when selecting a property based on property features that users have previously given high ratings to and emotions derived from user facial recognition. This allows the system to optimize the order in which properties are presented in the property list, prioritizing properties that users prefer.

[0134] Furthermore, the server evaluates the reliability of agents based on their transaction data and user reviews. Based on this evaluation and the analysis results from the sentiment engine, it selects the most suitable agent for the user and provides that information to the user. This information is integrated into the terminal's display screen, allowing the user to view and act upon it at a glance.

[0135] Furthermore, the server provides users with personalized advice and suggests action schedules tailored to their emotional state. For example, if a user is emotionally motivated to purchase, it can immediately suggest scheduling a viewing. Reminders and schedule management functions displayed on the device allow users to easily carry out the suggested actions.

[0136] In this way, it is possible to achieve efficient and personalized property searching and agent selection while taking user emotions into consideration.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user uses the input form on their device to enter their desired property criteria (e.g., area, price range, floor plan, etc.) and presses the submit button. This sends the user's criteria data from the device to the server.

[0140] Step 2:

[0141] The server analyzes the received user criteria data using an AI algorithm. As a result of the analysis, the attributes of the property the user desires are identified, and based on this information, a query for property searching is prepared.

[0142] Step 3:

[0143] The server queries the real estate database to find property information that matches the user's criteria. It generates a list of matching properties as a search result and stores it in temporary storage.

[0144] Step 4:

[0145] The server uses an emotion engine to collect user reaction data (e.g., emotional information obtained from facial recognition and selection history) through the device. Based on this emotional information, it infers the user's preferences and purchasing intent.

[0146] Step 5:

[0147] The server analyzes the collected sentiment data and optimizes the order in which the property list is presented based on the results. This prioritizes placing properties that the user is most likely to be interested in at the top of the list.

[0148] Step 6:

[0149] The server analyzes the agent's past transaction data and reviews to assess their reliability. Once a reliable agent is identified, it prepares to present that agent information to the user in combination with property information.

[0150] Step 7:

[0151] The terminal receives optimized property listings and agent information from the server and integrates and displays them on the user's screen. Based on this information, the user can select properties and contact agents.

[0152] Step 8:

[0153] The server generates advice that takes into account the user's emotional data and property selection status, and proposes a personalized action schedule to the user. This suggestion is displayed as a reminder on the device, allowing the user to proceed with the suggested actions on time.

[0154] (Example 2)

[0155] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0156] When searching for information online, information provided without considering the user's subjective and emotional factors can make it difficult for users to find the options they truly desire. Furthermore, a lack of reliable intermediaries can lead users to make inappropriate choices. Addressing these issues is crucial for efficiently providing information and improving the user experience.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes information processing means for receiving condition input from a user and analyzing the conditions; information processing means for searching for information from a data storage device based on the conditions and generating a list of relevant information; and information processing means for analyzing the user's emotional state and optimizing the priority of the information list based on that. This makes it possible to provide personalized information that takes into account the user's emotions and preferences.

[0159] A "user" is the entity that uses this system to search for and receive information.

[0160] "Conditional input" refers to data entry that allows users to specify the details and preferences of the information they are looking for.

[0161] "Information processing means" refers to a function that analyzes input data and generates or extracts necessary information.

[0162] A "data storage device" is a database system that stores large amounts of information and allows it to be searched and used as needed.

[0163] An "information list" is a list of information extracted based on the user's criteria.

[0164] "Information transmission means" refers to a communication method or technology for delivering generated information to a user's terminal.

[0165] "Intermediary information" refers to data about third parties who assist in providing information to users.

[0166] "Display means" refers to equipment or technology used to visually present information to users.

[0167] A "display screen means" is an interface that allows users to manipulate or view information.

[0168] "Personalized instructions" refer to advice and suggestions that are optimized according to the user's characteristics and circumstances.

[0169] An "action plan" is a set of tasks and schedules predetermined to help the user achieve their goals.

[0170] "Emotional state" is a concept that describes a user's current feelings and psychological condition.

[0171] "Optimizing priorities" means rearranging information so that the most important information for the user is presented first.

[0172] This invention is designed based on the interaction between a user, a server, and a terminal. When searching for a property, the user inputs their desired conditions through the terminal's interface. This terminal can be a general-purpose computer such as a PC, smartphone, or tablet.

[0173] The user's desired conditions are sent to the server via a secure protocol. The server is equipped with an information processing system using a generative AI model, which analyzes the received conditions. This model utilizes natural language processing technology to flexibly interpret the user's conditions according to the context. Based on the analysis results, the server searches the database for relevant property information and generates a list of information.

[0174] Simultaneously, the server uses an emotion engine to evaluate the user's emotional state. For example, it analyzes the user's past preference data and recent emotion metrics to customize the order in which properties are presented. This allows for the display of properties that the user finds more appealing to a priority.

[0175] The server further analyzes the intermediary's past transaction data and user reviews to provide reliable intermediary information. Data mining techniques within the server are used to select and notify users of highly-rated intermediaries.

[0176] All information is integrated into the terminal's display screen and provided to the user. Through this interface, users can easily view information relevant to their needs and take necessary actions. For example, if a user enters a prompt such as "I would like efficient suggestions for pet-friendly properties within my budget," the system will return the best suggestions based on those conditions.

[0177] This system delivers a superior user experience by considering user emotions while improving the speed and accuracy of information delivery.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] Users input their desired property criteria through the terminal's interface. These criteria are specific, such as "located in Tokyo, 2LDK, pet-friendly, monthly rent under 200,000 yen." The entered data is sent to the server as structured data by the terminal.

[0181] Step 2:

[0182] The server inputs the conditions received from the terminal into the generative AI model. The generative AI model uses natural language processing to analyze the conditions. Through this analysis, it interprets the conditions broadly and constructs a search query based on that interpretation. As a result of the analysis, a search query is generated.

[0183] Step 3:

[0184] The server queries the database using the generated search query. The database contains a large amount of property information. The server executes the SQL query to find property information that matches the criteria and lists the results. The output is a list of property information.

[0185] Step 4:

[0186] The server simultaneously uses an emotion engine to analyze the user's past preference data and current emotion data. User emotion is obtained using facial recognition technology and past click data. This optimizes the display order of property information for the user. An optimized property list is then output.

[0187] Step 5:

[0188] The server evaluates the agent's past transaction data and user reviews to quantify the intermediary's reliability. This information is analyzed using data mining techniques. Highly reliable agent information is then output.

[0189] Step 6:

[0190] The server sends optimized property listings and agent information to the terminal. The terminal integrates the received data into an interface and displays it in a way that allows the user to intuitively select options. The user can operate the terminal to view detailed property information and agent contact information.

[0191] Step 7:

[0192] The server provides users with personalized advice based on sentiment analysis. For example, it immediately suggests viewing a property that the user has shown strong interest in. This suggestion is displayed as a notification on the device, and the user can manage their schedule using the reminder function.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In traditional real estate searches, property lists are presented based solely on the user's desired criteria, neglecting emotional aspects and consequently making it difficult to maximize user satisfaction. Especially in face-to-face interactions with agents at physical offices, there is a need for a method to instantly present users with the most suitable property and agent information. Furthermore, the reliability of intermediary information is not adequately assessed, necessitating enhanced measures to support user selection.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching property information from an information storage device based on the conditions and generating a list of relevant properties; information processing means for analyzing intermediary information related to property selection and evaluating its reliability; and sentiment analysis means for acquiring the customer's emotional state and optimizing the presentation of options. This makes it possible to present properties and optimal intermediary information that take into account not only the user's desired conditions but also their emotional state.

[0198] "Information processing means" refers to functions for analyzing and processing data based on user input or instructions from the system.

[0199] An "information storage device" refers to a device that stores information in the form of a database or similar, and allows it to be searched or retrieved as needed.

[0200] "Information transmission means" refers to communication methods and networks used to transmit information to a user's device.

[0201] "Intermediary information" refers to information related to the transaction history and evaluation of intermediaries.

[0202] "Display means" refers to displays and interfaces used to visually present information to users.

[0203] "Display screen means" refers to a user interface that allows users to manipulate information and manage it in an integrated manner.

[0204] "Personalized advice" refers to advice that is customized according to the user's individual needs and feelings.

[0205] "Action plan" refers to a schedule that outlines the next actions or plans a user should take.

[0206] "Emotional analysis methods" refer to technologies for measuring and analyzing a user's emotions, such as facial expressions and voice.

[0207] This system is realized by coordinating the user, terminal, server, and sentiment analysis engine. The terminal is provided in the form of, for example, smart glasses or a smartphone, and has an interface to receive input from the user. When the user enters their desired property conditions, that data is transmitted to the server via an information transmission method.

[0208] The server uses information processing tools to analyze the received user conditions and access the information storage device to search for relevant property information. The property information is organized and presented to the user in the most suitable order. In this process, sentiment analysis tools are utilized to acquire and analyze the user's emotional state in real time, enabling the user to make the most meaningful property selection.

[0209] The display system shows property and real estate agent information according to user input, and provides personalized advice. It also manages user schedules, allowing for suggestions of property viewings tailored to the user's availability. Specifically, agent information includes past transaction data and user reviews, and reliable agents are identified through information processing.

[0210] For example, if a user is looking for a house with a large living room, the system can extract their preferences from facial expressions captured by the device's camera and analyze their voice. The server then prioritizes and presents properties that match these preferences. At the same time, the agent's rating and detailed information are also displayed to support the user's interaction.

[0211] An example of a prompt message would be: "Assuming the customer is looking for family-friendly properties, explain how to optimize suggested properties by analyzing facial expressions such as smiles and changes in voice tone."

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] The user enters their desired property criteria using a terminal. The terminal transmits the input data to the server via a data transmission method. This input data includes information such as property conditions and desired area.

[0215] Step 2:

[0216] The server analyzes the received property conditions using information processing equipment. This analysis searches for data matching the conditions in the information storage device and generates a list of relevant properties. It receives the user's desired conditions as input and outputs property information that satisfies those conditions.

[0217] Step 3:

[0218] The server uses a display device to generate a property list, which is then sent to the terminal and presented to the user. The transmitted property list is arranged in order according to the user's preferences and includes detailed information.

[0219] Step 4:

[0220] The server uses emotion analysis tools to acquire the user's emotional state. This emotional data is used to analyze the user's facial expressions and voice tone. The emotional state information is further used to optimize property selection.

[0221] Step 5:

[0222] The server optimizes the order of the property list, taking into account the user's emotional state. Based on the emotional analysis results and property information, it prioritizes displaying properties that the user is likely to be more interested in.

[0223] Step 6:

[0224] The server analyzes intermediary information and evaluates their reliability. Based on user reviews and past transaction data, the information processing system selects highly reliable intermediaries. It takes intermediary data as input and outputs a reliability evaluation.

[0225] Step 7:

[0226] The server displays the selected intermediary information on the terminal. Information on reliable intermediaries related to the property selected by the user is presented, along with transaction history as additional information.

[0227] Step 8:

[0228] Once the user has selected a property and is ready to proceed to the next step, the server suggests a plan of action. For example, it might suggest a schedule for immediately setting up a viewing, supporting the user's actions.

[0229] This processing flow allows users to choose the property that best suits their emotions and desired conditions.

[0230] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0231] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0232] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0236] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0237] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0238] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0239] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0240] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0241] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0242] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0243] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0244] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0245] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0246] The system according to the present invention is built through the interaction of a user, a server, and a terminal. It is designed to enable users to quickly find the most suitable property and select a reliable real estate agent. A specific embodiment is described below.

[0247] First, the user enters their desired conditions through the terminal's user interface. These conditions include a wide range of information such as budget, location, floor plan, and property type. The terminal sends this information to a server where it is analyzed.

[0248] The server uses an AI algorithm to analyze the received conditions. Based on this analysis, the server searches a real estate database and extracts property information that matches the conditions. This creates a list of properties that best suit the user's desired conditions. For example, if a user enters "1LDK apartment in Tokyo, under 100,000 yen per month," the server will collect property information that meets these conditions and prepare it as a list.

[0249] Furthermore, the server also analyzes agent information. It evaluates the agent's reliability based on their past transaction data and reviews, and uses the results to select the most suitable agent for the user. The selected agent information, along with property information, is sent to the terminal and presented to the user.

[0250] The device screen displays integrated property and agent information, making it easy for users to compare and consider options. Personalized advice is also provided to users. For example, based on the user's past choices and activity history, suggestions are made to recommend viewing specific properties or to facilitate contact with agents.

[0251] Ultimately, the server manages the user's activity schedule and promptly notifies the user's device of timely reminders for viewings and signing contracts. Through this implementation, users can efficiently and rationally proceed with property searches and agent selection.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] Users fill in their desired property criteria on a terminal's input form. This includes information such as budget, preferred area, and floor plan. After the user finishes entering the information, they click the submit button, and the data is sent to the server.

[0255] Step 2:

[0256] The terminal sends the conditional data received from the user to the server. The transmitted data is processed within the server and prepared to proceed to the analysis process.

[0257] Step 3:

[0258] The server uses an AI algorithm to analyze the received data. Based on the analysis, points are assigned according to the user's criteria, and a search of the real estate database is initiated using this information.

[0259] Step 4:

[0260] The server executes an SQL query against the real estate database to search for properties that meet the user's criteria. The property information obtained from this search is collected and organized in a list format.

[0261] Step 5:

[0262] Based on the property list generated by the server, the notification system activates and prepares to send the property list to the user's terminal. During this process, arrangements are also made to send push notifications to users of new properties.

[0263] Step 6:

[0264] The server further evaluates the reliability of agents based on their past transaction history and user reviews. Based on this evaluation, it selects highly reliable agents.

[0265] Step 7:

[0266] On the terminal, property information and agent information sent from the server are displayed on the screen. Users can check the information on this screen and register favorites or make inquiries.

[0267] Step 8:

[0268] The server analyzes the user's conditions and behavioral history to generate personalized advice. For example, it might suggest viewing specific properties or prepare reminders for the necessary procedures leading up to a contract.

[0269] Step 9:

[0270] The device receives notifications from the server and displays schedule management and reminders to the user. This allows the user to understand the appropriate timing for their next action.

[0271] (Example 1)

[0272] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In today's real estate market, a challenge exists in that it is difficult for users to quickly find the optimal property and select a reliable intermediary. With traditional methods, information is scattered, making it difficult for users to choose from a vast amount of information that suits their needs. Furthermore, there is a lack of objective indicators to individually assess the reliability of each intermediary, making it difficult to proceed with transactions with peace of mind.

[0274] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0275] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching for target information from a storage device based on the conditions and generating a list of corresponding targets; and means for receiving external information and continuously updating the latest information that matches the user's desired conditions. This enables the user to efficiently and quickly find the most suitable property and select a reliable intermediary.

[0276] "The information processing means" refers to a device or system for analyzing input from a user and performing searches and evaluations of data based on conditions.

[0277] "The storage device" refers to a digital or physical medium for storing information and enabling its retrieval as needed.

[0278] "The communication means" refers to a technology or device for transmitting and receiving information between a server and a user's mobile device or other networks.

[0279] "The display means" refers to a display or other visualization technology for visually presenting information to a user.

[0280] "The display screen means" refers to a display and its control system for a user to visually confirm information and interactively operate.

[0281] "The means for providing advice" refers to a technology or algorithm for generating and presenting individualized recommendations and advice to a user.

[0282] "The means for managing an action plan" refers to a system for managing a user's schedule and tasks and sending reminders and notifications at the necessary times.

[0283] "The means for continuously updating the latest information" refers to a technology or system for constantly receiving external data and providing the latest information that meets the user's conditions.

[0284] In this invention, an efficient information provision and decision support are realized by constructing a system in which a user, a server, and a terminal operate in cooperation with each other. Specifically, the user inputs their desired conditions through an interface on the terminal, and the server performs processing based on this.

[0285] The user inputs detailed conditions such as location, budget, and floor plan into the terminal. This information is sent to the server in real time. The server analyzes the received data using an AI model built in Python and libraries such as TensorFlow. Through this analysis, the server continuously extracts and updates the latest property information that matches the user's desired conditions from the real estate database. Also, the server analyzes the transaction history of the intermediary and the user's evaluation data to evaluate the reliability of the intermediary.

[0286] The results generated by the server are sent to the terminal and presented to the user. On the user interface on the terminal, information on reliable intermediaries is integrated and displayed together with the property information. Also, based on the user's past behavior history and selections, personalized advice such as recommendations for property viewings and suggestions for contacting intermediaries is provided. Furthermore, the server manages the user's schedule and notifies the terminal of reminders for important related appointments.

[0287] Throughout the entire process, this system efficiently and rationally supports the user's decision-making and provides optimal information, significantly simplifying the process of property selection and intermediary selection.

[0288] As a specific example, when the user sets conditions such as "within the 23 wards of Tokyo, rent of 100,000 yen or less, 2LDK", the server immediately lists up the properties that meet these conditions and presents them together with information on reliable intermediaries.

[0289] Examples of prompt sentences include "Please tell me how to set the parameters to find a rental property within my budget in a major city using the real estate search system. This property is ideal for a family with 3LDK." By inputting this prompt into the generative AI model, a detailed explanation of the support content provided by the system can be obtained.

[0290] The flow of the specific process in Example 1 will be described using FIG. 11.

[0291] Step 1:

[0292] The user enters their preferences, including region, budget, floor plan, and property type, into the terminal. The entered data is formatted by the user interface and prepared for transmission. The terminal converts the data received through the input form into JSON format and prepares it for transmission to the server.

[0293] Step 2:

[0294] The terminal sends the formatted input data to the server. The terminal uses HTTP requests to send the data to the server and confirms that the transfer was successful. The transmission is performed in real time and is designed to respond quickly to user requests.

[0295] Step 3:

[0296] The server analyzes the conditional data received from the terminal. It uses AI algorithms based on Python and TensorFlow to analyze the data. Based on the analysis results, the server filters and selects property data that matches the conditions and determines the guidelines for database searches.

[0297] Step 4:

[0298] The server searches the real estate database for property information that matches the criteria based on the analysis results. The search process uses SQL queries to access the database and extract information quickly and accurately. The server generates a list of matching properties and stores this list in a cache.

[0299] Step 5:

[0300] The server analyzes past transaction history and user reviews to evaluate the intermediary's information. In this step, AI models are used to quantify reliability and rank the intermediaries based on certain criteria.

[0301] Step 6:

[0302] The server integrates the property information and the mediator information evaluated for reliability, and transmits it to the user's terminal. The integrated data is formatted in JSON format and sent in a form that can be easily understood by the user. When the transmission is completed, the server confirms that the result has been received by the terminal.

[0303] Step 7:

[0304] The terminal analyzes the property and mediator information received from the server and displays it to the user. The terminal provides the received data in a visually understandable and interactive form on the interface. Furthermore, the terminal makes individualized viewing recommendations based on the user's past selection history and proposes contacting the mediator to the user.

[0305] (Application Example 1)

[0306] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0307] In an existing physical store, there is a problem that it is difficult for customers to quickly find the products they want. Also, in order to obtain detailed information and professional advice regarding products, it may require a lot of time and effort. Furthermore, there is also an issue that the means for customers to easily access reliable experts are limited.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0309] In this invention, the server includes an information processing device means for receiving condition input from a user and analyzing the conditions; an information processing device means for searching for product information from an information storage device based on the conditions and generating a list of relevant products; and a display means for selecting an expert based on the evaluation and presenting it to the user along with the expert's information. This enables customers to quickly obtain product information that matches their desired conditions and receive advice from reliable experts in real time at a physical store.

[0310] An "information processing device" is a computing device that receives and analyzes input information from users. It is used for information management and calculations.

[0311] An "information storage device" is a data storage device that stores data such as product information and expert information, and allows for searching and retrieval as needed.

[0312] "Communication means" refers to a network interface used to send and receive data to and from a user's terminal. It enables information exchange with remote locations.

[0313] "Display means" refers to the components of devices and software used to visually present information to the user. Screens and display devices fall into this category.

[0314] A "display screen means" is an interface for displaying information in response to user actions. It allows for the integrated visual management of multiple pieces of information.

[0315] "Programming means for portable terminals" refers to application software that runs on a portable device. It is a series of processes programmed to achieve a specific function.

[0316] An "expert" refers to someone who possesses extensive knowledge and experience in a particular product or field, and who can provide reliable advice to customers.

[0317] The system for realizing this invention is constructed to provide product information quickly and efficiently in physical stores. The main components of the system are an information processing device, an information storage device, communication means, display means, display screen means, and a program for a portable terminal.

[0318] First, the user enters the desired product criteria using a portable terminal installed in the store, such as a tablet or smart glasses. This input is sent to an information processing device, where the criteria are analyzed. The information processing device then searches for product information from the information storage device based on the criteria. The information storage device stores data on all products in the store.

[0319] After the information processing device obtains search results, it notifies the user terminal of the results via communication means. The display means provides an effective shopping experience by presenting the user with a real-time list of products and expert information familiar with the relevant products. The display screen means comprehensively manages information in response to user operations, organizing necessary information for easy reference.

[0320] The server uses a program for mobile devices to provide users with personalized advice and manage their planned activities. This allows users to receive appropriate product information along with advice from trusted experts when they visit the store.

[0321] For example, if a user enters criteria such as "blue T-shirt, size M, under 2000 yen," the system will generate product information matching these criteria, along with a list of experts providing detailed information about those products, in real time. Based on this information, the user can find the product in the store and make a purchase smoothly.

[0322] Examples of prompts to input into a generative AI model are as follows:

[0323] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] The user uses a portable device to enter the specifications of the desired product. This includes category, budget, color, size, etc. This input data is then transmitted by the device to an information processing unit.

[0327] Step 2:

[0328] The server analyzes the user conditions received. In this process, an AI algorithm is used to analyze each condition and identify matching keywords and ranges. Based on the analysis, a generative AI model is executed, and a query is generated in the database.

[0329] Step 3:

[0330] The server uses the generated query to search for relevant product information from the information storage device. This process involves performing a database search and generating a list of products that match the criteria. The search results are temporarily stored on the server.

[0331] Step 4:

[0332] The server selects suitable product information from the search results and transmits it to the terminal using a communication method. Simultaneously, it also verifies information about product experts and selects highly reliable information.

[0333] Step 5:

[0334] The terminal displays the received product list and expert information on its screen. Using a display screen, the product list and expert information are presented to the user in an easy-to-read format. The user can then refer to this information and proceed with their shopping.

[0335] Step 6:

[0336] The server generates personalized advice based on the user's selection history and behavioral patterns, and sends it back to the device to manage their planned actions. The user can then plan their next actions based on the suggested information.

[0337] Examples of prompts to input into a generative AI model are as follows:

[0338] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0339] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0340] The system according to the present invention is built through the interaction of a user, a server, a terminal, and an emotion engine, and is designed to efficiently search for properties that match the user's desired conditions. It provides a better user experience by searching for property information from a database, analyzing agent information, and personalizing the service while considering the user's emotional state.

[0341] First, the user enters their desired property criteria through the terminal's interface. This input data is sent from the terminal to the server. An AI algorithm on the server analyzes the received criteria and searches the real estate database based on them. A list of properties that match the user's criteria is generated as a search result.

[0342] The server simultaneously uses an emotion engine to collect and analyze user emotion data. For example, it identifies the points that users consider important when selecting a property based on property features that users have previously given high ratings to and emotions derived from user facial recognition. This allows the system to optimize the order in which properties are presented in the property list, prioritizing properties that users prefer.

[0343] Furthermore, the server evaluates the reliability of agents based on their transaction data and user reviews. Based on this evaluation and the analysis results from the sentiment engine, it selects the most suitable agent for the user and provides that information to the user. This information is integrated into the terminal's display screen, allowing the user to view and act upon it at a glance.

[0344] Furthermore, the server provides users with personalized advice and suggests action schedules tailored to their emotional state. For example, if a user is emotionally motivated to purchase, it can immediately suggest scheduling a viewing. Reminders and schedule management functions displayed on the device allow users to easily carry out the suggested actions.

[0345] In this way, it is possible to achieve efficient and personalized property searching and agent selection while taking user emotions into consideration.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The user uses the input form on their device to enter their desired property criteria (e.g., area, price range, floor plan, etc.) and presses the submit button. This sends the user's criteria data from the device to the server.

[0349] Step 2:

[0350] The server analyzes the received user criteria data using an AI algorithm. As a result of the analysis, the attributes of the property the user desires are identified, and based on this information, a query for property searching is prepared.

[0351] Step 3:

[0352] The server queries the real estate database to find property information that matches the user's criteria. It generates a list of matching properties as a search result and stores it in temporary storage.

[0353] Step 4:

[0354] The server uses an emotion engine to collect user reaction data (e.g., emotional information obtained from facial recognition and selection history) through the device. Based on this emotional information, it infers the user's preferences and purchasing intent.

[0355] Step 5:

[0356] The server analyzes the collected sentiment data and optimizes the order in which the property list is presented based on the results. This prioritizes placing properties that the user is most likely to be interested in at the top of the list.

[0357] Step 6:

[0358] The server analyzes the agent's past transaction data and reviews to assess their reliability. Once a reliable agent is identified, it prepares to present that agent information to the user in combination with property information.

[0359] Step 7:

[0360] The terminal receives optimized property listings and agent information from the server and integrates and displays them on the user's screen. Based on this information, the user can select properties and contact agents.

[0361] Step 8:

[0362] The server generates advice that takes into account the user's emotional data and property selection status, and proposes a personalized action schedule to the user. This suggestion is displayed as a reminder on the device, allowing the user to proceed with the suggested actions on time.

[0363] (Example 2)

[0364] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0365] When searching for information online, information provided without considering the user's subjective and emotional factors can make it difficult for users to find the options they truly desire. Furthermore, a lack of reliable intermediaries can lead users to make inappropriate choices. Addressing these issues is crucial for efficiently providing information and improving the user experience.

[0366] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0367] In this invention, the server includes information processing means for receiving condition input from a user and analyzing the conditions; information processing means for searching for information from a data storage device based on the conditions and generating a list of relevant information; and information processing means for analyzing the user's emotional state and optimizing the priority of the information list based on that. This makes it possible to provide personalized information that takes into account the user's emotions and preferences.

[0368] A "user" is the entity that uses this system to search for and receive information.

[0369] "Conditional input" refers to data entry that allows users to specify the details and preferences of the information they are looking for.

[0370] "Information processing means" refers to a function that analyzes input data and generates or extracts necessary information.

[0371] A "data storage device" is a database system that stores large amounts of information and allows it to be searched and used as needed.

[0372] An "information list" is a list of information extracted based on the user's criteria.

[0373] "Information transmission means" refers to a communication method or technology for delivering generated information to a user's terminal.

[0374] "Intermediary information" refers to data about third parties who assist in providing information to users.

[0375] "Display means" refers to equipment or technology used to visually present information to users.

[0376] A "display screen means" is an interface that allows users to manipulate or view information.

[0377] "Personalized instructions" refer to advice and suggestions that are optimized according to the user's characteristics and circumstances.

[0378] An "action plan" is a set of tasks and schedules predetermined to help the user achieve their goals.

[0379] "Emotional state" is a concept that describes a user's current feelings and psychological condition.

[0380] "Optimizing priorities" means rearranging information so that the most important information for the user is presented first.

[0381] This invention is designed based on the interaction between a user, a server, and a terminal. When searching for a property, the user inputs their desired conditions through the terminal's interface. This terminal can be a general-purpose computer such as a PC, smartphone, or tablet.

[0382] The user's desired conditions are sent to the server via a secure protocol. The server is equipped with an information processing system using a generative AI model, which analyzes the received conditions. This model utilizes natural language processing technology to flexibly interpret the user's conditions according to the context. Based on the analysis results, the server searches the database for relevant property information and generates a list of information.

[0383] Simultaneously, the server uses an emotion engine to evaluate the user's emotional state. For example, it analyzes the user's past preference data and recent emotion metrics to customize the order in which properties are presented. This allows for the display of properties that the user finds more appealing to a priority.

[0384] The server further analyzes the intermediary's past transaction data and user reviews to provide reliable intermediary information. Data mining techniques within the server are used to select and notify users of highly-rated intermediaries.

[0385] All information is integrated into the terminal's display screen and provided to the user. Through this interface, users can easily view information relevant to their needs and take necessary actions. For example, if a user enters a prompt such as "I would like efficient suggestions for pet-friendly properties within my budget," the system will return the best suggestions based on those conditions.

[0386] This system delivers a superior user experience by considering user emotions while improving the speed and accuracy of information delivery.

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] Users input their desired property criteria through the terminal's interface. These criteria are specific, such as "located in Tokyo, 2LDK, pet-friendly, monthly rent under 200,000 yen." The entered data is sent to the server as structured data by the terminal.

[0390] Step 2:

[0391] The server inputs the conditions received from the terminal into the generative AI model. The generative AI model uses natural language processing to analyze the conditions. Through this analysis, it interprets the conditions broadly and constructs a search query based on that interpretation. As a result of the analysis, a search query is generated.

[0392] Step 3:

[0393] The server queries the database using the generated search query. The database contains a large amount of property information. The server executes the SQL query to find property information that matches the criteria and lists the results. The output is a list of property information.

[0394] Step 4:

[0395] The server simultaneously uses an emotion engine to analyze the user's past preference data and current emotion data. User emotion is obtained using facial recognition technology and past click data. This optimizes the display order of property information for the user. An optimized property list is then output.

[0396] Step 5:

[0397] The server evaluates the agent's past transaction data and user reviews to quantify the intermediary's reliability. This information is analyzed using data mining techniques. Highly reliable agent information is then output.

[0398] Step 6:

[0399] The server sends optimized property listings and agent information to the terminal. The terminal integrates the received data into an interface and displays it in a way that allows the user to intuitively select options. The user can operate the terminal to view detailed property information and agent contact information.

[0400] Step 7:

[0401] The server provides users with personalized advice based on sentiment analysis. For example, it immediately suggests viewing a property that the user has shown strong interest in. This suggestion is displayed as a notification on the device, and the user can manage their schedule using the reminder function.

[0402] (Application Example 2)

[0403] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0404] In traditional real estate searches, property lists are presented based solely on the user's desired criteria, neglecting emotional aspects and consequently making it difficult to maximize user satisfaction. Especially in face-to-face interactions with agents at physical offices, there is a need for a method to instantly present users with the most suitable property and agent information. Furthermore, the reliability of intermediary information is not adequately assessed, necessitating enhanced measures to support user selection.

[0405] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0406] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching property information from an information storage device based on the conditions and generating a list of relevant properties; information processing means for analyzing intermediary information related to property selection and evaluating its reliability; and sentiment analysis means for acquiring the customer's emotional state and optimizing the presentation of options. This makes it possible to present properties and optimal intermediary information that take into account not only the user's desired conditions but also their emotional state.

[0407] "Information processing means" refers to functions for analyzing and processing data based on user input or instructions from the system.

[0408] An "information storage device" refers to a device that stores information in the form of a database or similar, and allows it to be searched or retrieved as needed.

[0409] "Information transmission means" refers to communication methods and networks used to transmit information to a user's device.

[0410] "Intermediary information" refers to information related to the transaction history and evaluation of intermediaries.

[0411] "Display means" refers to displays and interfaces used to visually present information to users.

[0412] "Display screen means" refers to a user interface that allows users to manipulate information and manage it in an integrated manner.

[0413] "Personalized advice" refers to advice that is customized according to the user's individual needs and feelings.

[0414] "Action plan" refers to a schedule that outlines the next actions or plans a user should take.

[0415] "Emotional analysis methods" refer to technologies for measuring and analyzing a user's emotions, such as facial expressions and voice.

[0416] This system is realized by coordinating the user, terminal, server, and sentiment analysis engine. The terminal is provided in the form of, for example, smart glasses or a smartphone, and has an interface to receive input from the user. When the user enters their desired property conditions, that data is transmitted to the server via an information transmission method.

[0417] The server uses information processing tools to analyze the received user conditions and access the information storage device to search for relevant property information. The property information is organized and presented to the user in the most suitable order. In this process, sentiment analysis tools are utilized to acquire and analyze the user's emotional state in real time, enabling the user to make the most meaningful property selection.

[0418] The display system shows property and real estate agent information according to user input, and provides personalized advice. It also manages user schedules, allowing for suggestions of property viewings tailored to the user's availability. Specifically, agent information includes past transaction data and user reviews, and reliable agents are identified through information processing.

[0419] For example, if a user is looking for a house with a large living room, the system can extract their preferences from facial expressions captured by the device's camera and analyze their voice. The server then prioritizes and presents properties that match these preferences. At the same time, the agent's rating and detailed information are also displayed to support the user's interaction.

[0420] An example of a prompt message would be: "Assuming the customer is looking for family-friendly properties, explain how to optimize suggested properties by analyzing facial expressions such as smiles and changes in voice tone."

[0421] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0422] Step 1:

[0423] The user enters their desired property criteria using a terminal. The terminal transmits the input data to the server via a data transmission method. This input data includes information such as property conditions and desired area.

[0424] Step 2:

[0425] The server analyzes the received property conditions using information processing equipment. This analysis searches for data matching the conditions in the information storage device and generates a list of relevant properties. It receives the user's desired conditions as input and outputs property information that satisfies those conditions.

[0426] Step 3:

[0427] The server uses a display device to generate a property list, which is then sent to the terminal and presented to the user. The transmitted property list is arranged in order according to the user's preferences and includes detailed information.

[0428] Step 4:

[0429] The server uses emotion analysis tools to acquire the user's emotional state. This emotional data is used to analyze the user's facial expressions and voice tone. The emotional state information is further used to optimize property selection.

[0430] Step 5:

[0431] The server optimizes the order of the property list, taking into account the user's emotional state. Based on the emotional analysis results and property information, it prioritizes displaying properties that the user is likely to be more interested in.

[0432] Step 6:

[0433] The server analyzes intermediary information and evaluates their reliability. Based on user reviews and past transaction data, the information processing system selects highly reliable intermediaries. It takes intermediary data as input and outputs a reliability evaluation.

[0434] Step 7:

[0435] The server displays the selected intermediary information on the terminal. Information on reliable intermediaries related to the property selected by the user is presented, along with transaction history as additional information.

[0436] Step 8:

[0437] Once the user has selected a property and is ready to proceed to the next step, the server suggests a plan of action. For example, it might suggest a schedule for immediately setting up a viewing, supporting the user's actions.

[0438] This processing flow allows users to choose the property that best suits their emotions and desired conditions.

[0439] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0440] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0441] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0442] [Third Embodiment]

[0443] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0444] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0445] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0446] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0447] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0448] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0449] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0450] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0451] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0452] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0453] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0454] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0455] The system according to the present invention is built through the interaction of a user, a server, and a terminal. It is designed to enable users to quickly find the most suitable property and select a reliable real estate agent. A specific embodiment is described below.

[0456] First, the user enters their desired conditions through the terminal's user interface. These conditions include a wide range of information such as budget, location, floor plan, and property type. The terminal sends this information to a server where it is analyzed.

[0457] The server uses an AI algorithm to analyze the received conditions. Based on this analysis, the server searches a real estate database and extracts property information that matches the conditions. This creates a list of properties that best suit the user's desired conditions. For example, if a user enters "1LDK apartment in Tokyo, under 100,000 yen per month," the server will collect property information that meets these conditions and prepare it as a list.

[0458] Furthermore, the server also analyzes agent information. It evaluates the agent's reliability based on their past transaction data and reviews, and uses the results to select the most suitable agent for the user. The selected agent information, along with property information, is sent to the terminal and presented to the user.

[0459] The device screen displays integrated property and agent information, making it easy for users to compare and consider options. Personalized advice is also provided to users. For example, based on the user's past choices and activity history, suggestions are made to recommend viewing specific properties or to facilitate contact with agents.

[0460] Ultimately, the server manages the user's activity schedule and promptly notifies the user's device of timely reminders for viewings and signing contracts. Through this implementation, users can efficiently and rationally proceed with property searches and agent selection.

[0461] The following describes the processing flow.

[0462] Step 1:

[0463] Users fill in their desired property criteria on a terminal's input form. This includes information such as budget, preferred area, and floor plan. After the user finishes entering the information, they click the submit button, and the data is sent to the server.

[0464] Step 2:

[0465] The terminal sends the conditional data received from the user to the server. The transmitted data is processed within the server and prepared to proceed to the analysis process.

[0466] Step 3:

[0467] The server uses an AI algorithm to analyze the received data. Based on the analysis, points are assigned according to the user's criteria, and a search of the real estate database is initiated using this information.

[0468] Step 4:

[0469] The server executes an SQL query against the real estate database to search for properties that meet the user's criteria. The property information obtained from this search is collected and organized in a list format.

[0470] Step 5:

[0471] Based on the property list generated by the server, the notification system activates and prepares to send the property list to the user's terminal. During this process, arrangements are also made to send push notifications to users of new properties.

[0472] Step 6:

[0473] The server further evaluates the reliability of agents based on their past transaction history and user reviews. Based on this evaluation, it selects highly reliable agents.

[0474] Step 7:

[0475] On the terminal, property information and agent information sent from the server are displayed on the screen. Users can check the information on this screen and register favorites or make inquiries.

[0476] Step 8:

[0477] The server analyzes the user's conditions and behavioral history to generate personalized advice. For example, it might suggest viewing specific properties or prepare reminders for the necessary procedures leading up to a contract.

[0478] Step 9:

[0479] The device receives notifications from the server and displays schedule management and reminders to the user. This allows the user to understand the appropriate timing for their next action.

[0480] (Example 1)

[0481] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0482] In today's real estate market, a challenge exists in that it is difficult for users to quickly find the optimal property and select a reliable intermediary. With traditional methods, information is scattered, making it difficult for users to choose from a vast amount of information that suits their needs. Furthermore, there is a lack of objective indicators to individually assess the reliability of each intermediary, making it difficult to proceed with transactions with peace of mind.

[0483] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0484] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching for target information from a storage device based on the conditions and generating a list of corresponding targets; and means for receiving external information and continuously updating the latest information that matches the user's desired conditions. This enables the user to efficiently and quickly find the most suitable property and select a reliable intermediary.

[0485] "Information processing means" refers to a device or system for analyzing user input and performing data retrieval and evaluation based on specified conditions.

[0486] A "storage device" is a digital or physical medium used to store information and to allow that information to be retrieved as needed.

[0487] "Communication means" refers to technologies or devices for sending and receiving information between a server and a user's mobile device or other network.

[0488] "Display means" refers to a display or other visualization technology used to visually present information to a user.

[0489] "Display screen means" refers to a display and its control system for users to visually confirm information and interact with it.

[0490] "Means of providing advice" refers to technologies or algorithms for generating and presenting personalized recommendations and advice to users.

[0491] A "means for managing action plans" refers to a system that manages users' schedules and tasks and provides reminders and notifications at the necessary times.

[0492] "Means of continuously updating the latest information" refers to technologies or systems that constantly receive external data and provide the most up-to-date information that matches the user's requirements.

[0493] This invention achieves efficient information provision and decision support by constructing a system in which the user, server, and terminal work in cooperation with each other. Specifically, the user inputs their desired conditions through an interface on the terminal, and the server processes them based on that input.

[0494] Users enter detailed criteria such as region, budget, and floor plan into their terminal. This information is sent to the server in real time. The server analyzes the received data using AI models built in Python and libraries such as TensorFlow. Through this analysis, the server continuously extracts and updates the latest property information that matches the user's desired conditions from the real estate database. The server also analyzes the transaction history of intermediaries and user evaluation data to assess the reliability of the intermediaries.

[0495] The results generated on the server are sent to the terminal and presented to the user. The user interface on the terminal displays property information along with information on reliable intermediaries, all integrated together. In addition, personalized advice is provided based on the user's past activity history and choices, such as recommendations for viewings and suggestions for contacting intermediaries. Furthermore, the server manages the user's schedule and notifies the terminal of reminders for relevant important appointments.

[0496] Throughout the entire process, this system efficiently and rationally supports user decision-making and provides optimal information, significantly simplifying the property selection and intermediary selection processes.

[0497] For example, if a user sets conditions such as "within Tokyo's 23 wards, rent under 100,000 yen, 2LDK," the server will immediately list properties that meet these conditions and present them along with reliable intermediary information.

[0498] An example of a prompt might be, "Please tell me how to set up a real estate search system to find a rental property within my budget in a major city. Ideally, I'd like a 3LDK property suitable for a family." By inputting this prompt into the generating AI model, you can obtain a detailed explanation of the support the system will provide.

[0499] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0500] Step 1:

[0501] The user enters their preferences, including region, budget, floor plan, and property type, into the terminal. The entered data is formatted by the user interface and prepared for transmission. The terminal converts the data received through the input form into JSON format and prepares it for transmission to the server.

[0502] Step 2:

[0503] The terminal sends the formatted input data to the server. The terminal uses HTTP requests to send the data to the server and confirms that the transfer was successful. The transmission is performed in real time and is designed to respond quickly to user requests.

[0504] Step 3:

[0505] The server analyzes the conditional data received from the terminal. It uses AI algorithms based on Python and TensorFlow to analyze the data. Based on the analysis results, the server filters and selects property data that matches the conditions and determines the guidelines for database searches.

[0506] Step 4:

[0507] The server searches the real estate database for property information that matches the criteria based on the analysis results. The search process uses SQL queries to access the database and extract information quickly and accurately. The server generates a list of matching properties and stores this list in a cache.

[0508] Step 5:

[0509] The server analyzes past transaction history and user reviews to evaluate the intermediary's information. In this step, AI models are used to quantify reliability and rank the intermediaries based on certain criteria.

[0510] Step 6:

[0511] The server integrates property information and reliable intermediary information and sends it to the user's terminal. The integrated data is formatted in JSON format and sent in a format that is easy for the user to understand. Once the transmission is complete, the server confirms that the results have been received by the terminal.

[0512] Step 7:

[0513] The terminal analyzes property and intermediary information received from the server and displays it to the user. The terminal provides the received data in a visually clear and interactive format on the interface. Furthermore, it provides the user with personalized property viewing recommendations and suggestions for contacting intermediaries based on their past selection history.

[0514] (Application Example 1)

[0515] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0516] In existing physical stores, there is a problem in that it is difficult for customers to quickly find the products they want. Furthermore, obtaining detailed information and expert advice about products can be time-consuming and require considerable effort. Additionally, there is a challenge in that customers have limited easy access to trusted experts.

[0517] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0518] In this invention, the server includes an information processing device means for receiving condition input from a user and analyzing the conditions; an information processing device means for searching for product information from an information storage device based on the conditions and generating a list of relevant products; and a display means for selecting an expert based on the evaluation and presenting it to the user along with the expert's information. This enables customers to quickly obtain product information that matches their desired conditions and receive advice from reliable experts in real time at a physical store.

[0519] An "information processing device" is a computing device that receives and analyzes input information from users. It is used for information management and calculations.

[0520] An "information storage device" is a data storage device that stores data such as product information and expert information, and allows for searching and retrieval as needed.

[0521] "Communication means" refers to a network interface used to send and receive data to and from a user's terminal. It enables information exchange with remote locations.

[0522] "Display means" refers to the components of devices and software used to visually present information to the user. Screens and display devices fall into this category.

[0523] A "display screen means" is an interface for displaying information in response to user actions. It allows for the integrated visual management of multiple pieces of information.

[0524] "Programming means for portable terminals" refers to application software that runs on a portable device. It is a series of processes programmed to achieve a specific function.

[0525] An "expert" refers to someone who possesses extensive knowledge and experience in a particular product or field, and who can provide reliable advice to customers.

[0526] The system for realizing this invention is constructed to provide product information quickly and efficiently in physical stores. The main components of the system are an information processing device, an information storage device, communication means, display means, display screen means, and a program for a portable terminal.

[0527] First, the user enters the desired product criteria using a portable terminal installed in the store, such as a tablet or smart glasses. This input is sent to an information processing device, where the criteria are analyzed. The information processing device then searches for product information from the information storage device based on the criteria. The information storage device stores data on all products in the store.

[0528] After the information processing device obtains search results, it notifies the user terminal of the results via communication means. The display means provides an effective shopping experience by presenting the user with a real-time list of products and expert information familiar with the relevant products. The display screen means comprehensively manages information in response to user operations, organizing necessary information for easy reference.

[0529] The server uses a program for mobile devices to provide users with personalized advice and manage their planned activities. This allows users to receive appropriate product information along with advice from trusted experts when they visit the store.

[0530] For example, if a user enters criteria such as "blue T-shirt, size M, under 2000 yen," the system will generate product information matching these criteria, along with a list of experts providing detailed information about those products, in real time. Based on this information, the user can find the product in the store and make a purchase smoothly.

[0531] Examples of prompts to input into a generative AI model are as follows:

[0532] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0533] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0534] Step 1:

[0535] The user uses a portable device to enter the specifications of the desired product. This includes category, budget, color, size, etc. This input data is then transmitted by the device to an information processing unit.

[0536] Step 2:

[0537] The server analyzes the user conditions received. In this process, an AI algorithm is used to analyze each condition and identify matching keywords and ranges. Based on the analysis, a generative AI model is executed, and a query is generated in the database.

[0538] Step 3:

[0539] The server uses the generated query to search for relevant product information from the information storage device. This process involves performing a database search and generating a list of products that match the criteria. The search results are temporarily stored on the server.

[0540] Step 4:

[0541] The server selects suitable product information from the search results and transmits it to the terminal using a communication method. Simultaneously, it also verifies information about product experts and selects highly reliable information.

[0542] Step 5:

[0543] The terminal displays the received product list and expert information on its screen. Using a display screen, the product list and expert information are presented to the user in an easy-to-read format. The user can then refer to this information and proceed with their shopping.

[0544] Step 6:

[0545] The server generates personalized advice based on the user's selection history and behavioral patterns, and sends it back to the device to manage their planned actions. The user can then plan their next actions based on the suggested information.

[0546] Examples of prompts to input into a generative AI model are as follows:

[0547] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0548] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0549] The system according to the present invention is built through the interaction of a user, a server, a terminal, and an emotion engine, and is designed to efficiently search for properties that match the user's desired conditions. It provides a better user experience by searching for property information from a database, analyzing agent information, and personalizing the service while considering the user's emotional state.

[0550] First, the user enters their desired property criteria through the terminal's interface. This input data is sent from the terminal to the server. An AI algorithm on the server analyzes the received criteria and searches the real estate database based on them. A list of properties that match the user's criteria is generated as a search result.

[0551] The server simultaneously uses an emotion engine to collect and analyze user emotion data. For example, it identifies the points that users consider important when selecting a property based on property features that users have previously given high ratings to and emotions derived from user facial recognition. This allows the system to optimize the order in which properties are presented in the property list, prioritizing properties that users prefer.

[0552] Furthermore, the server evaluates the reliability of agents based on their transaction data and user reviews. Based on this evaluation and the analysis results from the sentiment engine, it selects the most suitable agent for the user and provides that information to the user. This information is integrated into the terminal's display screen, allowing the user to view and act upon it at a glance.

[0553] Furthermore, the server provides users with personalized advice and suggests action schedules tailored to their emotional state. For example, if a user is emotionally motivated to purchase, it can immediately suggest scheduling a viewing. Reminders and schedule management functions displayed on the device allow users to easily carry out the suggested actions.

[0554] In this way, it is possible to achieve efficient and personalized property searching and agent selection while taking user emotions into consideration.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The user uses the input form on their device to enter their desired property criteria (e.g., area, price range, floor plan, etc.) and presses the submit button. This sends the user's criteria data from the device to the server.

[0558] Step 2:

[0559] The server analyzes the received user criteria data using an AI algorithm. As a result of the analysis, the attributes of the property the user desires are identified, and based on this information, a query for property searching is prepared.

[0560] Step 3:

[0561] The server queries the real estate database to find property information that matches the user's criteria. It generates a list of matching properties as a search result and stores it in temporary storage.

[0562] Step 4:

[0563] The server uses an emotion engine to collect user reaction data (e.g., emotional information obtained from facial recognition and selection history) through the device. Based on this emotional information, it infers the user's preferences and purchasing intent.

[0564] Step 5:

[0565] The server analyzes the collected sentiment data and optimizes the order in which the property list is presented based on the results. This prioritizes placing properties that the user is most likely to be interested in at the top of the list.

[0566] Step 6:

[0567] The server analyzes the agent's past transaction data and reviews to assess their reliability. Once a reliable agent is identified, it prepares to present that agent information to the user in combination with property information.

[0568] Step 7:

[0569] The terminal receives optimized property listings and agent information from the server and integrates and displays them on the user's screen. Based on this information, the user can select properties and contact agents.

[0570] Step 8:

[0571] The server generates advice that takes into account the user's emotional data and property selection status, and proposes a personalized action schedule to the user. This suggestion is displayed as a reminder on the device, allowing the user to proceed with the suggested actions on time.

[0572] (Example 2)

[0573] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0574] When searching for information online, information provided without considering the user's subjective and emotional factors can make it difficult for users to find the options they truly desire. Furthermore, a lack of reliable intermediaries can lead users to make inappropriate choices. Addressing these issues is crucial for efficiently providing information and improving the user experience.

[0575] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0576] In this invention, the server includes information processing means for receiving condition input from a user and analyzing the conditions; information processing means for searching for information from a data storage device based on the conditions and generating a list of relevant information; and information processing means for analyzing the user's emotional state and optimizing the priority of the information list based on that. This makes it possible to provide personalized information that takes into account the user's emotions and preferences.

[0577] A "user" is the entity that uses this system to search for and receive information.

[0578] "Conditional input" refers to data entry that allows users to specify the details and preferences of the information they are looking for.

[0579] "Information processing means" refers to a function that analyzes input data and generates or extracts necessary information.

[0580] A "data storage device" is a database system that stores large amounts of information and allows it to be searched and used as needed.

[0581] An "information list" is a list of information extracted based on the user's criteria.

[0582] "Information transmission means" refers to a communication method or technology for delivering generated information to a user's terminal.

[0583] "Intermediary information" refers to data about third parties who assist in providing information to users.

[0584] "Display means" refers to equipment or technology used to visually present information to users.

[0585] A "display screen means" is an interface that allows users to manipulate or view information.

[0586] "Personalized instructions" refer to advice and suggestions that are optimized according to the user's characteristics and circumstances.

[0587] An "action plan" is a set of tasks and schedules predetermined to help the user achieve their goals.

[0588] "Emotional state" is a concept that describes a user's current feelings and psychological condition.

[0589] "Optimizing priorities" means rearranging information so that the most important information for the user is presented first.

[0590] This invention is designed based on the interaction between a user, a server, and a terminal. When searching for a property, the user inputs their desired conditions through the terminal's interface. This terminal can be a general-purpose computer such as a PC, smartphone, or tablet.

[0591] The user's desired conditions are sent to the server via a secure protocol. The server is equipped with an information processing system using a generative AI model, which analyzes the received conditions. This model utilizes natural language processing technology to flexibly interpret the user's conditions according to the context. Based on the analysis results, the server searches the database for relevant property information and generates a list of information.

[0592] Simultaneously, the server uses an emotion engine to evaluate the user's emotional state. For example, it analyzes the user's past preference data and recent emotion metrics to customize the order in which properties are presented. This allows for the display of properties that the user finds more appealing to a priority.

[0593] The server further analyzes the intermediary's past transaction data and user reviews to provide reliable intermediary information. Data mining techniques within the server are used to select and notify users of highly-rated intermediaries.

[0594] All information is integrated into the terminal's display screen and provided to the user. Through this interface, users can easily view information relevant to their needs and take necessary actions. For example, if a user enters a prompt such as "I would like efficient suggestions for pet-friendly properties within my budget," the system will return the best suggestions based on those conditions.

[0595] This system delivers a superior user experience by considering user emotions while improving the speed and accuracy of information delivery.

[0596] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0597] Step 1:

[0598] Users input their desired property criteria through the terminal's interface. These criteria are specific, such as "located in Tokyo, 2LDK, pet-friendly, monthly rent under 200,000 yen." The entered data is sent to the server as structured data by the terminal.

[0599] Step 2:

[0600] The server inputs the conditions received from the terminal into the generative AI model. The generative AI model uses natural language processing to analyze the conditions. Through this analysis, it interprets the conditions broadly and constructs a search query based on that interpretation. As a result of the analysis, a search query is generated.

[0601] Step 3:

[0602] The server queries the database using the generated search query. The database contains a large amount of property information. The server executes the SQL query to find property information that matches the criteria and lists the results. The output is a list of property information.

[0603] Step 4:

[0604] The server simultaneously uses an emotion engine to analyze the user's past preference data and current emotion data. User emotion is obtained using facial recognition technology and past click data. This optimizes the display order of property information for the user. An optimized property list is then output.

[0605] Step 5:

[0606] The server evaluates the agent's past transaction data and user reviews to quantify the intermediary's reliability. This information is analyzed using data mining techniques. Highly reliable agent information is then output.

[0607] Step 6:

[0608] The server sends optimized property listings and agent information to the terminal. The terminal integrates the received data into an interface and displays it in a way that allows the user to intuitively select options. The user can operate the terminal to view detailed property information and agent contact information.

[0609] Step 7:

[0610] The server provides users with personalized advice based on sentiment analysis. For example, it immediately suggests viewing a property that the user has shown strong interest in. This suggestion is displayed as a notification on the device, and the user can manage their schedule using the reminder function.

[0611] (Application Example 2)

[0612] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0613] In traditional real estate searches, property lists are presented based solely on the user's desired criteria, neglecting emotional aspects and consequently making it difficult to maximize user satisfaction. Especially in face-to-face interactions with agents at physical offices, there is a need for a method to instantly present users with the most suitable property and agent information. Furthermore, the reliability of intermediary information is not adequately assessed, necessitating enhanced measures to support user selection.

[0614] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0615] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching property information from an information storage device based on the conditions and generating a list of relevant properties; information processing means for analyzing intermediary information related to property selection and evaluating its reliability; and sentiment analysis means for acquiring the customer's emotional state and optimizing the presentation of options. This makes it possible to present properties and optimal intermediary information that take into account not only the user's desired conditions but also their emotional state.

[0616] "Information processing means" refers to functions for analyzing and processing data based on user input or instructions from the system.

[0617] An "information storage device" refers to a device that stores information in the form of a database or similar, and allows it to be searched or retrieved as needed.

[0618] "Information transmission means" refers to communication methods and networks used to transmit information to a user's device.

[0619] "Intermediary information" refers to information related to the transaction history and evaluation of intermediaries.

[0620] "Display means" refers to displays and interfaces used to visually present information to users.

[0621] "Display screen means" refers to a user interface that allows users to manipulate information and manage it in an integrated manner.

[0622] "Personalized advice" refers to advice that is customized according to the user's individual needs and feelings.

[0623] "Action plan" refers to a schedule that outlines the next actions or plans a user should take.

[0624] "Emotional analysis methods" refer to technologies for measuring and analyzing a user's emotions, such as facial expressions and voice.

[0625] This system is realized by coordinating the user, terminal, server, and sentiment analysis engine. The terminal is provided in the form of, for example, smart glasses or a smartphone, and has an interface to receive input from the user. When the user enters their desired property conditions, that data is transmitted to the server via an information transmission method.

[0626] The server uses information processing tools to analyze the received user conditions and access the information storage device to search for relevant property information. The property information is organized and presented to the user in the most suitable order. In this process, sentiment analysis tools are utilized to acquire and analyze the user's emotional state in real time, enabling the user to make the most meaningful property selection.

[0627] The display system shows property and real estate agent information according to user input, and provides personalized advice. It also manages user schedules, allowing for suggestions of property viewings tailored to the user's availability. Specifically, agent information includes past transaction data and user reviews, and reliable agents are identified through information processing.

[0628] For example, if a user is looking for a house with a large living room, the system can extract their preferences from facial expressions captured by the device's camera and analyze their voice. The server then prioritizes and presents properties that match these preferences. At the same time, the agent's rating and detailed information are also displayed to support the user's interaction.

[0629] An example of a prompt message would be: "Assuming the customer is looking for family-friendly properties, explain how to optimize suggested properties by analyzing facial expressions such as smiles and changes in voice tone."

[0630] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0631] Step 1:

[0632] The user enters their desired property criteria using a terminal. The terminal transmits the input data to the server via a data transmission method. This input data includes information such as property conditions and desired area.

[0633] Step 2:

[0634] The server analyzes the received property conditions using information processing equipment. This analysis searches for data matching the conditions in the information storage device and generates a list of relevant properties. It receives the user's desired conditions as input and outputs property information that satisfies those conditions.

[0635] Step 3:

[0636] The server uses a display device to generate a property list, which is then sent to the terminal and presented to the user. The transmitted property list is arranged in order according to the user's preferences and includes detailed information.

[0637] Step 4:

[0638] The server uses emotion analysis tools to acquire the user's emotional state. This emotional data is used to analyze the user's facial expressions and voice tone. The emotional state information is further used to optimize property selection.

[0639] Step 5:

[0640] The server optimizes the order of the property list, taking into account the user's emotional state. Based on the emotional analysis results and property information, it prioritizes displaying properties that the user is likely to be more interested in.

[0641] Step 6:

[0642] The server analyzes intermediary information and evaluates their reliability. Based on user reviews and past transaction data, the information processing system selects highly reliable intermediaries. It takes intermediary data as input and outputs a reliability evaluation.

[0643] Step 7:

[0644] The server displays the selected intermediary information on the terminal. Information on reliable intermediaries related to the property selected by the user is presented, along with transaction history as additional information.

[0645] Step 8:

[0646] Once the user has selected a property and is ready to proceed to the next step, the server suggests a plan of action. For example, it might suggest a schedule for immediately setting up a viewing, supporting the user's actions.

[0647] This processing flow allows users to choose the property that best suits their emotions and desired conditions.

[0648] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0649] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0650] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0651] [Fourth Embodiment]

[0652] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0653] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0654] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0655] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0656] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0657] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0658] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0659] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0660] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0661] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0662] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0663] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0664] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0665] The system according to the present invention is built through the interaction of a user, a server, and a terminal. It is designed to enable users to quickly find the most suitable property and select a reliable real estate agent. A specific embodiment is described below.

[0666] First, the user enters their desired conditions through the terminal's user interface. These conditions include a wide range of information such as budget, location, floor plan, and property type. The terminal sends this information to a server where it is analyzed.

[0667] The server uses an AI algorithm to analyze the received conditions. Based on this analysis, the server searches a real estate database and extracts property information that matches the conditions. This creates a list of properties that best suit the user's desired conditions. For example, if a user enters "1LDK apartment in Tokyo, under 100,000 yen per month," the server will collect property information that meets these conditions and prepare it as a list.

[0668] Furthermore, the server also analyzes agent information. It evaluates the agent's reliability based on their past transaction data and reviews, and uses the results to select the most suitable agent for the user. The selected agent information, along with property information, is sent to the terminal and presented to the user.

[0669] The device screen displays integrated property and agent information, making it easy for users to compare and consider options. Personalized advice is also provided to users. For example, based on the user's past choices and activity history, suggestions are made to recommend viewing specific properties or to facilitate contact with agents.

[0670] Ultimately, the server manages the user's activity schedule and promptly notifies the user's device of timely reminders for viewings and signing contracts. Through this implementation, users can efficiently and rationally proceed with property searches and agent selection.

[0671] The following describes the processing flow.

[0672] Step 1:

[0673] Users fill in their desired property criteria on a terminal's input form. This includes information such as budget, preferred area, and floor plan. After the user finishes entering the information, they click the submit button, and the data is sent to the server.

[0674] Step 2:

[0675] The terminal sends the conditional data received from the user to the server. The transmitted data is processed within the server and prepared to proceed to the analysis process.

[0676] Step 3:

[0677] The server uses an AI algorithm to analyze the received data. Based on the analysis, points are assigned according to the user's criteria, and a search of the real estate database is initiated using this information.

[0678] Step 4:

[0679] The server executes an SQL query against the real estate database to search for properties that meet the user's criteria. The property information obtained from this search is collected and organized in a list format.

[0680] Step 5:

[0681] Based on the property list generated by the server, the notification system activates and prepares to send the property list to the user's terminal. During this process, arrangements are also made to send push notifications to users of new properties.

[0682] Step 6:

[0683] The server further evaluates the reliability of agents based on their past transaction history and user reviews. Based on this evaluation, it selects highly reliable agents.

[0684] Step 7:

[0685] On the terminal, property information and agent information sent from the server are displayed on the screen. Users can check the information on this screen and register favorites or make inquiries.

[0686] Step 8:

[0687] The server analyzes the user's conditions and behavioral history to generate personalized advice. For example, it might suggest viewing specific properties or prepare reminders for the necessary procedures leading up to a contract.

[0688] Step 9:

[0689] The device receives notifications from the server and displays schedule management and reminders to the user. This allows the user to understand the appropriate timing for their next action.

[0690] (Example 1)

[0691] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0692] In today's real estate market, a challenge exists in that it is difficult for users to quickly find the optimal property and select a reliable intermediary. With traditional methods, information is scattered, making it difficult for users to choose from a vast amount of information that suits their needs. Furthermore, there is a lack of objective indicators to individually assess the reliability of each intermediary, making it difficult to proceed with transactions with peace of mind.

[0693] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0694] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching for target information from a storage device based on the conditions and generating a list of corresponding targets; and means for receiving external information and continuously updating the latest information that matches the user's desired conditions. This enables the user to efficiently and quickly find the most suitable property and select a reliable intermediary.

[0695] "Information processing means" refers to a device or system for analyzing user input and performing data retrieval and evaluation based on specified conditions.

[0696] A "storage device" is a digital or physical medium used to store information and to allow that information to be retrieved as needed.

[0697] "Communication means" refers to technologies or devices for sending and receiving information between a server and a user's mobile device or other network.

[0698] "Display means" refers to a display or other visualization technology used to visually present information to a user.

[0699] "Display screen means" refers to a display and its control system for users to visually confirm information and interact with it.

[0700] "Means of providing advice" refers to technologies or algorithms for generating and presenting personalized recommendations and advice to users.

[0701] A "means for managing action plans" refers to a system that manages users' schedules and tasks and provides reminders and notifications at the necessary times.

[0702] "Means of continuously updating the latest information" refers to technologies or systems that constantly receive external data and provide the most up-to-date information that matches the user's requirements.

[0703] This invention achieves efficient information provision and decision support by constructing a system in which the user, server, and terminal work in cooperation with each other. Specifically, the user inputs their desired conditions through an interface on the terminal, and the server processes them based on that input.

[0704] Users enter detailed criteria such as region, budget, and floor plan into their terminal. This information is sent to the server in real time. The server analyzes the received data using AI models built in Python and libraries such as TensorFlow. Through this analysis, the server continuously extracts and updates the latest property information that matches the user's desired conditions from the real estate database. The server also analyzes the transaction history of intermediaries and user evaluation data to assess the reliability of the intermediaries.

[0705] The results generated on the server are sent to the terminal and presented to the user. The user interface on the terminal displays property information along with information on reliable intermediaries, all integrated together. In addition, personalized advice is provided based on the user's past activity history and choices, such as recommendations for viewings and suggestions for contacting intermediaries. Furthermore, the server manages the user's schedule and notifies the terminal of reminders for relevant important appointments.

[0706] Throughout the entire process, this system efficiently and rationally supports user decision-making and provides optimal information, significantly simplifying the property selection and intermediary selection processes.

[0707] For example, if a user sets conditions such as "within Tokyo's 23 wards, rent under 100,000 yen, 2LDK," the server will immediately list properties that meet these conditions and present them along with reliable intermediary information.

[0708] An example of a prompt might be, "Please tell me how to set up a real estate search system to find a rental property within my budget in a major city. Ideally, I'd like a 3LDK property suitable for a family." By inputting this prompt into the generating AI model, you can obtain a detailed explanation of the support the system will provide.

[0709] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0710] Step 1:

[0711] The user enters their preferences, including region, budget, floor plan, and property type, into the terminal. The entered data is formatted by the user interface and prepared for transmission. The terminal converts the data received through the input form into JSON format and prepares it for transmission to the server.

[0712] Step 2:

[0713] The terminal sends the formatted input data to the server. The terminal uses HTTP requests to send the data to the server and confirms that the transfer was successful. The transmission is performed in real time and is designed to respond quickly to user requests.

[0714] Step 3:

[0715] The server analyzes the conditional data received from the terminal. It uses AI algorithms based on Python and TensorFlow to analyze the data. Based on the analysis results, the server filters and selects property data that matches the conditions and determines the guidelines for database searches.

[0716] Step 4:

[0717] The server searches the real estate database for property information that matches the criteria based on the analysis results. The search process uses SQL queries to access the database and extract information quickly and accurately. The server generates a list of matching properties and stores this list in a cache.

[0718] Step 5:

[0719] The server analyzes past transaction history and user reviews to evaluate the intermediary's information. In this step, AI models are used to quantify reliability and rank the intermediaries based on certain criteria.

[0720] Step 6:

[0721] The server integrates property information and reliable intermediary information and sends it to the user's terminal. The integrated data is formatted in JSON format and sent in a format that is easy for the user to understand. Once the transmission is complete, the server confirms that the results have been received by the terminal.

[0722] Step 7:

[0723] The terminal analyzes property and intermediary information received from the server and displays it to the user. The terminal provides the received data in a visually clear and interactive format on the interface. Furthermore, it provides the user with personalized property viewing recommendations and suggestions for contacting intermediaries based on their past selection history.

[0724] (Application Example 1)

[0725] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0726] In existing physical stores, there is a problem in that it is difficult for customers to quickly find the products they want. Furthermore, obtaining detailed information and expert advice about products can be time-consuming and require considerable effort. Additionally, there is a challenge in that customers have limited easy access to trusted experts.

[0727] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0728] In this invention, the server includes an information processing device means for receiving condition input from a user and analyzing the conditions; an information processing device means for searching for product information from an information storage device based on the conditions and generating a list of relevant products; and a display means for selecting an expert based on the evaluation and presenting it to the user along with the expert's information. This enables customers to quickly obtain product information that matches their desired conditions and receive advice from reliable experts in real time at a physical store.

[0729] An "information processing device" is a computing device that receives and analyzes input information from users. It is used for information management and calculations.

[0730] An "information storage device" is a data storage device that stores data such as product information and expert information, and allows for searching and retrieval as needed.

[0731] "Communication means" refers to a network interface used to send and receive data to and from a user's terminal. It enables information exchange with remote locations.

[0732] "Display means" refers to the components of devices and software used to visually present information to the user. Screens and display devices fall into this category.

[0733] A "display screen means" is an interface for displaying information in response to user actions. It allows for the integrated visual management of multiple pieces of information.

[0734] "Programming means for portable terminals" refers to application software that runs on a portable device. It is a series of processes programmed to achieve a specific function.

[0735] An "expert" refers to someone who possesses extensive knowledge and experience in a particular product or field, and who can provide reliable advice to customers.

[0736] The system for realizing this invention is constructed to provide product information quickly and efficiently in physical stores. The main components of the system are an information processing device, an information storage device, communication means, display means, display screen means, and a program for a portable terminal.

[0737] First, the user enters the desired product criteria using a portable terminal installed in the store, such as a tablet or smart glasses. This input is sent to an information processing device, where the criteria are analyzed. The information processing device then searches for product information from the information storage device based on the criteria. The information storage device stores data on all products in the store.

[0738] After the information processing device obtains search results, it notifies the user terminal of the results via communication means. The display means provides an effective shopping experience by presenting the user with a real-time list of products and expert information familiar with the relevant products. The display screen means comprehensively manages information in response to user operations, organizing necessary information for easy reference.

[0739] The server uses a program for mobile devices to provide users with personalized advice and manage their planned activities. This allows users to receive appropriate product information along with advice from trusted experts when they visit the store.

[0740] For example, if a user enters criteria such as "blue T-shirt, size M, under 2000 yen," the system will generate product information matching these criteria, along with a list of experts providing detailed information about those products, in real time. Based on this information, the user can find the product in the store and make a purchase smoothly.

[0741] Examples of prompts to input into a generative AI model are as follows:

[0742] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0743] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0744] Step 1:

[0745] The user uses a portable device to enter the specifications of the desired product. This includes category, budget, color, size, etc. This input data is then transmitted by the device to an information processing unit.

[0746] Step 2:

[0747] The server analyzes the user conditions received. In this process, an AI algorithm is used to analyze each condition and identify matching keywords and ranges. Based on the analysis, a generative AI model is executed, and a query is generated in the database.

[0748] Step 3:

[0749] The server uses the generated query to search for relevant product information from the information storage device. This process involves performing a database search and generating a list of products that match the criteria. The search results are temporarily stored on the server.

[0750] Step 4:

[0751] The server selects suitable product information from the search results and transmits it to the terminal using a communication method. Simultaneously, it also verifies information about product experts and selects highly reliable information.

[0752] Step 5:

[0753] The terminal displays the received product list and expert information on its screen. Using a display screen, the product list and expert information are presented to the user in an easy-to-read format. The user can then refer to this information and proceed with their shopping.

[0754] Step 6:

[0755] The server generates personalized advice based on the user's selection history and behavioral patterns, and sends it back to the device to manage their planned actions. The user can then plan their next actions based on the suggested information.

[0756] Examples of prompts to input into a generative AI model are as follows:

[0757] "Please write an AI model program that finds the product information best suited to the user's desired criteria. These criteria include product category, budget, color, size, etc."

[0758] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0759] The system according to the present invention is built through the interaction of a user, a server, a terminal, and an emotion engine, and is designed to efficiently search for properties that match the user's desired conditions. It provides a better user experience by searching for property information from a database, analyzing agent information, and personalizing the service while considering the user's emotional state.

[0760] First, the user enters their desired property criteria through the terminal's interface. This input data is sent from the terminal to the server. An AI algorithm on the server analyzes the received criteria and searches the real estate database based on them. A list of properties that match the user's criteria is generated as a search result.

[0761] The server simultaneously uses an emotion engine to collect and analyze user emotion data. For example, it identifies the points that users consider important when selecting a property based on property features that users have previously given high ratings to and emotions derived from user facial recognition. This allows the system to optimize the order in which properties are presented in the property list, prioritizing properties that users prefer.

[0762] Furthermore, the server evaluates the reliability of agents based on their transaction data and user reviews. Based on this evaluation and the analysis results from the sentiment engine, it selects the most suitable agent for the user and provides that information to the user. This information is integrated into the terminal's display screen, allowing the user to view and act upon it at a glance.

[0763] Furthermore, the server provides users with personalized advice and suggests action schedules tailored to their emotional state. For example, if a user is emotionally motivated to purchase, it can immediately suggest scheduling a viewing. Reminders and schedule management functions displayed on the device allow users to easily carry out the suggested actions.

[0764] In this way, it is possible to achieve efficient and personalized property searching and agent selection while taking user emotions into consideration.

[0765] The following describes the processing flow.

[0766] Step 1:

[0767] The user uses the input form on their device to enter their desired property criteria (e.g., area, price range, floor plan, etc.) and presses the submit button. This sends the user's criteria data from the device to the server.

[0768] Step 2:

[0769] The server analyzes the received user criteria data using an AI algorithm. As a result of the analysis, the attributes of the property the user desires are identified, and based on this information, a query for property searching is prepared.

[0770] Step 3:

[0771] The server queries the real estate database to find property information that matches the user's criteria. It generates a list of matching properties as a search result and stores it in temporary storage.

[0772] Step 4:

[0773] The server uses an emotion engine to collect user reaction data (e.g., emotional information obtained from facial recognition and selection history) through the device. Based on this emotional information, it infers the user's preferences and purchasing intent.

[0774] Step 5:

[0775] The server analyzes the collected sentiment data and optimizes the order in which the property list is presented based on the results. This prioritizes placing properties that the user is most likely to be interested in at the top of the list.

[0776] Step 6:

[0777] The server analyzes the agent's past transaction data and reviews to assess their reliability. Once a reliable agent is identified, it prepares to present that agent information to the user in combination with property information.

[0778] Step 7:

[0779] The terminal receives optimized property listings and agent information from the server and integrates and displays them on the user's screen. Based on this information, the user can select properties and contact agents.

[0780] Step 8:

[0781] The server generates advice that takes into account the user's emotional data and property selection status, and proposes a personalized action schedule to the user. This suggestion is displayed as a reminder on the device, allowing the user to proceed with the suggested actions on time.

[0782] (Example 2)

[0783] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0784] When searching for information online, information provided without considering the user's subjective and emotional factors can make it difficult for users to find the options they truly desire. Furthermore, a lack of reliable intermediaries can lead users to make inappropriate choices. Addressing these issues is crucial for efficiently providing information and improving the user experience.

[0785] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0786] In this invention, the server includes information processing means for receiving condition input from a user and analyzing the conditions; information processing means for searching for information from a data storage device based on the conditions and generating a list of relevant information; and information processing means for analyzing the user's emotional state and optimizing the priority of the information list based on that. This makes it possible to provide personalized information that takes into account the user's emotions and preferences.

[0787] A "user" is the entity that uses this system to search for and receive information.

[0788] "Conditional input" refers to data entry that allows users to specify the details and preferences of the information they are looking for.

[0789] "Information processing means" refers to a function that analyzes input data and generates or extracts necessary information.

[0790] A "data storage device" is a database system that stores large amounts of information and allows it to be searched and used as needed.

[0791] An "information list" is a list of information extracted based on the user's criteria.

[0792] "Information transmission means" refers to a communication method or technology for delivering generated information to a user's terminal.

[0793] "Intermediary information" refers to data about third parties who assist in providing information to users.

[0794] "Display means" refers to equipment or technology used to visually present information to users.

[0795] A "display screen means" is an interface that allows users to manipulate or view information.

[0796] "Personalized instructions" refer to advice and suggestions that are optimized according to the user's characteristics and circumstances.

[0797] An "action plan" is a set of tasks and schedules predetermined to help the user achieve their goals.

[0798] "Emotional state" is a concept that describes a user's current feelings and psychological condition.

[0799] "Optimizing priorities" means rearranging information so that the most important information for the user is presented first.

[0800] This invention is designed based on the interaction between a user, a server, and a terminal. When searching for a property, the user inputs their desired conditions through the terminal's interface. This terminal can be a general-purpose computer such as a PC, smartphone, or tablet.

[0801] The user's desired conditions are sent to the server via a secure protocol. The server is equipped with an information processing system using a generative AI model, which analyzes the received conditions. This model utilizes natural language processing technology to flexibly interpret the user's conditions according to the context. Based on the analysis results, the server searches the database for relevant property information and generates a list of information.

[0802] Simultaneously, the server uses an emotion engine to evaluate the user's emotional state. For example, it analyzes the user's past preference data and recent emotion metrics to customize the order in which properties are presented. This allows for the display of properties that the user finds more appealing to a priority.

[0803] The server further analyzes the intermediary's past transaction data and user reviews to provide reliable intermediary information. Data mining techniques within the server are used to select and notify users of highly-rated intermediaries.

[0804] All information is integrated into the terminal's display screen and provided to the user. Through this interface, users can easily view information relevant to their needs and take necessary actions. For example, if a user enters a prompt such as "I would like efficient suggestions for pet-friendly properties within my budget," the system will return the best suggestions based on those conditions.

[0805] This system delivers a superior user experience by considering user emotions while improving the speed and accuracy of information delivery.

[0806] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0807] Step 1:

[0808] Users input their desired property criteria through the terminal's interface. These criteria are specific, such as "located in Tokyo, 2LDK, pet-friendly, monthly rent under 200,000 yen." The entered data is sent to the server as structured data by the terminal.

[0809] Step 2:

[0810] The server inputs the conditions received from the terminal into the generative AI model. The generative AI model uses natural language processing to analyze the conditions. Through this analysis, it interprets the conditions broadly and constructs a search query based on that interpretation. As a result of the analysis, a search query is generated.

[0811] Step 3:

[0812] The server queries the database using the generated search query. The database contains a large amount of property information. The server executes the SQL query to find property information that matches the criteria and lists the results. The output is a list of property information.

[0813] Step 4:

[0814] The server simultaneously uses an emotion engine to analyze the user's past preference data and current emotion data. User emotion is obtained using facial recognition technology and past click data. This optimizes the display order of property information for the user. An optimized property list is then output.

[0815] Step 5:

[0816] The server evaluates the agent's past transaction data and user reviews to quantify the intermediary's reliability. This information is analyzed using data mining techniques. Highly reliable agent information is then output.

[0817] Step 6:

[0818] The server sends optimized property listings and agent information to the terminal. The terminal integrates the received data into an interface and displays it in a way that allows the user to intuitively select options. The user can operate the terminal to view detailed property information and agent contact information.

[0819] Step 7:

[0820] The server provides users with personalized advice based on sentiment analysis. For example, it immediately suggests viewing a property that the user has shown strong interest in. This suggestion is displayed as a notification on the device, and the user can manage their schedule using the reminder function.

[0821] (Application Example 2)

[0822] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0823] In traditional real estate searches, property lists are presented based solely on the user's desired criteria, neglecting emotional aspects and consequently making it difficult to maximize user satisfaction. Especially in face-to-face interactions with agents at physical offices, there is a need for a method to instantly present users with the most suitable property and agent information. Furthermore, the reliability of intermediary information is not adequately assessed, necessitating enhanced measures to support user selection.

[0824] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0825] In this invention, the server includes information processing means for receiving condition input from the user and analyzing the conditions; information processing means for searching property information from an information storage device based on the conditions and generating a list of relevant properties; information processing means for analyzing intermediary information related to property selection and evaluating its reliability; and sentiment analysis means for acquiring the customer's emotional state and optimizing the presentation of options. This makes it possible to present properties and optimal intermediary information that take into account not only the user's desired conditions but also their emotional state.

[0826] "Information processing means" refers to functions for analyzing and processing data based on user input or instructions from the system.

[0827] An "information storage device" refers to a device that stores information in the form of a database or similar, and allows it to be searched or retrieved as needed.

[0828] "Information transmission means" refers to communication methods and networks used to transmit information to a user's device.

[0829] "Intermediary information" refers to information related to the transaction history and evaluation of intermediaries.

[0830] "Display means" refers to displays and interfaces used to visually present information to users.

[0831] "Display screen means" refers to a user interface that allows users to manipulate information and manage it in an integrated manner.

[0832] "Personalized advice" refers to advice that is customized according to the user's individual needs and feelings.

[0833] "Action plan" refers to a schedule that outlines the next actions or plans a user should take.

[0834] "Emotional analysis methods" refer to technologies for measuring and analyzing a user's emotions, such as facial expressions and voice.

[0835] This system is realized by coordinating the user, terminal, server, and sentiment analysis engine. The terminal is provided in the form of, for example, smart glasses or a smartphone, and has an interface to receive input from the user. When the user enters their desired property conditions, that data is transmitted to the server via an information transmission method.

[0836] The server uses information processing tools to analyze the received user conditions and access the information storage device to search for relevant property information. The property information is organized and presented to the user in the most suitable order. In this process, sentiment analysis tools are utilized to acquire and analyze the user's emotional state in real time, enabling the user to make the most meaningful property selection.

[0837] The display system shows property and real estate agent information according to user input, and provides personalized advice. It also manages user schedules, allowing for suggestions of property viewings tailored to the user's availability. Specifically, agent information includes past transaction data and user reviews, and reliable agents are identified through information processing.

[0838] For example, if a user is looking for a house with a large living room, the system can extract their preferences from facial expressions captured by the device's camera and analyze their voice. The server then prioritizes and presents properties that match these preferences. At the same time, the agent's rating and detailed information are also displayed to support the user's interaction.

[0839] An example of a prompt message would be: "Assuming the customer is looking for family-friendly properties, explain how to optimize suggested properties by analyzing facial expressions such as smiles and changes in voice tone."

[0840] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0841] Step 1:

[0842] The user enters their desired property criteria using a terminal. The terminal transmits the input data to the server via a data transmission method. This input data includes information such as property conditions and desired area.

[0843] Step 2:

[0844] The server analyzes the received property conditions using information processing equipment. This analysis searches for data matching the conditions in the information storage device and generates a list of relevant properties. It receives the user's desired conditions as input and outputs property information that satisfies those conditions.

[0845] Step 3:

[0846] The server uses a display device to generate a property list, which is then sent to the terminal and presented to the user. The transmitted property list is arranged in order according to the user's preferences and includes detailed information.

[0847] Step 4:

[0848] The server uses emotion analysis tools to acquire the user's emotional state. This emotional data is used to analyze the user's facial expressions and voice tone. The emotional state information is further used to optimize property selection.

[0849] Step 5:

[0850] The server optimizes the order of the property list, taking into account the user's emotional state. Based on the emotional analysis results and property information, it prioritizes displaying properties that the user is likely to be more interested in.

[0851] Step 6:

[0852] The server analyzes intermediary information and evaluates their reliability. Based on user reviews and past transaction data, the information processing system selects highly reliable intermediaries. It takes intermediary data as input and outputs a reliability evaluation.

[0853] Step 7:

[0854] The server displays the selected intermediary information on the terminal. Information on reliable intermediaries related to the property selected by the user is presented, along with transaction history as additional information.

[0855] Step 8:

[0856] Once the user has selected a property and is ready to proceed to the next step, the server suggests a plan of action. For example, it might suggest a schedule for immediately setting up a viewing, supporting the user's actions.

[0857] This processing flow allows users to choose the property that best suits their emotions and desired conditions.

[0858] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0859] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0860] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0861] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0862] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0863] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0864] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0865] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0866] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0867] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0868] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0869] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0870] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0871] 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.

[0872] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0873] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0874] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0875] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0876] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0877] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0878] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0879] The following is further disclosed regarding the embodiments described above.

[0880] (Claim 1)

[0881] A computing device means that receives condition input from a user and analyzes those conditions,

[0882] A computing device means that searches for property information from a database based on the aforementioned conditions and generates a list of corresponding properties,

[0883] A communication means for notifying the user's terminal of the aforementioned property list,

[0884] A computing device means for analyzing agent information related to property selection and evaluating its reliability,

[0885] Based on the aforementioned evaluation, an agent is selected and a display means is provided to present the relevant agent information to the user,

[0886] A display screen means for comprehensively managing property information and agent information in response to user operations,

[0887] A computing device means that provides personalized advice to the user and manages their action schedule,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, which generates and notifies users of a list of new properties in real time based on their desired conditions.

[0891] (Claim 3)

[0892] The system according to claim 1, which analyzes the agent's past transaction data and user reviews to evaluate reliability.

[0893] "Example 1"

[0894] (Claim 1)

[0895] An information processing means that receives condition input from a user and analyzes those conditions,

[0896] Information processing means that searches for target information from a storage device based on the aforementioned conditions and generates a list of corresponding targets,

[0897] A communication means for notifying the user's mobile device of the aforementioned target list,

[0898] An information processing means for analyzing intermediary information related to target selection and evaluating its reliability,

[0899] A display means that selects an intermediary based on the aforementioned evaluation and presents the relevant intermediary information to the user,

[0900] A display screen means for comprehensively managing target information and intermediary information in response to user operations,

[0901] An information processing means that provides personalized advice to users and manages action plans,

[0902] A means of receiving external information and continuously updating it with the latest information that matches the user's desired conditions,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, which generates the latest target list based on the user's desired conditions and immediately notifies the user.

[0906] (Claim 3)

[0907] The system according to claim 1, which analyzes the past transaction data and user ratings of an intermediary to evaluate reliability.

[0908] "Application Example 1"

[0909] (Claim 1)

[0910] An information processing device means that receives condition input from a user and analyzes those conditions,

[0911] Information processing means for searching for product information from an information storage device based on the aforementioned conditions and generating a list of corresponding products,

[0912] A communication means for notifying the user's terminal of the aforementioned product list,

[0913] An information processing device that analyzes expert information regarding product selection and evaluates its reliability,

[0914] A means of displaying information that selects an expert based on the aforementioned evaluation and presents it to the user along with the information of the relevant expert,

[0915] A display screen means for integrating and managing product information and expert information in response to user operations,

[0916] Information processing device means that provides personalized advice to users and manages their action schedules,

[0917] A program for a portable terminal that enables the integrated provision of product information and expert support in real time within a physical store, based on the user's desired conditions,

[0918] A system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, which instantly generates and notifies the user of a product list within a physical store based on their desired conditions.

[0921] (Claim 3)

[0922] The system according to claim 1, which analyzes the past transaction data of experts and customer reviews to evaluate reliability.

[0923] "Example 2 of combining an emotion engine"

[0924] (Claim 1)

[0925] An information processing means that receives condition input from a user and analyzes those conditions,

[0926] Information processing means that retrieves information from a data storage device based on the aforementioned conditions and generates a list of relevant information,

[0927] Information transmission means for notifying the user's terminal of the aforementioned list of information,

[0928] An information processing means for analyzing intermediary information related to information selection and evaluating its reliability,

[0929] A means for selecting an intermediary based on the aforementioned evaluation and presenting it to the user along with the relevant intermediary information,

[0930] A display screen means for integrating and managing information in response to user operations and intermediary information,

[0931] An information processing means that provides personalized instructions to users and manages action plans,

[0932] An information processing means that analyzes the user's emotional state and optimizes the priority of the information list based on that analysis,

[0933] A system that includes this.

[0934] (Claim 2)

[0935] The system according to claim 1, which generates and notifies users of a list of new information in real time based on their desired conditions.

[0936] (Claim 3)

[0937] The system according to claim 1, which analyzes the past transaction data and user reviews of intermediaries to evaluate their reliability and select the most suitable intermediary.

[0938] "Application example 2 when combining with an emotional engine"

[0939] (Claim 1)

[0940] An information processing means that receives condition input from a user and analyzes those conditions,

[0941] Information processing means that retrieves property information from an information storage device based on the aforementioned conditions and generates a list of corresponding properties,

[0942] Information transmission means for notifying the user's terminal of the aforementioned property list,

[0943] An information processing means for analyzing intermediary information related to property selection and evaluating its reliability,

[0944] A means for selecting an intermediary based on the aforementioned evaluation and presenting it to the user along with the relevant intermediary information,

[0945] A display screen means for integrally managing property information and intermediary information in response to user operations,

[0946] An information processing means that provides personalized advice to users and manages their action plans,

[0947] A means of sentiment analysis for acquiring the customer's emotional state and optimizing the presentation of choices,

[0948] A system that includes this.

[0949] (Claim 2)

[0950] The system according to claim 1, which generates and notifies users of a list of new properties in real time based on their desired conditions.

[0951] (Claim 3)

[0952] The system according to claim 1, which analyzes the past transaction information and user reviews of an intermediary to evaluate their reliability. [Explanation of Symbols]

[0953] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A computing device means that receives condition input from a user and analyzes those conditions, A computing device means that searches for property information from a database based on the aforementioned conditions and generates a list of corresponding properties, A communication means for notifying the user's terminal of the aforementioned property list, A computing device means for analyzing agent information related to property selection and evaluating its reliability, Based on the aforementioned evaluation, an agent is selected and a display means is provided to present the relevant agent information to the user, A display screen means for comprehensively managing property information and agent information in response to user operations, A computing device means that provides personalized advice to the user and manages their action schedule, A system that includes this.

2. The system according to claim 1, which generates and notifies users of a list of new properties in real time based on their desired conditions.

3. The system according to claim 1, which analyzes the agent's past transaction data and user reviews to evaluate reliability.

Images