system

Abstract

We provide the system. [Solution] A means for users to input their desired conditions, A means for collecting data from multiple sources based on the aforementioned desired conditions, A means for analyzing the aforementioned data and evaluating the property, A means for presenting the aforementioned evaluation results to the user, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 <9: When looking for a rental property, there is a problem that it is difficult to understand the reasonableness of the rent and the appropriateness of the contract terms. Property information is scattered on the Internet, and it is a heavy burden for users to compare and analyze by themselves, and troubles may occur due to improper contracts or insufficient information. In such a situation, a mechanism is required to assist users in reasonably selecting rental properties. 【Means for Solving the Problems】 【0005】 This invention proposes a system that provides a means for users to input their desired conditions and a means for collecting property data from multiple sources based on those conditions. Furthermore, by using a means to analyze the collected data and evaluate properties, it becomes possible to present the evaluation results to the user. This allows users to select rental properties without hassle and protects them from unfair contracts. In addition, by providing risk assessment, the system further supports the user's decision-making. 【0006】 A "user" is an individual or group that uses the system to search for rental property information and make decisions. 【0007】 "Desired conditions" refer to the requirements that users have when selecting a residence, such as area, rent, floor plan, and age of the building. 【0008】 "Information sources" refer to media that provide property information, such as real estate databases and websites that are publicly available on the internet. 【0009】 "Data" refers to a collection of information about rental properties gathered from various sources. 【0010】 "Analysis" is the process of evaluating the characteristics of a property based on collected data and making a quantitative judgment based on those characteristics. 【0011】 "Property evaluation" is the act of conducting a multifaceted analysis of a property and quantifying or ranking its value and the appropriateness of its contract terms. 【0012】 "Risk assessment" is a process for predicting potential problems and troubles hidden within properties and contracts, and for alerting users to these issues. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]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 an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Embodiments for Carrying Out the Invention】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of 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. 【0017】 In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs, various parameters, and the like. 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. 【0019】 In the following embodiments, a communication I / F (Interface) with a reference numeral is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0020】 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." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 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. 【0024】 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). 【0025】 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. 【0026】 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. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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. 【0028】 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. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 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. 【0031】 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. 【0032】 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. 【0033】 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". 【0034】 The present invention relates to a system that assists in searching for and evaluating rental properties, and this system mainly consists of three components: a user, a terminal, and a server. 【0035】 The user first uses a terminal to input their desired property criteria. This includes specific conditions such as the desired area, rent range, floor plan, and age of the building. The terminal receives the user's input and sends it to the server as data. 【0036】 The server collects relevant property information from multiple sources on the internet based on the data it receives. This process is designed to obtain the latest information using automated data collection methods such as scraping and API access. For example, when searching for properties in Tokyo with a rent of 100,000 yen or less, the server gathers matching data from multiple real estate websites and integrates it into a single database. 【0037】 After collection, the server analyzes the property data. Using a generated AI model, properties are evaluated and scored based on factors such as rent appropriateness, property amenities, and age of the building. These analysis results are then sent back to the terminal. 【0038】 The terminal displays the evaluation results received from the server to the user. This presentation is visually easy to understand, allowing the user to easily comprehend and consider the information presented. For example, information about property A might be displayed in the format of "Recommendation level: High" and "Contract risk: Medium." 【0039】 Based on the information received, users can compare properties and make appropriate selections. Furthermore, if the user requests additional information, the terminal can query the server again to supplement with detailed information and risk assessments. In this way, the present invention supports the process of users selecting rental properties in a rational and efficient manner. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The user launches a property search application using their device and enters their desired rental conditions. These conditions include location, rent range, floor plan, and building age. The device waits for user input and prepares to send the information to the server once input is complete. 【0043】 Step 2: 【0044】 The terminal sends the entered desired conditions to the server. Based on the conditions received, the server prepares to access relevant internet sources. These sources include databases and websites that provide real estate information. 【0045】 Step 3: 【0046】 The server collects property information matching the desired criteria from multiple sources through scraping or API access. This process also includes data cleaning as needed to maintain data integrity and accuracy. 【0047】 Step 4: 【0048】 The server passes the collected property data to an automated analysis system, which uses a generated AI model to evaluate each property. Evaluation criteria include market reasonableness of rent, property amenities, and age of the building, and each item is scored. 【0049】 Step 5: 【0050】 The server organizes the analysis results and converts them into a user-friendly format. This may include visual hints about the property's recommendation level and contract risks. The converted evaluation results are then sent to the terminal. 【0051】 Step 6: 【0052】 The terminal displays the evaluation results received from the server to the user. The user reviews each evaluation criterion for the presented property and examines the details as needed. The information is presented in a visually organized format and designed to support the user's decision-making. 【0053】 Step 7: 【0054】 Users compare properties based on the evaluation results and make the choice they deem best. If users require more detailed information, they can request additional information from the server via their device. 【0055】 Step 8: 【0056】 The server receives requests for additional information from the user and performs further data analysis. If there is a detailed risk assessment or supplementary information, it is also sent back to the terminal. This process can be repeated until the user is satisfied. 【0057】 (Example 1) 【0058】 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." 【0059】 Traditional rental property search systems lacked the detailed property evaluations and risk information users needed, making efficient property selection difficult. Furthermore, obtaining up-to-date information in real time was challenging, even with data collection from multiple sources. Additionally, there was a lack of flexible, interactive features to select suitable properties based on user preferences. 【0060】 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. 【0061】 In this invention, the server includes a device for receiving user requests, a device for acquiring information from an external data source, a device for integrating the information and performing an evaluation, a device for using a generative artificial intelligence model for the evaluation, a device for visualizing and displaying the evaluation results to the user, and a program for providing the results of the property risk evaluation. This enables the user to make efficient and appropriate property selections based on detailed property evaluations and risk information. 【0062】 A "user" is an individual or corporation who wishes to search for or evaluate properties, and is the entity that enters their desired conditions. 【0063】 "Desired conditions" refer to the requirements and criteria that users look for in a rental property, and specifically include area, rent, floor plan, and age of the building. 【0064】 "Device" refers to an electronic system or instrument, and in this context, it refers to a component that has the function of receiving, processing, and outputting data. 【0065】 "Information sources" refer to external databases and websites that provide data on rental properties, and include various platforms that provide real estate information. 【0066】 "Evaluation" is the process of analyzing the value and characteristics of a property based on collected information, and then scoring or ranking it. 【0067】 A "generative artificial intelligence model" is an algorithmic structure that learns patterns from large amounts of data and uses them for evaluation and prediction. 【0068】 "Visualization" is a method of presenting data and evaluation results visually in the form of graphs, charts, and other diagrams, making them easy for users to understand. 【0069】 A "program" is a set of instructions that automatically perform evaluations or information processing on specific items, and is executed by a computer device. 【0070】 "Risk assessment" is the process of analyzing potential risks associated with a property and notifying the user. 【0071】 "Interactive format" refers to a method in which users interact with the system in a two-way manner, and it plays an important role in searching for and retrieving information. 【0072】 This invention is a system for assisting in the search and evaluation of rental properties, and mainly consists of three elements: a user, a terminal, and a server. The user first uses the terminal to input their desired conditions. These conditions include the desired area, rent range, floor plan, and age of the building. 【0073】 The terminal organizes the data entered by the user and sends it to the server. This transmission utilizes data formats such as JSON and XML for efficient data exchange. 【0074】 The server collects information from multiple data sources on the internet based on the user's desired conditions. This information collection utilizes scraping techniques and API access, enabling the acquisition of the latest property information in real time. After collection, the server integrates this data, removing redundant data and standardizing the format. 【0075】 Once data integration is complete, the server uses a generated AI model to evaluate properties. This process involves scoring each property based on criteria such as rent appropriateness, amenities, and age of the building. The results are then processed into a visually easy-to-understand format and sent to the terminal. 【0076】 The terminal displays the evaluation results received from the server to the user. This display is done through an interactive UI, supporting the user in easily comparing and considering properties. 【0077】 For example, if a user searches for a property in Tokyo with a rent of 80,000 yen or less, 2LDK layout, and built within the last 10 years, the terminal sends these conditions to the server. The server collects relevant data from various real estate information websites and uses a generated AI model to evaluate the results, presenting them to the user in the form of "Recommendation Level: High" and "Contract Risk: Medium." An example of a prompt message to be entered into this system is as follows: "Please collect and evaluate information on properties in Tokyo with a rent of 100,000 yen or less, 1LDK layout, and built within the last 5 years." In this way, users can efficiently find rental properties that closely match their preferences through this system. 【0078】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0079】 Step 1: 【0080】 Users use a terminal to input their desired conditions for rental properties. The data entered includes specific requirements such as area, rent range, floor plan, and building age. This input forms the basic dataset that is sent to the server. 【0081】 Step 2: 【0082】 The terminal receives input from the user, converts it into JSON or XML format, and packages the data. This packaged data is then sent to the server efficiently and quickly. 【0083】 Step 3: 【0084】 The server analyzes data received from the terminal and collects property information that matches the user's desired criteria. The server accesses multiple information sources through scraping and APIs to perform large-scale data collection. Desired criteria data is provided as input, and a list of highly relevant property data is obtained as output. 【0085】 Step 4: 【0086】 The server integrates the collected property data. It organizes the database by removing duplicate data and converting it to a consistent format. This operation generates a unified dataset. 【0087】 Step 5: 【0088】 The server uses a generative AI model to evaluate properties based on integrated data. Here, scoring is performed considering factors such as rent appropriateness, amenities, and age of the building. The input is an integrated and organized dataset, and the output is an evaluation result with a score for each property. 【0089】 Step 6: 【0090】 The server sends the scored evaluation results to the terminal. The evaluation results are visualized in a way that is easy for the user to understand, and are presented as graphs and tables. 【0091】 Step 7: 【0092】 The terminal receives evaluation results from the server and presents them visually to the user. Using an interactive UI, the user can compare evaluations and select the best property. 【0093】 Step 8: 【0094】 If a user requires more detailed information, they can request additional information from the server via their device. The server then collects and analyzes the requested information again and sends it back to the device. This iterative process allows the user to gain a deeper understanding of the property. 【0095】 (Application Example 1) 【0096】 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." 【0097】 The modern housing selection process presents a problem: users must spend considerable time and effort searching for properties that meet their desired criteria. Furthermore, information is generally provided in text format, making sophisticated analysis and evaluation difficult. Additionally, there are limited means for users to efficiently obtain information using voice. 【0098】 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. 【0099】 In this invention, the server includes means for receiving desired conditions from the user, means for collecting data from multiple information sources based on the desired conditions, and means for analyzing the data and evaluating properties using an evaluation algorithm. This enables the user to intuitively and efficiently select properties through voice and visual information presentation. 【0100】 A "user" is a consumer who uses a system to search for and rate property information. 【0101】 "Desired conditions" refer to the factors that users prioritize when selecting a property, and specifically include elements such as location, rent, floor plan, and age of the building. 【0102】 "Information sources" refer to various digital platforms from which property information can be obtained, including websites and databases on the internet. 【0103】 "Data" refers to all property information collected from the source, including address, rent, equipment specifications, and images. 【0104】 "Analysis" is a data processing process that uses collected data to evaluate properties that meet the conditions requested by the user. 【0105】 An "evaluation algorithm" is a computational method for quantitatively evaluating the quality and value of a property, using a generative AI model to score the reasonableness of the rent and the property's amenities. 【0106】 "Voice recognition" is a technology that interprets voice commands spoken by a user as digital data. 【0107】 "Speech synthesis" is a technology that converts text data into speech data and provides it to the user as audio information. 【0108】 "Presenting audio and visually" means providing evaluation results in a format that is easy for users to understand through both audio and visual means. 【0109】 To implement this invention, a user terminal and a server are key components. The user uses the terminal to input information about the desired property, such as location, rent, and floor plan. The terminal is responsible for transmitting this information to the server. 【0110】 Meanwhile, the server collects property data in real time from multiple sources. This collection utilizes API access using the Python Requests library and scraping techniques using BeautifulSoup to quickly obtain the necessary property information. The collected data is analyzed by a generative AI model for the evaluation algorithm, and properties are scored. This AI model uses OpenAI's GPT technology. 【0111】 The evaluation results generated by the server are provided to the user via the terminal in both audio and visual formats. Google® Speech-to-Text API is used for speech recognition, and existing text-to-speech technologies are used for speech synthesis. This makes it easier for users to intuitively understand the evaluation results. 【0112】 For example, if a user verbally requests, "I'd like a 2LDK apartment in Tokyo where I can live with my pet, with a rent of 150,000 yen or less," the server will select properties that meet the criteria and provide voice guidance such as, "In this area, we recommend a pet-friendly property with a rent of 140,000 yen," while also displaying the property's score and detailed information on the screen. An example of a prompt message would be, "Evaluate the property information based on the conditions specified by the user and suggest a suitable property." 【0113】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0114】 Step 1: 【0115】 The user inputs their desired property conditions by voice using a terminal. The terminal converts the voice data into text data using voice recognition software and sends it to the server as the received desired conditions. In this process, the input is the user's voice data, and the output is the desired conditions in text format. 【0116】 Step 2: 【0117】 The server collects property data from multiple sources on the internet based on the received request criteria. It uses API access via the Python Requests library and scraping techniques with BeautifulSoup. The input is property criteria in text format, and the output is a set of collected property data. 【0118】 Step 3: 【0119】 The server analyzes the collected property data. Using a generative AI model, it applies a property evaluation algorithm and scores each property. The input is a property dataset, and the output is a list of scores for each property. This identifies the property that best matches the user's desired conditions. 【0120】 Step 4: 【0121】 The server sends the scoring results to the terminal. The terminal presents this information to the user through a visual display and audio output using speech synthesis technology. The input is the scoring results, and the output is the visual and audio presentation to the user. 【0122】 Step 5: 【0123】 Users can review properties based on the provided information and request additional information as needed. The terminal resends this request to the server, which then performs further data collection and analysis. The input is the user's request for additional information, and the output is the updated property details. 【0124】 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. 【0125】 This invention relates to a system that integrates an emotion engine that reflects the user's emotions into the rental property search and evaluation process. This system consists of four main components: the user, the terminal, the server, and the emotion engine. 【0126】 The user first launches the property search application using their terminal and enters their desired property criteria. These criteria include specific requirements such as location, rent range, floor plan, and age of the building. The terminal receives the user's input and prepares to send that information to the server. 【0127】 The server collects property information from multiple sources on the internet based on the desired conditions received from the terminal. This process involves obtaining accurate and up-to-date information through scraping and API access. Before passing the collected data to the sentiment engine, the server inputs it into an automated analysis system, where a generative AI model is used to evaluate the properties. This evaluation considers factors such as market reasonableness of rent, property amenities, and age of the building. 【0128】 The emotion engine acquires and analyzes emotional data from user interactions, input, voice, and facial expressions. The server integrates this emotional data with property evaluation results and adjusts the information presented according to the user's emotional state. This allows the system to provide information tailored to the user's preferences and stress level at the optimal time. 【0129】 The terminal displays sentiment-based evaluation results received from the server to the user. The information is visually organized and presented in a user-friendly format, making decision-making easier. For example, the terminal could display "Property A: Recommendation Level: High" and "Sentiment-Based Recommendation: Provides a sense of security," allowing the user to confidently select a property. 【0130】 Users can compare properties based on the information provided and make the most appropriate choice. Furthermore, if the user requests more detailed information, the device will query the server again to provide the necessary additional information. This process allows users to thoroughly consider properties until they are satisfied. The introduction of an emotion engine improves the recommendation accuracy and usability of traditional property search systems, providing a more personalized experience for individual users. 【0131】 The following describes the processing flow. 【0132】 Step 1: 【0133】 The user accesses the terminal and opens the property search application. They enter their desired property criteria, such as area, rent range, floor plan, and year of construction. The terminal temporarily stores this input data and prepares to send it. 【0134】 Step 2: 【0135】 The terminal sends the entered desired conditions to the server. The server then identifies the search conditions and receives the information needed to begin the data collection process. 【0136】 Step 3: 【0137】 The server accesses multiple real estate information sources based on the received preferences. It uses APIs and web scraping techniques to collect relevant property information. The server stores the collected data in a temporary database. 【0138】 Step 4: 【0139】 The server passes the stored property data to a generating AI model for analysis. This analysis evaluates factors such as the reasonableness of the rent, the property's facilities, and its age, and assigns a score to each property. 【0140】 Step 5: 【0141】 The device simultaneously activates an emotion engine to recognize the user's emotions. It analyzes the user's input and reactions during operation to generate emotion data. For example, it measures the speed of input and the time taken to make selections to infer the user's interests and anxieties. 【0142】 Step 6: 【0143】 The emotional data obtained by the emotion engine is sent to the server. Based on this, the server adjusts the property evaluation results based on the user's emotional state. This makes it possible to suggest properties that take the user's emotions into consideration. 【0144】 Step 7: 【0145】 The server returns the adjusted evaluation results to the terminal. The terminal displays the evaluation results to the user in a visually organized format. The information is structured to aid user understanding and support decision-making. 【0146】 Step 8: 【0147】 Users compare properties based on the information presented and make their selection. By referring to the displayed sentiment-based recommendations and risk assessments, they can make a more informed choice. 【0148】 Step 9: 【0149】 If a user desires further details, they can request additional information through their device. The server analyzes the detailed data based on this request, taking into account the user's sentiment data, and provides additional information. This iterative process allows users to consider properties until they are satisfied. 【0150】 (Example 2) 【0151】 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 will be referred to as the "terminal." 【0152】 Traditional property search systems have the problem of presenting uniform information without considering the user's emotional state, making it difficult to alleviate the stress and anxiety they cause. Furthermore, common information formats often lack sufficient personalization to accommodate individual preferences and emotions. 【0153】 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. 【0154】 In this invention, the server includes a device for inputting search criteria from the user, a device for acquiring information from multiple information sources based on the search criteria, a device for analyzing the information and evaluating the target, a device for introducing the evaluation results into a generating AI model and integrating it with the user's emotional data, and a device for presenting the integrated information to the user. This makes it possible to provide information that corresponds to the user's emotional state. 【0155】 A "device for users to input search criteria" is a device that provides an interface for users to specify their desired conditions to the system and for those conditions to be treated as data. 【0156】 A "device that acquires information from multiple sources" is a device that collects necessary data from various sources, such as the internet and databases. 【0157】 A "device for evaluating an object" is a device that has the function of evaluating an object according to certain criteria based on acquired information and outputting the evaluation results. 【0158】 A "device for integrating user sentiment data into a generative AI model" is a device that inputs evaluation results into a generative model and adjusts and integrates those results while taking user sentiment data into consideration. 【0159】 A "device that presents integrated information to the user" is a device that displays processed evaluation and adjustment results in a format that is easy for the user to understand. 【0160】 This invention is a system that enables users to obtain property information based on their desired conditions during the real estate search process, and further provides information according to the user's emotional state. A specific embodiment of this system is shown below. 【0161】 The user launches a property search application using their device. Here, the user enters search criteria such as location, rent, floor plan, and year of construction. The device receives this information and sends it to the server via the network. 【0162】 The server collects property information from multiple sources on the internet based on search criteria sent from the terminal. Web scraping techniques and public APIs are used as collection methods. This allows the server to obtain the latest and most accurate information and aggregate it into a database. 【0163】 Next, the server inputs the aggregated information into a generating AI model. This model evaluates the property, assessing it from multiple perspectives, including the appropriateness of the rent, the quality of the facilities, and the age of the building. 【0164】 Furthermore, the server uses an emotion engine to analyze emotional data obtained from the user. This data is collected from user input, voice, facial expressions, and other sources. The server integrates and adjusts this emotional data with the property evaluation results to generate information that is optimal for the user's emotional state. 【0165】 The terminal receives evaluation results sent from the server and displays the information to the user in a visually organized format. This allows the user to make more rational decisions. For example, the terminal might display information such as "Property A: Recommendation Level: High, Emotional Recommendation: Provides a sense of security." 【0166】 For example, if a user specifies search criteria such as "Tokyo, 2LDK, under 100,000 yen, built within the last 10 years," the system will present a list of properties matching these criteria, along with sentiment ratings. This allows the user to smoothly make the best choice based on this information. 【0167】 This system breaks away from the uniformity of information in conventional property searches and enables the provision of customized information that resonates with the user's emotions. 【0168】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0169】 Step 1: 【0170】 The user launches a property search application on their device and enters their search criteria. This information includes location, rent, floor plan, and year of construction. This data is converted into a digital format within the device, preparing it for further processing. The output of this process is formatted search criteria data. 【0171】 Step 2: 【0172】 The terminal sends search criteria data obtained from the user to the server via the network. This process includes preparing the data for transmission, encoding it, and converting it into network packets. This allows the server to analyze the data. The output of this step is data formatted for the server to receive. 【0173】 Step 3: 【0174】 The server collects property information from multiple databases on the internet based on the search criteria received from the terminal. This collection utilizes web scraping and API access to retrieve the latest information in real time. The input is the search criteria, and the output is a collection of relevant property information. 【0175】 Step 4: 【0176】 The server analyzes the collected property information. Using a generative AI model, it evaluates each property from perspectives such as market value, facilities, and age. This evaluation allows for the quantification of the property's attractiveness and value. The input is the collected property information, and the output is a dataset of evaluation results. 【0177】 Step 5: 【0178】 The emotion engine analyzes user emotional data. It analyzes the user's emotional state from voice, facial expressions, and input data obtained from the device, and determines how information should be presented. The input is raw data about the user's emotions, and the output is analyzed emotion evaluation data. 【0179】 Step 6: 【0180】 The server integrates property evaluation results with analyzed sentiment evaluation data. It adjusts the property recommendation level according to the user's emotional state, generating customized information. This integration enables the provision of information that aligns with the user's emotions. The output is the integrated evaluation information. 【0181】 Step 7: 【0182】 The terminal receives customized evaluation information sent from the server and displays it to the user. The display is in an easy-to-understand format to assist the user in making decisions. The input is integrated evaluation information from the server, and the output is visual information presented to the user. 【0183】 Step 8: 【0184】 The user compares and selects properties based on the information presented. If necessary, they request further details and make additional inquiries to the server via their terminal. This allows the user to obtain sufficient information to make an informed decision. The input is the displayed property information, and the output is the user's selection result. 【0185】 (Application Example 2) 【0186】 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". 【0187】 Traditional property search systems often present information without considering the user's emotional state, resulting in stressful information being presented or information being displayed at inappropriate times. Furthermore, the lack of personalized recommendations tailored to individual users resulted in poor usability. 【0188】 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. 【0189】 In this invention, the server includes means for analyzing the user's emotions, means for adjusting the presentation of information based on the results of the emotion analysis, and means for providing additional information to the user in an interactive format. This enables the provision of information at the optimal timing according to the user's emotions and improves usability through high personalization. 【0190】 A "user" is an entity that uses the system to input desired conditions and participates in the search and evaluation of properties. 【0191】 "Desired conditions" refer to the specific requirements that users set when searching for a property, such as location, rent, floor plan, and age of the building. 【0192】 "Device" refers to a general term for equipment and programs used within a system as a means of inputting, collecting, analyzing, and presenting information. 【0193】 "Information sources" refer to multiple data providers on the internet that are accessed to collect property information. 【0194】 "Information" refers to detailed data about a property that is analyzed based on collected data. 【0195】 "Evaluation" is the process of determining the value and suitability of a property based on the information gathered about it. 【0196】 "Presentation" refers to the act of providing the user with the results of the system's analysis and evaluation, either visually or audibly. 【0197】 "Emotions" represent the user's mental state and are data obtained from the user's facial expressions, voice, and input interactions. 【0198】 "Analysis" is the process of analyzing collected information and emotional data to generate meaningful evaluation results. 【0199】 "Adjustment" is the process of optimizing the content and timing of information presented based on the results of the user's sentiment analysis. 【0200】 "Dialogue format" refers to a method of interactive information exchange between the user and the system. 【0201】 This invention provides a specific embodiment of a system for searching and evaluating property information based on user emotions. The system mainly consists of a user terminal, a server, an emotion analysis device, and an information presentation device. 【0202】 The user launches a property search application using their device and enters their desired property criteria. The device has the function of sending the user's desired criteria to the server. 【0203】 The server collects property data from multiple sources based on the received conditions. This information is obtained through internet databases and APIs. The server analyzes this information and generates property evaluations using an AI model. 【0204】 The emotion analysis device acquires emotional data such as the user's facial expressions and voice, and analyzes their emotional state using a cloud-based emotion analysis API (for example, Azure® Emotion API). The analysis results are sent to a server, where the emotional data is integrated into the property evaluation results. 【0205】 This integrated information is displayed on the user's terminal via an information display device. The terminal then presents the user with property information best suited to their emotional evaluation. For example, if the user indicates a desire for a sense of security, the system can provide information in the format of "Property A: Recommendation Level: High, Provides a sense of security." 【0206】 Through this process, users can make more informed decisions when selecting a property. Furthermore, the interactive features provided by the system allow users to easily obtain additional information and conduct more in-depth comparisons. 【0207】 Examples of prompt statements for generative AI models are as follows: 【0208】 "Please display a list of recommended products for users when they are having fun." 【0209】 "Please tell us about products that help users relax when they are feeling stressed." 【0210】 In this way, by utilizing sentiment analysis to provide information tailored to the user's preferences and emotions, highly personalized property selection support can be achieved. 【0211】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0212】 Step 1: 【0213】 The user operates the terminal to launch the property search application and enters the desired property criteria (area, rent, floor plan, year built, etc.). The entered criteria are formatted into a structured data format within the terminal and prepared for transmission to the server. 【0214】 Step 2: 【0215】 The server uses the desired conditions received from the terminal to collect property data from multiple sources on the internet. Specifically, it obtains information that matches the conditions through a property information database and external APIs. In doing so, it utilizes scraping techniques and API access to collect the latest and most accurate data, which is then stored in an internal database. 【0216】 Step 3: 【0217】 The server uses a generative AI model to evaluate properties based on collected property data. The AI ​​model calculates a score for each property using a dataset that includes factors such as market price reasonableness, property amenities, and age. This evaluation result is then passed on to the next process. 【0218】 Step 4: 【0219】 The emotion analysis device collects user facial expression data and voice input and sends it to a server. Specifically, it acquires data from the device's camera and microphone, and this data is processed by an emotion analysis API (e.g., Azure Emotion API) to generate data indicating emotions. 【0220】 Step 5: 【0221】 The server adjusts property evaluation results based on sentiment analysis. If the user's emotional state is positive, it makes specific adjustments, such as setting a higher recommendation level. By applying emotion-based filtering and ranking, it creates information optimized for each individual user. 【0222】 Step 6: 【0223】 The integrated evaluation information sent from the server is presented to the terminal. Specifically, the terminal displays property information in a visually easy-to-understand format. Property details and recommendation levels are displayed at a time and in a format that is easy for the user to accept, helping them make a selection. 【0224】 Step 7: 【0225】 Users can compare properties based on the information displayed on their device and select the most suitable one. If they require further details, they can query the server again to obtain additional information. This allows users to thoroughly consider properties until they are satisfied. 【0226】 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. 【0227】 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. 【0228】 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. 【0229】 [Second Embodiment] 【0230】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0231】 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. 【0232】 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). 【0233】 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. 【0234】 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. 【0235】 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). 【0236】 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. 【0237】 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. 【0238】 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. 【0239】 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. 【0240】 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. 【0241】 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". 【0242】 The present invention relates to a system that assists in searching for and evaluating rental properties, and this system mainly consists of three components: a user, a terminal, and a server. 【0243】 The user first uses a terminal to input their desired property criteria. This includes specific conditions such as the desired area, rent range, floor plan, and age of the building. The terminal receives the user's input and sends it to the server as data. 【0244】 The server collects relevant property information from multiple sources on the internet based on the data it receives. This process is designed to obtain the latest information using automated data collection methods such as scraping and API access. For example, when searching for properties in Tokyo with a rent of 100,000 yen or less, the server gathers matching data from multiple real estate websites and integrates it into a single database. 【0245】 After collection, the server analyzes the property data. Using a generated AI model, properties are evaluated and scored based on factors such as rent appropriateness, property amenities, and age of the building. These analysis results are then sent back to the terminal. 【0246】 The terminal displays the evaluation results received from the server to the user. This presentation is visually easy to understand, allowing the user to easily comprehend and consider the information presented. For example, information about property A might be displayed in the format of "Recommendation level: High" and "Contract risk: Medium." 【0247】 Based on the information received, users can compare properties and make appropriate selections. Furthermore, if the user requests additional information, the terminal can query the server again to supplement with detailed information and risk assessments. In this way, the present invention supports the process of users selecting rental properties in a rational and efficient manner. 【0248】 The following describes the processing flow. 【0249】 Step 1: 【0250】 The user launches a property search application using their device and enters their desired rental conditions. These conditions include location, rent range, floor plan, and building age. The device waits for user input and prepares to send the information to the server once input is complete. 【0251】 Step 2: 【0252】 The terminal sends the entered desired conditions to the server. Based on the conditions received, the server prepares to access relevant internet sources. These sources include databases and websites that provide real estate information. 【0253】 Step 3: 【0254】 The server collects property information matching the desired criteria from multiple sources through scraping or API access. This process also includes data cleaning as needed to maintain data integrity and accuracy. 【0255】 Step 4: 【0256】 The server passes the collected property data to an automated analysis system, which uses a generated AI model to evaluate each property. Evaluation criteria include market reasonableness of rent, property amenities, and age of the building, and each item is scored. 【0257】 Step 5: 【0258】 The server organizes the analysis results and converts them into a user-friendly format. This may include visual hints about the property's recommendation level and contract risks. The converted evaluation results are then sent to the terminal. 【0259】 Step 6: 【0260】 The terminal displays the evaluation results received from the server to the user. The user reviews each evaluation criterion for the presented property and examines the details as needed. The information is presented in a visually organized format and designed to support the user's decision-making. 【0261】 Step 7: 【0262】 Users compare properties based on the evaluation results and make the choice they deem best. If users require more detailed information, they can request additional information from the server via their device. 【0263】 Step 8: 【0264】 The server receives requests for additional information from the user and performs further data analysis. If there is a detailed risk assessment or supplementary information, it is also sent back to the terminal. This process can be repeated until the user is satisfied. 【0265】 (Example 1) 【0266】 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." 【0267】 Traditional rental property search systems lacked the detailed property evaluations and risk information users needed, making efficient property selection difficult. Furthermore, obtaining up-to-date information in real time was challenging, even with data collection from multiple sources. Additionally, there was a lack of flexible, interactive features to select suitable properties based on user preferences. 【0268】 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. 【0269】 In this invention, the server includes a device for receiving user requests, a device for acquiring information from an external data source, a device for integrating the information and performing an evaluation, a device for using a generative artificial intelligence model for the evaluation, a device for visualizing and displaying the evaluation results to the user, and a program for providing the results of the property risk evaluation. This enables the user to make efficient and appropriate property selections based on detailed property evaluations and risk information. 【0270】 A "user" is an individual or corporation who wishes to search for or evaluate properties, and is the entity that enters their desired conditions. 【0271】 "Desired conditions" refer to the requirements and criteria that users look for in a rental property, and specifically include area, rent, floor plan, and age of the building. 【0272】 "Device" refers to an electronic system or instrument, and in this context, it refers to a component that has the function of receiving, processing, and outputting data. 【0273】 "Information sources" refer to external databases and websites that provide data on rental properties, and include various platforms that provide real estate information. 【0274】 "Evaluation" is the process of analyzing the value and characteristics of a property based on collected information, and then scoring or ranking it. 【0275】 A "generative artificial intelligence model" is an algorithmic structure that learns patterns from large amounts of data and uses them for evaluation and prediction. 【0276】 "Visualization" is a method of presenting data and evaluation results visually in the form of graphs, charts, and other diagrams, making them easy for users to understand. 【0277】 A "program" is a set of instructions that automatically perform evaluations or information processing on specific items, and is executed by a computer device. 【0278】 "Risk assessment" is the process of analyzing potential risks associated with a property and notifying the user. 【0279】 "Interactive format" refers to a method in which users interact with the system in a two-way manner, and it plays an important role in searching for and retrieving information. 【0280】 This invention is a system for assisting in the search and evaluation of rental properties, mainly composed of three elements: a user, a terminal, and a server. The user first uses the terminal to input desired conditions. These conditions include the desired area, rental range, floor plan, years since construction, etc. 【0281】 The terminal organizes the data input by the user and sends the data to the server. This transmission utilizes data formats such as JSON format or XML format for the purpose of efficient data exchange. 【0282】 The server collects information from multiple data sources on the Internet based on the user's desired conditions. For this information collection, scraping technology and API access are utilized to enable the acquisition of the latest property information in real time. After collection, the server integrates these data and performs operations such as deleting redundant data and unifying the format. 【0283】 Once the data integration is completed, the server performs property evaluation by utilizing a generative AI model. In this process, scoring is implemented for each property based on criteria such as the validity of the rent, facilities, years since construction, etc. The results are processed into a visually easy-to-understand form and sent to the terminal. 【0284】 The terminal presents the evaluation results received from the server to the user. The presentation is carried out through an interactive UI to support the user in easily comparing and considering properties. 【0285】 As a specific example, when a user searches for "a property in Tokyo with a rent of less than 80,000 yen, 2LDK, and built within 10 years", the terminal sends these conditions to the server. The server collects the corresponding data from various real estate information websites and presents the results evaluated using the generated AI model to the user in the form of "Recommendation level: High" and "Contract risk: Medium". Examples of prompt sentences input into this system are as follows. "Please collect and evaluate information on properties within Tokyo with a rent of less than 100,000 yen, 1LDK, and built within 5 years." In this way, the user can efficiently find rental properties close to their wishes through this system. 【0286】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0287】 Step 1: 【0288】 The user uses the terminal to input the desired conditions for the rental property. The data to be input are specific requirements such as the area, rent range, floor plan, and years since construction. This input becomes the basic dataset to be sent to the server. 【0289】 Step 2: 【0290】 The terminal receives the input from the user, converts it into JSON format or XML format, and packages the data. This packaged data is sent to the server efficiently and quickly. 【0291】 Step 3: 【0292】 The server analyzes the data received from the terminal and collects property information that matches the user's desired conditions. The server accesses multiple information sources through scraping or APIs to perform large-scale data collection. The input is the desired condition data, and the output is a list of highly relevant property data. 【0293】 Step 4: |> 【0294】 The server integrates the collected property data. It organizes the database by removing duplicate data and converting it to a consistent format. This operation generates a unified dataset. 【0295】 Step 5: 【0296】 The server uses a generative AI model to evaluate properties based on integrated data. Here, scoring is performed considering factors such as rent appropriateness, amenities, and age of the building. The input is an integrated and organized dataset, and the output is an evaluation result with a score for each property. 【0297】 Step 6: 【0298】 The server sends the scored evaluation results to the terminal. The evaluation results are visualized in a way that is easy for the user to understand, and are presented as graphs and tables. 【0299】 Step 7: 【0300】 The terminal receives evaluation results from the server and presents them visually to the user. Using an interactive UI, the user can compare evaluations and select the best property. 【0301】 Step 8: 【0302】 If a user requires more detailed information, they can request additional information from the server via their device. The server then collects and analyzes the requested information again and sends it back to the device. This iterative process allows the user to gain a deeper understanding of the property. 【0303】 (Application Example 1) 【0304】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0305】 In the modern housing selection process, there is a problem that users have to spend a great deal of time and effort on their own to search for properties that meet their desired conditions. In addition, information is generally provided as text information, making it difficult to perform advanced analysis and evaluation. Furthermore, the means for users to efficiently obtain information using voice is also limited. 【0306】 The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means. 【0307】 In this invention, the server includes means for a user to input desired conditions, means for collecting data from a plurality of information sources based on the desired conditions, and means for analyzing the data and performing property evaluation using an evaluation algorithm. As a result, through voice and visual information presentation, it becomes possible for users to intuitively and efficiently select properties. 【0308】 A "user" refers to a consumer who uses a system for searching and evaluating property information. 【0309】 "Desired conditions" refer to factors that users value when selecting a property, specifically including elements such as location, rent, floor plan, and years since construction. 【0310】 An "information source" is various digital platforms from which property information can be obtained, including websites and databases on the Internet. 【0311】 "Data" refers to the entire property information collected from information sources, including address, rent, equipment specifications, images, etc. 【0312】 "Analysis" is a data processing process for performing property evaluation that meets the conditions required by users based on the collected data. 【0313】 An "evaluation algorithm" is a calculation method for quantitatively evaluating the quality and value of a property, and uses a generated AI model to score the validity of rent and the equipment of the property. 【0314】 "Voice recognition" is a technology that interprets voice commands spoken by a user as digital data. 【0315】 "Speech synthesis" is a technology that converts text data into speech data and provides it to the user as audio information. 【0316】 "Presenting audio and visually" means providing evaluation results in a format that is easy for users to understand through both audio and visual means. 【0317】 To implement this invention, a user terminal and a server are key components. The user uses the terminal to input information about the desired property, such as location, rent, and floor plan. The terminal is responsible for transmitting this information to the server. 【0318】 Meanwhile, the server collects property data in real time from multiple sources. This collection utilizes API access using the Python Requests library and scraping techniques using BeautifulSoup to quickly obtain the necessary property information. The collected data is analyzed by a generative AI model for the evaluation algorithm, and properties are scored. This AI model uses OpenAI's GPT technology. 【0319】 The evaluation results generated by the server are provided to the user via the terminal in both audio and visual formats. The Google Speech-to-Text API is used for speech recognition, and existing text-to-speech technologies are used for speech synthesis. This makes it easier for users to intuitively understand the evaluation results. 【0320】 For example, if a user verbally requests, "I'd like a 2LDK apartment in Tokyo where I can live with my pet, with a rent of 150,000 yen or less," the server will select properties that meet the criteria and provide voice guidance such as, "In this area, we recommend a pet-friendly property with a rent of 140,000 yen," while also displaying the property's score and detailed information on the screen. An example of a prompt message would be, "Evaluate the property information based on the conditions specified by the user and suggest a suitable property." 【0321】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0322】 Step 1: 【0323】 The user inputs their desired property conditions by voice using a terminal. The terminal converts the voice data into text data using voice recognition software and sends it to the server as the received desired conditions. In this process, the input is the user's voice data, and the output is the desired conditions in text format. 【0324】 Step 2: 【0325】 The server collects property data from multiple sources on the internet based on the received request criteria. It uses API access via the Python Requests library and scraping techniques with BeautifulSoup. The input is property criteria in text format, and the output is a set of collected property data. 【0326】 Step 3: 【0327】 The server analyzes the collected property data. Using a generative AI model, it applies a property evaluation algorithm and scores each property. The input is a property dataset, and the output is a list of scores for each property. This identifies the property that best matches the user's desired conditions. 【0328】 Step 4: 【0329】 The server sends the scoring results to the terminal. The terminal presents this information to the user through a visual display and audio output using speech synthesis technology. The input is the scoring results, and the output is the visual and audio presentation to the user. 【0330】 Step 5: 【0331】 Users can review properties based on the provided information and request additional information as needed. The terminal resends this request to the server, which then performs further data collection and analysis. The input is the user's request for additional information, and the output is the updated property details. 【0332】 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. 【0333】 This invention relates to a system that integrates an emotion engine that reflects the user's emotions into the rental property search and evaluation process. This system consists of four main components: the user, the terminal, the server, and the emotion engine. 【0334】 The user first launches the property search application using their terminal and enters their desired property criteria. These criteria include specific requirements such as location, rent range, floor plan, and age of the building. The terminal receives the user's input and prepares to send that information to the server. 【0335】 The server collects property information from multiple sources on the internet based on the desired conditions received from the terminal. This process involves obtaining accurate and up-to-date information through scraping and API access. Before passing the collected data to the sentiment engine, the server inputs it into an automated analysis system, where a generative AI model is used to evaluate the properties. This evaluation considers factors such as market reasonableness of rent, property amenities, and age of the building. 【0336】 The emotion engine acquires and analyzes emotional data from user interactions, input, voice, and facial expressions. The server integrates this emotional data with property evaluation results and adjusts the information presented according to the user's emotional state. This allows the system to provide information tailored to the user's preferences and stress level at the optimal time. 【0337】 The terminal displays sentiment-based evaluation results received from the server to the user. The information is visually organized and presented in a user-friendly format, making decision-making easier. For example, the terminal could display "Property A: Recommendation Level: High" and "Sentiment-Based Recommendation: Provides a sense of security," allowing the user to confidently select a property. 【0338】 Users can compare properties based on the information provided and make the most appropriate choice. Furthermore, if the user requests more detailed information, the device will query the server again to provide the necessary additional information. This process allows users to thoroughly consider properties until they are satisfied. The introduction of an emotion engine improves the recommendation accuracy and usability of traditional property search systems, providing a more personalized experience for individual users. 【0339】 The following describes the processing flow. 【0340】 Step 1: 【0341】 The user accesses the terminal and opens the property search application. They enter their desired property criteria, such as area, rent range, floor plan, and year of construction. The terminal temporarily stores this input data and prepares to send it. 【0342】 Step 2: 【0343】 The terminal sends the entered desired conditions to the server. The server then identifies the search conditions and receives the information needed to begin the data collection process. 【0344】 Step 3: 【0345】 The server accesses multiple real estate information sources based on the received preferences. It uses APIs and web scraping techniques to collect relevant property information. The server stores the collected data in a temporary database. 【0346】 Step 4: 【0347】 The server passes the stored property data to a generating AI model for analysis. This analysis evaluates factors such as the reasonableness of the rent, the property's facilities, and its age, and assigns a score to each property. 【0348】 Step 5: 【0349】 The device simultaneously activates an emotion engine to recognize the user's emotions. It analyzes the user's input and reactions during operation to generate emotion data. For example, it measures the speed of input and the time taken to make selections to infer the user's interests and anxieties. 【0350】 Step 6: 【0351】 The emotional data obtained by the emotion engine is sent to the server. Based on this, the server adjusts the property evaluation results based on the user's emotional state. This makes it possible to suggest properties that take the user's emotions into consideration. 【0352】 Step 7: 【0353】 The server returns the adjusted evaluation results to the terminal. The terminal displays the evaluation results to the user in a visually organized format. The information is structured to aid user understanding and support decision-making. 【0354】 Step 8: 【0355】 Users compare properties based on the information presented and make their selection. By referring to the displayed sentiment-based recommendations and risk assessments, they can make a more informed choice. 【0356】 Step 9: 【0357】 If a user desires further details, they can request additional information through their device. The server analyzes the detailed data based on this request, taking into account the user's sentiment data, and provides additional information. This iterative process allows users to consider properties until they are satisfied. 【0358】 (Example 2) 【0359】 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". 【0360】 Traditional property search systems have the problem of presenting uniform information without considering the user's emotional state, making it difficult to alleviate the stress and anxiety they cause. Furthermore, common information formats often lack sufficient personalization to accommodate individual preferences and emotions. 【0361】 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. 【0362】 In this invention, the server includes a device for inputting search criteria from the user, a device for acquiring information from multiple information sources based on the search criteria, a device for analyzing the information and evaluating the target, a device for introducing the evaluation results into a generating AI model and integrating it with the user's emotional data, and a device for presenting the integrated information to the user. This makes it possible to provide information that corresponds to the user's emotional state. 【0363】 A "device for users to input search criteria" is a device that provides an interface for users to specify their desired conditions to the system and for those conditions to be treated as data. 【0364】 A "device that acquires information from multiple sources" is a device that collects necessary data from various sources, such as the internet and databases. 【0365】 A "device for evaluating an object" is a device that has the function of evaluating an object according to certain criteria based on acquired information and outputting the evaluation results. 【0366】 A "device for integrating user sentiment data into a generative AI model" is a device that inputs evaluation results into a generative model and adjusts and integrates those results while taking user sentiment data into consideration. 【0367】 A "device that presents integrated information to the user" is a device that displays processed evaluation and adjustment results in a format that is easy for the user to understand. 【0368】 This invention is a system that enables users to obtain property information based on their desired conditions during the real estate search process, and further provides information according to the user's emotional state. A specific embodiment of this system is shown below. 【0369】 The user launches a property search application using their device. Here, the user enters search criteria such as location, rent, floor plan, and year of construction. The device receives this information and sends it to the server via the network. 【0370】 The server collects property information from multiple sources on the internet based on search criteria sent from the terminal. Web scraping techniques and public APIs are used as collection methods. This allows the server to obtain the latest and most accurate information and aggregate it into a database. 【0371】 Next, the server inputs the aggregated information into a generating AI model. This model evaluates the property, assessing it from multiple perspectives, including the appropriateness of the rent, the quality of the facilities, and the age of the building. 【0372】 Furthermore, the server uses an emotion engine to analyze emotional data obtained from the user. This data is collected from user input, voice, facial expressions, and other sources. The server integrates and adjusts this emotional data with the property evaluation results to generate information that is optimal for the user's emotional state. 【0373】 The terminal receives evaluation results sent from the server and displays the information to the user in a visually organized format. This allows the user to make more rational decisions. For example, the terminal might display information such as "Property A: Recommendation Level: High, Emotional Recommendation: Provides a sense of security." 【0374】 For example, if a user specifies search criteria such as "Tokyo, 2LDK, under 100,000 yen, built within the last 10 years," the system will present a list of properties matching these criteria, along with sentiment ratings. This allows the user to smoothly make the best choice based on this information. 【0375】 This system breaks away from the uniformity of information in conventional property searches and enables the provision of customized information that resonates with the user's emotions. 【0376】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0377】 Step 1: 【0378】 The user launches a property search application on their device and enters their search criteria. This information includes location, rent, floor plan, and year of construction. This data is converted into a digital format within the device, preparing it for further processing. The output of this process is formatted search criteria data. 【0379】 Step 2: 【0380】 The terminal sends search criteria data obtained from the user to the server via the network. This process includes preparing the data for transmission, encoding it, and converting it into network packets. This allows the server to analyze the data. The output of this step is data formatted for the server to receive. 【0381】 Step 3: 【0382】 The server collects property information from multiple databases on the internet based on the search criteria received from the terminal. This collection utilizes web scraping and API access to retrieve the latest information in real time. The input is the search criteria, and the output is a collection of relevant property information. 【0383】 Step 4: 【0384】 The server analyzes the collected property information. Using a generative AI model, it evaluates each property from perspectives such as market value, facilities, and age. This evaluation allows for the quantification of the property's attractiveness and value. The input is the collected property information, and the output is a dataset of evaluation results. 【0385】 Step 5: 【0386】 The emotion engine analyzes user emotional data. It analyzes the user's emotional state from voice, facial expressions, and input data obtained from the device, and determines how information should be presented. The input is raw data about the user's emotions, and the output is analyzed emotion evaluation data. 【0387】 Step 6: 【0388】 The server integrates property evaluation results with analyzed sentiment evaluation data. It adjusts the property recommendation level according to the user's emotional state, generating customized information. This integration enables the provision of information that aligns with the user's emotions. The output is the integrated evaluation information. 【0389】 Step 7: 【0390】 The terminal receives customized evaluation information sent from the server and displays it to the user. The display is in an easy-to-understand format to assist the user in making decisions. The input is integrated evaluation information from the server, and the output is visual information presented to the user. 【0391】 Step 8: 【0392】 The user compares and selects properties based on the information presented. If necessary, they request further details and make additional inquiries to the server via their terminal. This allows the user to obtain sufficient information to make an informed decision. The input is the displayed property information, and the output is the user's selection result. 【0393】 (Application Example 2) 【0394】 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." 【0395】 Traditional property search systems often present information without considering the user's emotional state, resulting in stressful information being presented or information being displayed at inappropriate times. Furthermore, the lack of personalized recommendations tailored to individual users resulted in poor usability. 【0396】 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. 【0397】 In this invention, the server includes means for analyzing the user's emotions, means for adjusting the presentation of information based on the results of the emotion analysis, and means for providing additional information to the user in an interactive format. This enables the provision of information at the optimal timing according to the user's emotions and improves usability through high personalization. 【0398】 A "user" is an entity that uses the system to input desired conditions and participates in the search and evaluation of properties. 【0399】 "Desired conditions" refer to the specific requirements that users set when searching for a property, such as location, rent, floor plan, and age of the building. 【0400】 "Device" refers to a general term for equipment and programs used within a system as a means of inputting, collecting, analyzing, and presenting information. 【0401】 "Information sources" refer to multiple data providers on the internet that are accessed to collect property information. 【0402】 "Information" refers to detailed data about a property that is analyzed based on collected data. 【0403】 "Evaluation" is the process of determining the value and suitability of a property based on the information gathered about it. 【0404】 "Presentation" refers to the act of providing the user with the results of the system's analysis and evaluation, either visually or audibly. 【0405】 "Emotions" represent the user's mental state and are data obtained from the user's facial expressions, voice, and input interactions. 【0406】 "Analysis" is the process of analyzing collected information and emotional data to generate meaningful evaluation results. 【0407】 "Adjustment" is the process of optimizing the content and timing of information presented based on the results of the user's sentiment analysis. 【0408】 "Dialogue format" refers to a method of interactive information exchange between the user and the system. 【0409】 This invention provides a specific embodiment of a system for searching and evaluating property information based on user emotions. The system mainly consists of a user terminal, a server, an emotion analysis device, and an information presentation device. 【0410】 The user launches a property search application using their device and enters their desired property criteria. The device has the function of sending the user's desired criteria to the server. 【0411】 The server collects property data from multiple sources based on the received conditions. This information is obtained through internet databases and APIs. The server analyzes this information and generates property evaluations using an AI model. 【0412】 The emotion analysis device acquires emotional data such as the user's facial expressions and voice, and analyzes their emotional state using a cloud-based emotion analysis API (for example, Azure Emotion API). The analysis results are sent to a server, where the emotional data is integrated into the property evaluation results. 【0413】 This integrated information is displayed on the user's terminal via an information display device. The terminal then presents the user with property information best suited to their emotional evaluation. For example, if the user indicates a desire for a sense of security, the system can provide information in the format of "Property A: Recommendation Level: High, Provides a sense of security." 【0414】 Through this process, users can make more informed decisions when selecting a property. Furthermore, the interactive features provided by the system allow users to easily obtain additional information and conduct more in-depth comparisons. 【0415】 Examples of prompt statements for generative AI models are as follows: 【0416】 "Please display a list of recommended products for users when they are having fun." 【0417】 "Please tell us about products that help users relax when they are feeling stressed." 【0418】 In this way, by utilizing sentiment analysis to provide information tailored to the user's preferences and emotions, highly personalized property selection support can be achieved. 【0419】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0420】 Step 1: 【0421】 The user operates the terminal to launch the property search application and enters the desired property criteria (area, rent, floor plan, year built, etc.). The entered criteria are formatted into a structured data format within the terminal and prepared for transmission to the server. 【0422】 Step 2: 【0423】 The server uses the desired conditions received from the terminal to collect property data from multiple sources on the internet. Specifically, it obtains information that matches the conditions through a property information database and external APIs. In doing so, it utilizes scraping techniques and API access to collect the latest and most accurate data, which is then stored in an internal database. 【0424】 Step 3: 【0425】 The server uses a generative AI model to evaluate properties based on collected property data. The AI ​​model calculates a score for each property using a dataset that includes factors such as market price reasonableness, property amenities, and age. This evaluation result is then passed on to the next process. 【0426】 Step 4: 【0427】 The emotion analysis device collects user facial expression data and voice input and sends it to a server. Specifically, it acquires data from the device's camera and microphone, and this data is processed by an emotion analysis API (e.g., Azure Emotion API) to generate data indicating emotions. 【0428】 Step 5: 【0429】 The server adjusts property evaluation results based on sentiment analysis. If the user's emotional state is positive, it makes specific adjustments, such as setting a higher recommendation level. By applying emotion-based filtering and ranking, it creates information optimized for each individual user. 【0430】 Step 6: 【0431】 The integrated evaluation information sent from the server is presented to the terminal. Specifically, the terminal displays property information in a visually easy-to-understand format. Property details and recommendation levels are displayed at a time and in a format that is easy for the user to accept, helping them make a selection. 【0432】 Step 7: 【0433】 Users can compare properties based on the information displayed on their device and select the most suitable one. If they require further details, they can query the server again to obtain additional information. This allows users to thoroughly consider properties until they are satisfied. 【0434】 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. 【0435】 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. 【0436】 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. 【0437】 [Third Embodiment] 【0438】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0439】 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. 【0440】 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). 【0441】 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. 【0442】 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. 【0443】 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). 【0444】 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. 【0445】 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. 【0446】 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. 【0447】 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. 【0448】 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. 【0449】 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". 【0450】 The present invention relates to a system that assists in searching for and evaluating rental properties, and this system mainly consists of three components: a user, a terminal, and a server. 【0451】 The user first uses a terminal to input their desired property criteria. This includes specific conditions such as the desired area, rent range, floor plan, and age of the building. The terminal receives the user's input and sends it to the server as data. 【0452】 The server collects relevant property information from multiple sources on the internet based on the data it receives. This process is designed to obtain the latest information using automated data collection methods such as scraping and API access. For example, when searching for properties in Tokyo with a rent of 100,000 yen or less, the server gathers matching data from multiple real estate websites and integrates it into a single database. 【0453】 After collection, the server analyzes the property data. Using a generated AI model, properties are evaluated and scored based on factors such as rent appropriateness, property amenities, and age of the building. These analysis results are then sent back to the terminal. 【0454】 The terminal displays the evaluation results received from the server to the user. This presentation is visually easy to understand, allowing the user to easily comprehend and consider the information presented. For example, information about property A might be displayed in the format of "Recommendation level: High" and "Contract risk: Medium." 【0455】 Based on the information received, users can compare properties and make appropriate selections. Furthermore, if the user requests additional information, the terminal can query the server again to supplement with detailed information and risk assessments. In this way, the present invention supports the process of users selecting rental properties in a rational and efficient manner. 【0456】 The following describes the processing flow. 【0457】 Step 1: 【0458】 The user launches a property search application using their device and enters their desired rental conditions. These conditions include location, rent range, floor plan, and building age. The device waits for user input and prepares to send the information to the server once input is complete. 【0459】 Step 2: 【0460】 The terminal sends the entered desired conditions to the server. Based on the conditions received, the server prepares to access relevant internet sources. These sources include databases and websites that provide real estate information. 【0461】 Step 3: 【0462】 The server collects property information matching the desired criteria from multiple sources through scraping or API access. This process also includes data cleaning as needed to maintain data integrity and accuracy. 【0463】 Step 4: 【0464】 The server passes the collected property data to an automated analysis system, which uses a generated AI model to evaluate each property. Evaluation criteria include market reasonableness of rent, property amenities, and age of the building, and each item is scored. 【0465】 Step 5: 【0466】 The server organizes the analysis results and converts them into a user-friendly format. This may include visual hints about the property's recommendation level and contract risks. The converted evaluation results are then sent to the terminal. 【0467】 Step 6: 【0468】 The terminal displays the evaluation results received from the server to the user. The user reviews each evaluation criterion for the presented property and examines the details as needed. The information is presented in a visually organized format and designed to support the user's decision-making. 【0469】 Step 7: 【0470】 Users compare properties based on the evaluation results and make the choice they deem best. If users require more detailed information, they can request additional information from the server via their device. 【0471】 Step 8: 【0472】 The server receives requests for additional information from the user and performs further data analysis. If there is a detailed risk assessment or supplementary information, it is also sent back to the terminal. This process can be repeated until the user is satisfied. 【0473】 (Example 1) 【0474】 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." 【0475】 Traditional rental property search systems lacked the detailed property evaluations and risk information users needed, making efficient property selection difficult. Furthermore, obtaining up-to-date information in real time was challenging, even with data collection from multiple sources. Additionally, there was a lack of flexible, interactive features to select suitable properties based on user preferences. 【0476】 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. 【0477】 In this invention, the server includes a device for receiving user requests, a device for acquiring information from an external data source, a device for integrating the information and performing an evaluation, a device for using a generative artificial intelligence model for the evaluation, a device for visualizing and displaying the evaluation results to the user, and a program for providing the results of the property risk evaluation. This enables the user to make efficient and appropriate property selections based on detailed property evaluations and risk information. 【0478】 A "user" is an individual or corporation who wishes to search for or evaluate properties, and is the entity that enters their desired conditions. 【0479】 "Desired conditions" refer to the requirements and criteria that users look for in a rental property, and specifically include area, rent, floor plan, and age of the building. 【0480】 "Device" refers to an electronic system or instrument, and in this context, it refers to a component that has the function of receiving, processing, and outputting data. 【0481】 "Information sources" refer to external databases and websites that provide data on rental properties, and include various platforms that provide real estate information. 【0482】 "Evaluation" is the process of analyzing the value and characteristics of a property based on collected information, and then scoring or ranking it. 【0483】 A "generative artificial intelligence model" is an algorithmic structure that learns patterns from large amounts of data and uses them for evaluation and prediction. 【0484】 "Visualization" is a method of presenting data and evaluation results visually in the form of graphs, charts, and other diagrams, making them easy for users to understand. 【0485】 A "program" is a set of instructions that automatically perform evaluations or information processing on specific items, and is executed by a computer device. 【0486】 "Risk assessment" is the process of analyzing potential risks associated with a property and notifying the user. 【0487】 "Interactive format" refers to a method in which users interact with the system in a two-way manner, and it plays an important role in searching for and retrieving information. 【0488】 This invention is a system for assisting in the search and evaluation of rental properties, and mainly consists of three elements: a user, a terminal, and a server. The user first uses the terminal to input their desired conditions. These conditions include the desired area, rent range, floor plan, and age of the building. 【0489】 The terminal organizes the data entered by the user and sends it to the server. This transmission utilizes data formats such as JSON and XML for efficient data exchange. 【0490】 The server collects information from multiple data sources on the internet based on the user's desired conditions. This information collection utilizes scraping techniques and API access, enabling the acquisition of the latest property information in real time. After collection, the server integrates this data, removing redundant data and standardizing the format. 【0491】 Once data integration is complete, the server uses a generated AI model to evaluate properties. This process involves scoring each property based on criteria such as rent appropriateness, amenities, and age of the building. The results are then processed into a visually easy-to-understand format and sent to the terminal. 【0492】 The terminal displays the evaluation results received from the server to the user. This display is done through an interactive UI, supporting the user in easily comparing and considering properties. 【0493】 For example, if a user searches for a property in Tokyo with a rent of 80,000 yen or less, 2LDK layout, and built within the last 10 years, the terminal sends these conditions to the server. The server collects relevant data from various real estate information websites and uses a generated AI model to evaluate the results, presenting them to the user in the form of "Recommendation Level: High" and "Contract Risk: Medium." An example of a prompt message to be entered into this system is as follows: "Please collect and evaluate information on properties in Tokyo with a rent of 100,000 yen or less, 1LDK layout, and built within the last 5 years." In this way, users can efficiently find rental properties that closely match their preferences through this system. 【0494】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0495】 Step 1: 【0496】 Users use a terminal to input their desired conditions for rental properties. The data entered includes specific requirements such as area, rent range, floor plan, and building age. This input forms the basic dataset that is sent to the server. 【0497】 Step 2: 【0498】 The terminal receives input from the user, converts it into JSON or XML format, and packages the data. This packaged data is then sent to the server efficiently and quickly. 【0499】 Step 3: 【0500】 The server analyzes data received from the terminal and collects property information that matches the user's desired criteria. The server accesses multiple information sources through scraping and APIs to perform large-scale data collection. Desired criteria data is provided as input, and a list of highly relevant property data is obtained as output. 【0501】 Step 4: 【0502】 The server integrates the collected property data. It organizes the database by removing duplicate data and converting it to a consistent format. This operation generates a unified dataset. 【0503】 Step 5: 【0504】 The server uses a generative AI model to evaluate properties based on integrated data. Here, scoring is performed considering factors such as rent appropriateness, amenities, and age of the building. The input is an integrated and organized dataset, and the output is an evaluation result with a score for each property. 【0505】 Step 6: 【0506】 The server sends the scored evaluation results to the terminal. The evaluation results are visualized in a way that is easy for the user to understand, and are presented as graphs and tables. 【0507】 Step 7: 【0508】 The terminal receives evaluation results from the server and presents them visually to the user. Using an interactive UI, the user can compare evaluations and select the best property. 【0509】 Step 8: 【0510】 If a user requires more detailed information, they can request additional information from the server via their device. The server then collects and analyzes the requested information again and sends it back to the device. This iterative process allows the user to gain a deeper understanding of the property. 【0511】 (Application Example 1) 【0512】 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." 【0513】 The modern housing selection process presents a problem: users must spend considerable time and effort searching for properties that meet their desired criteria. Furthermore, information is generally provided in text format, making sophisticated analysis and evaluation difficult. Additionally, there are limited means for users to efficiently obtain information using voice. 【0514】 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. 【0515】 In this invention, the server includes means for receiving desired conditions from the user, means for collecting data from multiple information sources based on the desired conditions, and means for analyzing the data and evaluating properties using an evaluation algorithm. This enables the user to intuitively and efficiently select properties through voice and visual information presentation. 【0516】 A "user" is a consumer who uses a system to search for and rate property information. 【0517】 "Desired conditions" refer to the factors that users prioritize when selecting a property, and specifically include elements such as location, rent, floor plan, and age of the building. 【0518】 "Information sources" refer to various digital platforms from which property information can be obtained, including websites and databases on the internet. 【0519】 "Data" refers to all property information collected from the source, including address, rent, equipment specifications, and images. 【0520】 "Analysis" is a data processing process that uses collected data to evaluate properties that meet the conditions requested by the user. 【0521】 An "evaluation algorithm" is a computational method for quantitatively evaluating the quality and value of a property, using a generative AI model to score the reasonableness of the rent and the property's amenities. 【0522】 "Voice recognition" is a technology that interprets voice commands spoken by a user as digital data. 【0523】 "Speech synthesis" is a technology that converts text data into speech data and provides it to the user as audio information. 【0524】 "Presenting audio and visually" means providing evaluation results in a format that is easy for users to understand through both audio and visual means. 【0525】 To implement this invention, a user terminal and a server are key components. The user uses the terminal to input information about the desired property, such as location, rent, and floor plan. The terminal is responsible for transmitting this information to the server. 【0526】 Meanwhile, the server collects property data in real time from multiple sources. This collection utilizes API access using the Python Requests library and scraping techniques using BeautifulSoup to quickly obtain the necessary property information. The collected data is analyzed by a generative AI model for the evaluation algorithm, and properties are scored. This AI model uses OpenAI's GPT technology. 【0527】 The evaluation results generated by the server are provided to the user via the terminal in both audio and visual formats. The Google Speech-to-Text API is used for speech recognition, and existing text-to-speech technologies are used for speech synthesis. This makes it easier for users to intuitively understand the evaluation results. 【0528】 For example, if a user verbally requests, "I'd like a 2LDK apartment in Tokyo where I can live with my pet, with a rent of 150,000 yen or less," the server will select properties that meet the criteria and provide voice guidance such as, "In this area, we recommend a pet-friendly property with a rent of 140,000 yen," while also displaying the property's score and detailed information on the screen. An example of a prompt message would be, "Evaluate the property information based on the conditions specified by the user and suggest a suitable property." 【0529】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0530】 Step 1: 【0531】 The user inputs their desired property conditions by voice using a terminal. The terminal converts the voice data into text data using voice recognition software and sends it to the server as the received desired conditions. In this process, the input is the user's voice data, and the output is the desired conditions in text format. 【0532】 Step 2: 【0533】 The server collects property data from multiple sources on the internet based on the received request criteria. It uses API access via the Python Requests library and scraping techniques with BeautifulSoup. The input is property criteria in text format, and the output is a set of collected property data. 【0534】 Step 3: 【0535】 The server analyzes the collected property data. Using a generative AI model, it applies a property evaluation algorithm and scores each property. The input is a property dataset, and the output is a list of scores for each property. This identifies the property that best matches the user's desired conditions. 【0536】 Step 4: 【0537】 The server sends the scoring results to the terminal. The terminal presents this information to the user through a visual display and audio output using speech synthesis technology. The input is the scoring results, and the output is the visual and audio presentation to the user. 【0538】 Step 5: 【0539】 Users can review properties based on the provided information and request additional information as needed. The terminal resends this request to the server, which then performs further data collection and analysis. The input is the user's request for additional information, and the output is the updated property details. 【0540】 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. 【0541】 This invention relates to a system that integrates an emotion engine that reflects the user's emotions into the rental property search and evaluation process. This system consists of four main components: the user, the terminal, the server, and the emotion engine. 【0542】 The user first launches the property search application using their terminal and enters their desired property criteria. These criteria include specific requirements such as location, rent range, floor plan, and age of the building. The terminal receives the user's input and prepares to send that information to the server. 【0543】 The server collects property information from multiple sources on the internet based on the desired conditions received from the terminal. This process involves obtaining accurate and up-to-date information through scraping and API access. Before passing the collected data to the sentiment engine, the server inputs it into an automated analysis system, where a generative AI model is used to evaluate the properties. This evaluation considers factors such as market reasonableness of rent, property amenities, and age of the building. 【0544】 The emotion engine acquires and analyzes emotional data from user interactions, input, voice, and facial expressions. The server integrates this emotional data with property evaluation results and adjusts the information presented according to the user's emotional state. This allows the system to provide information tailored to the user's preferences and stress level at the optimal time. 【0545】 The terminal displays sentiment-based evaluation results received from the server to the user. The information is visually organized and presented in a user-friendly format, making decision-making easier. For example, the terminal could display "Property A: Recommendation Level: High" and "Sentiment-Based Recommendation: Provides a sense of security," allowing the user to confidently select a property. 【0546】 Users can compare properties based on the information provided and make the most appropriate choice. Furthermore, if the user requests more detailed information, the device will query the server again to provide the necessary additional information. This process allows users to thoroughly consider properties until they are satisfied. The introduction of an emotion engine improves the recommendation accuracy and usability of traditional property search systems, providing a more personalized experience for individual users. 【0547】 The following describes the processing flow. 【0548】 Step 1: 【0549】 The user accesses the terminal and opens the property search application. They enter their desired property criteria, such as area, rent range, floor plan, and year of construction. The terminal temporarily stores this input data and prepares to send it. 【0550】 Step 2: 【0551】 The terminal sends the entered desired conditions to the server. The server then identifies the search conditions and receives the information needed to begin the data collection process. 【0552】 Step 3: 【0553】 The server accesses multiple real estate information sources based on the received preferences. It uses APIs and web scraping techniques to collect relevant property information. The server stores the collected data in a temporary database. 【0554】 Step 4: 【0555】 The server passes the stored property data to a generating AI model for analysis. This analysis evaluates factors such as the reasonableness of the rent, the property's facilities, and its age, and assigns a score to each property. 【0556】 Step 5: 【0557】 The device simultaneously activates an emotion engine to recognize the user's emotions. It analyzes the user's input and reactions during operation to generate emotion data. For example, it measures the speed of input and the time taken to make selections to infer the user's interests and anxieties. 【0558】 Step 6: 【0559】 The emotional data obtained by the emotion engine is sent to the server. Based on this, the server adjusts the property evaluation results based on the user's emotional state. This makes it possible to suggest properties that take the user's emotions into consideration. 【0560】 Step 7: 【0561】 The server returns the adjusted evaluation results to the terminal. The terminal displays the evaluation results to the user in a visually organized format. The information is structured to aid user understanding and support decision-making. 【0562】 Step 8: 【0563】 Users compare properties based on the information presented and make their selection. By referring to the displayed sentiment-based recommendations and risk assessments, they can make a more informed choice. 【0564】 Step 9: 【0565】 If a user desires further details, they can request additional information through their device. The server analyzes the detailed data based on this request, taking into account the user's sentiment data, and provides additional information. This iterative process allows users to consider properties until they are satisfied. 【0566】 (Example 2) 【0567】 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." 【0568】 Traditional property search systems have the problem of presenting uniform information without considering the user's emotional state, making it difficult to alleviate the stress and anxiety they cause. Furthermore, common information formats often lack sufficient personalization to accommodate individual preferences and emotions. 【0569】 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. 【0570】 In this invention, the server includes a device for inputting search criteria from the user, a device for acquiring information from multiple information sources based on the search criteria, a device for analyzing the information and evaluating the target, a device for introducing the evaluation results into a generating AI model and integrating it with the user's emotional data, and a device for presenting the integrated information to the user. This makes it possible to provide information that corresponds to the user's emotional state. 【0571】 A "device for users to input search criteria" is a device that provides an interface for users to specify their desired conditions to the system and for those conditions to be treated as data. 【0572】 A "device that acquires information from multiple sources" is a device that collects necessary data from various sources, such as the internet and databases. 【0573】 A "device for evaluating an object" is a device that has the function of evaluating an object according to certain criteria based on acquired information and outputting the evaluation results. 【0574】 A "device for integrating user sentiment data into a generative AI model" is a device that inputs evaluation results into a generative model and adjusts and integrates those results while taking user sentiment data into consideration. 【0575】 A "device that presents integrated information to the user" is a device that displays processed evaluation and adjustment results in a format that is easy for the user to understand. 【0576】 This invention is a system that enables users to obtain property information based on their desired conditions during the real estate search process, and further provides information according to the user's emotional state. A specific embodiment of this system is shown below. 【0577】 The user launches a property search application using their device. Here, the user enters search criteria such as location, rent, floor plan, and year of construction. The device receives this information and sends it to the server via the network. 【0578】 The server collects property information from multiple sources on the internet based on search criteria sent from the terminal. Web scraping techniques and public APIs are used as collection methods. This allows the server to obtain the latest and most accurate information and aggregate it into a database. 【0579】 Next, the server inputs the aggregated information into a generating AI model. This model evaluates the property, assessing it from multiple perspectives, including the appropriateness of the rent, the quality of the facilities, and the age of the building. 【0580】 Furthermore, the server uses an emotion engine to analyze emotional data obtained from the user. This data is collected from user input, voice, facial expressions, and other sources. The server integrates and adjusts this emotional data with the property evaluation results to generate information that is optimal for the user's emotional state. 【0581】 The terminal receives evaluation results sent from the server and displays the information to the user in a visually organized format. This allows the user to make more rational decisions. For example, the terminal might display information such as "Property A: Recommendation Level: High, Emotional Recommendation: Provides a sense of security." 【0582】 For example, if a user specifies search criteria such as "Tokyo, 2LDK, under 100,000 yen, built within the last 10 years," the system will present a list of properties matching these criteria, along with sentiment ratings. This allows the user to smoothly make the best choice based on this information. 【0583】 This system breaks away from the uniformity of information in conventional property searches and enables the provision of customized information that resonates with the user's emotions. 【0584】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0585】 Step 1: 【0586】 The user launches a property search application on their device and enters their search criteria. This information includes location, rent, floor plan, and year of construction. This data is converted into a digital format within the device, preparing it for further processing. The output of this process is formatted search criteria data. 【0587】 Step 2: 【0588】 The terminal sends search criteria data obtained from the user to the server via the network. This process includes preparing the data for transmission, encoding it, and converting it into network packets. This allows the server to analyze the data. The output of this step is data formatted for the server to receive. 【0589】 Step 3: 【0590】 The server collects property information from multiple databases on the internet based on the search criteria received from the terminal. This collection utilizes web scraping and API access to retrieve the latest information in real time. The input is the search criteria, and the output is a collection of relevant property information. 【0591】 Step 4: 【0592】 The server analyzes the collected property information. Using a generative AI model, it evaluates each property from perspectives such as market value, facilities, and age. This evaluation allows for the quantification of the property's attractiveness and value. The input is the collected property information, and the output is a dataset of evaluation results. 【0593】 Step 5: 【0594】 The emotion engine analyzes user emotional data. It analyzes the user's emotional state from voice, facial expressions, and input data obtained from the device, and determines how information should be presented. The input is raw data about the user's emotions, and the output is analyzed emotion evaluation data. 【0595】 Step 6: 【0596】 The server integrates property evaluation results with analyzed sentiment evaluation data. It adjusts the property recommendation level according to the user's emotional state, generating customized information. This integration enables the provision of information that aligns with the user's emotions. The output is the integrated evaluation information. 【0597】 Step 7: 【0598】 The terminal receives customized evaluation information sent from the server and displays it to the user. The display is in an easy-to-understand format to assist the user in making decisions. The input is integrated evaluation information from the server, and the output is visual information presented to the user. 【0599】 Step 8: 【0600】 The user compares and selects properties based on the information presented. If necessary, they request further details and make additional inquiries to the server via their terminal. This allows the user to obtain sufficient information to make an informed decision. The input is the displayed property information, and the output is the user's selection result. 【0601】 (Application Example 2) 【0602】 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." 【0603】 Traditional property search systems often present information without considering the user's emotional state, resulting in stressful information being presented or information being displayed at inappropriate times. Furthermore, the lack of personalized recommendations tailored to individual users resulted in poor usability. 【0604】 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. 【0605】 In this invention, the server includes means for analyzing the user's emotions, means for adjusting the presentation of information based on the results of the emotion analysis, and means for providing additional information to the user in an interactive format. This enables the provision of information at the optimal timing according to the user's emotions and improves usability through high personalization. 【0606】 A "user" is an entity that uses the system to input desired conditions and participates in the search and evaluation of properties. 【0607】 "Desired conditions" refer to the specific requirements that users set when searching for a property, such as location, rent, floor plan, and age of the building. 【0608】 "Device" refers to a general term for equipment and programs used within a system as a means of inputting, collecting, analyzing, and presenting information. 【0609】 "Information sources" refer to multiple data providers on the internet that are accessed to collect property information. 【0610】 "Information" refers to detailed data about a property that is analyzed based on collected data. 【0611】 "Evaluation" is the process of determining the value and suitability of a property based on the information gathered about it. 【0612】 "Presentation" refers to the act of providing the user with the results of the system's analysis and evaluation, either visually or audibly. 【0613】 "Emotions" represent the user's mental state and are data obtained from the user's facial expressions, voice, and input interactions. 【0614】 "Analysis" is the process of analyzing collected information and emotional data to generate meaningful evaluation results. 【0615】 "Adjustment" is the process of optimizing the content and timing of information presented based on the results of the user's sentiment analysis. 【0616】 "Dialogue format" refers to a method of interactive information exchange between the user and the system. 【0617】 This invention provides a specific embodiment of a system for searching and evaluating property information based on user emotions. The system mainly consists of a user terminal, a server, an emotion analysis device, and an information presentation device. 【0618】 The user launches a property search application using their device and enters their desired property criteria. The device has the function of sending the user's desired criteria to the server. 【0619】 The server collects property data from multiple sources based on the received conditions. This information is obtained through internet databases and APIs. The server analyzes this information and generates property evaluations using an AI model. 【0620】 The emotion analysis device acquires emotional data such as the user's facial expressions and voice, and analyzes their emotional state using a cloud-based emotion analysis API (for example, Azure Emotion API). The analysis results are sent to a server, where the emotional data is integrated into the property evaluation results. 【0621】 This integrated information is displayed on the user's terminal via an information display device. The terminal then presents the user with property information best suited to their emotional evaluation. For example, if the user indicates a desire for a sense of security, the system can provide information in the format of "Property A: Recommendation Level: High, Provides a sense of security." 【0622】 Through this process, users can make more informed decisions when selecting a property. Furthermore, the interactive features provided by the system allow users to easily obtain additional information and conduct more in-depth comparisons. 【0623】 Examples of prompt statements for generative AI models are as follows: 【0624】 "Please display a list of recommended products for users when they are having fun." 【0625】 "Please tell us about products that help users relax when they are feeling stressed." 【0626】 In this way, by utilizing sentiment analysis to provide information tailored to the user's preferences and emotions, highly personalized property selection support can be achieved. 【0627】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0628】 Step 1: 【0629】 The user operates the terminal to launch the property search application and enters the desired property criteria (area, rent, floor plan, year built, etc.). The entered criteria are formatted into a structured data format within the terminal and prepared for transmission to the server. 【0630】 Step 2: 【0631】 The server uses the desired conditions received from the terminal to collect property data from multiple sources on the internet. Specifically, it obtains information that matches the conditions through a property information database and external APIs. In doing so, it utilizes scraping techniques and API access to collect the latest and most accurate data, which is then stored in an internal database. 【0632】 Step 3: 【0633】 The server uses a generative AI model to evaluate properties based on collected property data. The AI ​​model calculates a score for each property using a dataset that includes factors such as market price reasonableness, property amenities, and age. This evaluation result is then passed on to the next process. 【0634】 Step 4: 【0635】 The emotion analysis device collects user facial expression data and voice input and sends it to a server. Specifically, it acquires data from the device's camera and microphone, and this data is processed by an emotion analysis API (e.g., Azure Emotion API) to generate data indicating emotions. 【0636】 Step 5: 【0637】 The server adjusts property evaluation results based on sentiment analysis. If the user's emotional state is positive, it makes specific adjustments, such as setting a higher recommendation level. By applying emotion-based filtering and ranking, it creates information optimized for each individual user. 【0638】 Step 6: 【0639】 The integrated evaluation information sent from the server is presented to the terminal. Specifically, the terminal displays property information in a visually easy-to-understand format. Property details and recommendation levels are displayed at a time and in a format that is easy for the user to accept, helping them make a selection. 【0640】 Step 7: 【0641】 Users can compare properties based on the information displayed on their device and select the most suitable one. If they require further details, they can query the server again to obtain additional information. This allows users to thoroughly consider properties until they are satisfied. 【0642】 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. 【0643】 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. 【0644】 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. 【0645】 [Fourth Embodiment] 【0646】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0647】 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. 【0648】 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). 【0649】 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. 【0650】 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. 【0651】 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). 【0652】 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. 【0653】 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. 【0654】 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. 【0655】 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. 【0656】 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. 【0657】 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. 【0658】 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". 【0659】 The present invention relates to a system that assists in searching for and evaluating rental properties, and this system mainly consists of three components: a user, a terminal, and a server. 【0660】 The user first uses a terminal to input their desired property criteria. This includes specific conditions such as the desired area, rent range, floor plan, and age of the building. The terminal receives the user's input and sends it to the server as data. 【0661】 The server collects relevant property information from multiple sources on the internet based on the data it receives. This process is designed to obtain the latest information using automated data collection methods such as scraping and API access. For example, when searching for properties in Tokyo with a rent of 100,000 yen or less, the server gathers matching data from multiple real estate websites and integrates it into a single database. 【0662】 After collection, the server analyzes the property data. Using a generated AI model, properties are evaluated and scored based on factors such as rent appropriateness, property amenities, and age of the building. These analysis results are then sent back to the terminal. 【0663】 The terminal displays the evaluation results received from the server to the user. This presentation is visually easy to understand, allowing the user to easily comprehend and consider the information presented. For example, information about property A might be displayed in the format of "Recommendation level: High" and "Contract risk: Medium." 【0664】 Based on the information received, users can compare properties and make appropriate selections. Furthermore, if the user requests additional information, the terminal can query the server again to supplement with detailed information and risk assessments. In this way, the present invention supports the process of users selecting rental properties in a rational and efficient manner. 【0665】 The following describes the processing flow. 【0666】 Step 1: 【0667】 The user launches a property search application using their device and enters their desired rental conditions. These conditions include location, rent range, floor plan, and building age. The device waits for user input and prepares to send the information to the server once input is complete. 【0668】 Step 2: 【0669】 The terminal sends the entered desired conditions to the server. Based on the conditions received, the server prepares to access relevant internet sources. These sources include databases and websites that provide real estate information. 【0670】 Step 3: 【0671】 The server collects property information matching the desired criteria from multiple sources through scraping or API access. This process also includes data cleaning as needed to maintain data integrity and accuracy. 【0672】 Step 4: 【0673】 The server passes the collected property data to an automated analysis system, which uses a generated AI model to evaluate each property. Evaluation criteria include market reasonableness of rent, property amenities, and age of the building, and each item is scored. 【0674】 Step 5: 【0675】 The server organizes the analysis results and converts them into a user-friendly format. This may include visual hints about the property's recommendation level and contract risks. The converted evaluation results are then sent to the terminal. 【0676】 Step 6: 【0677】 The terminal displays the evaluation results received from the server to the user. The user reviews each evaluation criterion for the presented property and examines the details as needed. The information is presented in a visually organized format and designed to support the user's decision-making. 【0678】 Step 7: 【0679】 Users compare properties based on the evaluation results and make the choice they deem best. If users require more detailed information, they can request additional information from the server via their device. 【0680】 Step 8: 【0681】 The server receives requests for additional information from the user and performs further data analysis. If there is a detailed risk assessment or supplementary information, it is also sent back to the terminal. This process can be repeated until the user is satisfied. 【0682】 (Example 1) 【0683】 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". 【0684】 Traditional rental property search systems lacked the detailed property evaluations and risk information users needed, making efficient property selection difficult. Furthermore, obtaining up-to-date information in real time was challenging, even with data collection from multiple sources. Additionally, there was a lack of flexible, interactive features to select suitable properties based on user preferences. 【0685】 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. 【0686】 In this invention, the server includes a device for receiving user requests, a device for acquiring information from an external data source, a device for integrating the information and performing an evaluation, a device for using a generative artificial intelligence model for the evaluation, a device for visualizing and displaying the evaluation results to the user, and a program for providing the results of the property risk evaluation. This enables the user to make efficient and appropriate property selections based on detailed property evaluations and risk information. 【0687】 A "user" is an individual or corporation who wishes to search for or evaluate properties, and is the entity that enters their desired conditions. 【0688】 "Desired conditions" refer to the requirements and criteria that users look for in a rental property, and specifically include area, rent, floor plan, and age of the building. 【0689】 "Device" refers to an electronic system or instrument, and in this context, it refers to a component that has the function of receiving, processing, and outputting data. 【0690】 "Information sources" refer to external databases and websites that provide data on rental properties, and include various platforms that provide real estate information. 【0691】 "Evaluation" is the process of analyzing the value and characteristics of a property based on collected information, and then scoring or ranking it. 【0692】 A "generative artificial intelligence model" is an algorithmic structure that learns patterns from large amounts of data and uses them for evaluation and prediction. 【0693】 "Visualization" is a method of presenting data and evaluation results visually in the form of graphs, charts, and other diagrams, making them easy for users to understand. 【0694】 A "program" is a set of instructions that automatically perform evaluations or information processing on specific items, and is executed by a computer device. 【0695】 "Risk assessment" is the process of analyzing potential risks associated with a property and notifying the user. 【0696】 "Interactive format" refers to a method in which users interact with the system in a two-way manner, and it plays an important role in searching for and retrieving information. 【0697】 This invention is a system for assisting in the search and evaluation of rental properties, and mainly consists of three elements: a user, a terminal, and a server. The user first uses the terminal to input their desired conditions. These conditions include the desired area, rent range, floor plan, and age of the building. 【0698】 The terminal organizes the data entered by the user and sends it to the server. This transmission utilizes data formats such as JSON and XML for efficient data exchange. 【0699】 The server collects information from multiple data sources on the internet based on the user's desired conditions. This information collection utilizes scraping techniques and API access, enabling the acquisition of the latest property information in real time. After collection, the server integrates this data, removing redundant data and standardizing the format. 【0700】 Once data integration is complete, the server uses a generated AI model to evaluate properties. This process involves scoring each property based on criteria such as rent appropriateness, amenities, and age of the building. The results are then processed into a visually easy-to-understand format and sent to the terminal. 【0701】 The terminal displays the evaluation results received from the server to the user. This display is done through an interactive UI, supporting the user in easily comparing and considering properties. 【0702】 For example, if a user searches for a property in Tokyo with a rent of 80,000 yen or less, 2LDK layout, and built within the last 10 years, the terminal sends these conditions to the server. The server collects relevant data from various real estate information websites and uses a generated AI model to evaluate the results, presenting them to the user in the form of "Recommendation Level: High" and "Contract Risk: Medium." An example of a prompt message to be entered into this system is as follows: "Please collect and evaluate information on properties in Tokyo with a rent of 100,000 yen or less, 1LDK layout, and built within the last 5 years." In this way, users can efficiently find rental properties that closely match their preferences through this system. 【0703】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0704】 Step 1: 【0705】 Users use a terminal to input their desired conditions for rental properties. The data entered includes specific requirements such as area, rent range, floor plan, and building age. This input forms the basic dataset that is sent to the server. 【0706】 Step 2: 【0707】 The terminal receives input from the user, converts it into JSON or XML format, and packages the data. This packaged data is then sent to the server efficiently and quickly. 【0708】 Step 3: 【0709】 The server analyzes data received from the terminal and collects property information that matches the user's desired criteria. The server accesses multiple information sources through scraping and APIs to perform large-scale data collection. Desired criteria data is provided as input, and a list of highly relevant property data is obtained as output. 【0710】 Step 4: 【0711】 The server integrates the collected property data. It organizes the database by removing duplicate data and converting it to a consistent format. This operation generates a unified dataset. 【0712】 Step 5: 【0713】 The server uses a generative AI model to evaluate properties based on integrated data. Here, scoring is performed considering factors such as rent appropriateness, amenities, and age of the building. The input is an integrated and organized dataset, and the output is an evaluation result with a score for each property. 【0714】 Step 6: 【0715】 The server sends the scored evaluation results to the terminal. The evaluation results are visualized in a way that is easy for the user to understand, and are presented as graphs and tables. 【0716】 Step 7: 【0717】 The terminal receives evaluation results from the server and presents them visually to the user. Using an interactive UI, the user can compare evaluations and select the best property. 【0718】 Step 8: 【0719】 If a user requires more detailed information, they can request additional information from the server via their device. The server then collects and analyzes the requested information again and sends it back to the device. This iterative process allows the user to gain a deeper understanding of the property. 【0720】 (Application Example 1) 【0721】 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". 【0722】 The modern housing selection process presents a problem: users must spend considerable time and effort searching for properties that meet their desired criteria. Furthermore, information is generally provided in text format, making sophisticated analysis and evaluation difficult. Additionally, there are limited means for users to efficiently obtain information using voice. 【0723】 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. 【0724】 In this invention, the server includes means for receiving desired conditions from the user, means for collecting data from multiple information sources based on the desired conditions, and means for analyzing the data and evaluating properties using an evaluation algorithm. This enables the user to intuitively and efficiently select properties through voice and visual information presentation. 【0725】 A "user" is a consumer who uses a system to search for and rate property information. 【0726】 "Desired conditions" refer to the factors that users prioritize when selecting a property, and specifically include elements such as location, rent, floor plan, and age of the building. 【0727】 "Information sources" refer to various digital platforms from which property information can be obtained, including websites and databases on the internet. 【0728】 "Data" refers to all property information collected from the source, including address, rent, equipment specifications, and images. 【0729】 "Analysis" is a data processing process that uses collected data to evaluate properties that meet the conditions requested by the user. 【0730】 An "evaluation algorithm" is a computational method for quantitatively evaluating the quality and value of a property, using a generative AI model to score the reasonableness of the rent and the property's amenities. 【0731】 "Voice recognition" is a technology that interprets voice commands spoken by a user as digital data. 【0732】 "Speech synthesis" is a technology that converts text data into speech data and provides it to the user as audio information. 【0733】 "Presenting audio and visually" means providing evaluation results in a format that is easy for users to understand through both audio and visual means. 【0734】 To implement this invention, a user terminal and a server are key components. The user uses the terminal to input information about the desired property, such as location, rent, and floor plan. The terminal is responsible for transmitting this information to the server. 【0735】 Meanwhile, the server collects property data in real time from multiple sources. This collection utilizes API access using the Python Requests library and scraping techniques using BeautifulSoup to quickly obtain the necessary property information. The collected data is analyzed by a generative AI model for the evaluation algorithm, and properties are scored. This AI model uses OpenAI's GPT technology. 【0736】 The evaluation results generated by the server are provided to the user via the terminal in both audio and visual formats. The Google Speech-to-Text API is used for speech recognition, and existing text-to-speech technologies are used for speech synthesis. This makes it easier for users to intuitively understand the evaluation results. 【0737】 For example, if a user verbally requests, "I'd like a 2LDK apartment in Tokyo where I can live with my pet, with a rent of 150,000 yen or less," the server will select properties that meet the criteria and provide voice guidance such as, "In this area, we recommend a pet-friendly property with a rent of 140,000 yen," while also displaying the property's score and detailed information on the screen. An example of a prompt message would be, "Evaluate the property information based on the conditions specified by the user and suggest a suitable property." 【0738】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0739】 Step 1: 【0740】 The user inputs their desired property conditions by voice using a terminal. The terminal converts the voice data into text data using voice recognition software and sends it to the server as the received desired conditions. In this process, the input is the user's voice data, and the output is the desired conditions in text format. 【0741】 Step 2: 【0742】 The server collects property data from multiple sources on the internet based on the received request criteria. It uses API access via the Python Requests library and scraping techniques with BeautifulSoup. The input is property criteria in text format, and the output is a set of collected property data. 【0743】 Step 3: 【0744】 The server analyzes the collected property data. Using a generative AI model, it applies a property evaluation algorithm and scores each property. The input is a property dataset, and the output is a list of scores for each property. This identifies the property that best matches the user's desired conditions. 【0745】 Step 4: 【0746】 The server sends the scoring results to the terminal. The terminal presents this information to the user through a visual display and audio output using speech synthesis technology. The input is the scoring results, and the output is the visual and audio presentation to the user. 【0747】 Step 5: 【0748】 Users can review properties based on the provided information and request additional information as needed. The terminal resends this request to the server, which then performs further data collection and analysis. The input is the user's request for additional information, and the output is the updated property details. 【0749】 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. 【0750】 This invention relates to a system that integrates an emotion engine that reflects the user's emotions into the rental property search and evaluation process. This system consists of four main components: the user, the terminal, the server, and the emotion engine. 【0751】 The user first launches the property search application using their terminal and enters their desired property criteria. These criteria include specific requirements such as location, rent range, floor plan, and age of the building. The terminal receives the user's input and prepares to send that information to the server. 【0752】 The server collects property information from multiple sources on the internet based on the desired conditions received from the terminal. This process involves obtaining accurate and up-to-date information through scraping and API access. Before passing the collected data to the sentiment engine, the server inputs it into an automated analysis system, where a generative AI model is used to evaluate the properties. This evaluation considers factors such as market reasonableness of rent, property amenities, and age of the building. 【0753】 The emotion engine acquires and analyzes emotional data from user interactions, input, voice, and facial expressions. The server integrates this emotional data with property evaluation results and adjusts the information presented according to the user's emotional state. This allows the system to provide information tailored to the user's preferences and stress level at the optimal time. 【0754】 The terminal displays sentiment-based evaluation results received from the server to the user. The information is visually organized and presented in a user-friendly format, making decision-making easier. For example, the terminal could display "Property A: Recommendation Level: High" and "Sentiment-Based Recommendation: Provides a sense of security," allowing the user to confidently select a property. 【0755】 Users can compare properties based on the information provided and make the most appropriate choice. Furthermore, if the user requests more detailed information, the device will query the server again to provide the necessary additional information. This process allows users to thoroughly consider properties until they are satisfied. The introduction of an emotion engine improves the recommendation accuracy and usability of traditional property search systems, providing a more personalized experience for individual users. 【0756】 The following describes the processing flow. 【0757】 Step 1: 【0758】 The user accesses the terminal and opens the property search application. They enter their desired property criteria, such as area, rent range, floor plan, and year of construction. The terminal temporarily stores this input data and prepares to send it. 【0759】 Step 2: 【0760】 The terminal sends the entered desired conditions to the server. The server then identifies the search conditions and receives the information needed to begin the data collection process. 【0761】 Step 3: 【0762】 The server accesses multiple real estate information sources based on the received preferences. It uses APIs and web scraping techniques to collect relevant property information. The server stores the collected data in a temporary database. 【0763】 Step 4: 【0764】 The server passes the stored property data to a generating AI model for analysis. This analysis evaluates factors such as the reasonableness of the rent, the property's facilities, and its age, and assigns a score to each property. 【0765】 Step 5: 【0766】 The device simultaneously activates an emotion engine to recognize the user's emotions. It analyzes the user's input and reactions during operation to generate emotion data. For example, it measures the speed of input and the time taken to make selections to infer the user's interests and anxieties. 【0767】 Step 6: 【0768】 The emotional data obtained by the emotion engine is sent to the server. Based on this, the server adjusts the property evaluation results based on the user's emotional state. This makes it possible to suggest properties that take the user's emotions into consideration. 【0769】 Step 7: 【0770】 The server returns the adjusted evaluation results to the terminal. The terminal displays the evaluation results to the user in a visually organized format. The information is structured to aid user understanding and support decision-making. 【0771】 Step 8: 【0772】 Users compare properties based on the information presented and make their selection. By referring to the displayed sentiment-based recommendations and risk assessments, they can make a more informed choice. 【0773】 Step 9: 【0774】 If a user desires further details, they can request additional information through their device. The server analyzes the detailed data based on this request, taking into account the user's sentiment data, and provides additional information. This iterative process allows users to consider properties until they are satisfied. 【0775】 (Example 2) 【0776】 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". 【0777】 Traditional property search systems have the problem of presenting uniform information without considering the user's emotional state, making it difficult to alleviate the stress and anxiety they cause. Furthermore, common information formats often lack sufficient personalization to accommodate individual preferences and emotions. 【0778】 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. 【0779】 In this invention, the server includes a device for inputting search criteria from the user, a device for acquiring information from multiple information sources based on the search criteria, a device for analyzing the information and evaluating the target, a device for introducing the evaluation results into a generating AI model and integrating it with the user's emotional data, and a device for presenting the integrated information to the user. This makes it possible to provide information that corresponds to the user's emotional state. 【0780】 A "device for users to input search criteria" is a device that provides an interface for users to specify their desired conditions to the system and for those conditions to be treated as data. 【0781】 A "device that acquires information from multiple sources" is a device that collects necessary data from various sources, such as the internet and databases. 【0782】 A "device for evaluating an object" is a device that has the function of evaluating an object according to certain criteria based on acquired information and outputting the evaluation results. 【0783】 A "device for integrating user sentiment data into a generative AI model" is a device that inputs evaluation results into a generative model and adjusts and integrates those results while taking user sentiment data into consideration. 【0784】 A "device that presents integrated information to the user" is a device that displays processed evaluation and adjustment results in a format that is easy for the user to understand. 【0785】 This invention is a system that enables users to obtain property information based on their desired conditions during the real estate search process, and further provides information according to the user's emotional state. A specific embodiment of this system is shown below. 【0786】 The user launches a property search application using their device. Here, the user enters search criteria such as location, rent, floor plan, and year of construction. The device receives this information and sends it to the server via the network. 【0787】 The server collects property information from multiple sources on the internet based on search criteria sent from the terminal. Web scraping techniques and public APIs are used as collection methods. This allows the server to obtain the latest and most accurate information and aggregate it into a database. 【0788】 Next, the server inputs the aggregated information into a generating AI model. This model evaluates the property, assessing it from multiple perspectives, including the appropriateness of the rent, the quality of the facilities, and the age of the building. 【0789】 Furthermore, the server uses an emotion engine to analyze emotional data obtained from the user. This data is collected from user input, voice, facial expressions, and other sources. The server integrates and adjusts this emotional data with the property evaluation results to generate information that is optimal for the user's emotional state. 【0790】 The terminal receives evaluation results sent from the server and displays the information to the user in a visually organized format. This allows the user to make more rational decisions. For example, the terminal might display information such as "Property A: Recommendation Level: High, Emotional Recommendation: Provides a sense of security." 【0791】 For example, if a user specifies search criteria such as "Tokyo, 2LDK, under 100,000 yen, built within the last 10 years," the system will present a list of properties matching these criteria, along with sentiment ratings. This allows the user to smoothly make the best choice based on this information. 【0792】 This system breaks away from the uniformity of information in conventional property searches and enables the provision of customized information that resonates with the user's emotions. 【0793】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0794】 Step 1: 【0795】 The user launches a property search application on their device and enters their search criteria. This information includes location, rent, floor plan, and year of construction. This data is converted into a digital format within the device, preparing it for further processing. The output of this process is formatted search criteria data. 【0796】 Step 2: 【0797】 The terminal sends search criteria data obtained from the user to the server via the network. This process includes preparing the data for transmission, encoding it, and converting it into network packets. This allows the server to analyze the data. The output of this step is data formatted for the server to receive. 【0798】 Step 3: 【0799】 The server collects property information from multiple databases on the internet based on the search criteria received from the terminal. This collection utilizes web scraping and API access to retrieve the latest information in real time. The input is the search criteria, and the output is a collection of relevant property information. 【0800】 Step 4: 【0801】 The server analyzes the collected property information. Using a generative AI model, it evaluates each property from perspectives such as market value, facilities, and age. This evaluation allows for the quantification of the property's attractiveness and value. The input is the collected property information, and the output is a dataset of evaluation results. 【0802】 Step 5: 【0803】 The emotion engine analyzes user emotional data. It analyzes the user's emotional state from voice, facial expressions, and input data obtained from the device, and determines how information should be presented. The input is raw data about the user's emotions, and the output is analyzed emotion evaluation data. 【0804】 Step 6: 【0805】 The server integrates property evaluation results with analyzed sentiment evaluation data. It adjusts the property recommendation level according to the user's emotional state, generating customized information. This integration enables the provision of information that aligns with the user's emotions. The output is the integrated evaluation information. 【0806】 Step 7: 【0807】 The terminal receives customized evaluation information sent from the server and displays it to the user. The display is in an easy-to-understand format to assist the user in making decisions. The input is integrated evaluation information from the server, and the output is visual information presented to the user. 【0808】 Step 8: 【0809】 The user compares and selects properties based on the information presented. If necessary, they request further details and make additional inquiries to the server via their terminal. This allows the user to obtain sufficient information to make an informed decision. The input is the displayed property information, and the output is the user's selection result. 【0810】 (Application Example 2) 【0811】 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". 【0812】 Traditional property search systems often present information without considering the user's emotional state, resulting in stressful information being presented or information being displayed at inappropriate times. Furthermore, the lack of personalized recommendations tailored to individual users resulted in poor usability. 【0813】 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. 【0814】 In this invention, the server includes means for analyzing the user's emotions, means for adjusting the presentation of information based on the results of the emotion analysis, and means for providing additional information to the user in an interactive format. This enables the provision of information at the optimal timing according to the user's emotions and improves usability through high personalization. 【0815】 A "user" is an entity that uses the system to input desired conditions and participates in the search and evaluation of properties. 【0816】 "Desired conditions" refer to the specific requirements that users set when searching for a property, such as location, rent, floor plan, and age of the building. 【0817】 "Device" refers to a general term for equipment and programs used within a system as a means of inputting, collecting, analyzing, and presenting information. 【0818】 "Information sources" refer to multiple data providers on the internet that are accessed to collect property information. 【0819】 "Information" refers to detailed data about a property that is analyzed based on collected data. 【0820】 "Evaluation" is the process of determining the value and suitability of a property based on the information gathered about it. 【0821】 "Presentation" refers to the act of providing the user with the results of the system's analysis and evaluation, either visually or audibly. 【0822】 "Emotions" represent the user's mental state and are data obtained from the user's facial expressions, voice, and input interactions. 【0823】 "Analysis" is the process of analyzing collected information and emotional data to generate meaningful evaluation results. 【0824】 "Adjustment" is the process of optimizing the content and timing of information presented based on the results of the user's sentiment analysis. 【0825】 "Dialogue format" refers to a method of interactive information exchange between the user and the system. 【0826】 This invention provides a specific embodiment of a system for searching and evaluating property information based on user emotions. The system mainly consists of a user terminal, a server, an emotion analysis device, and an information presentation device. 【0827】 The user launches a property search application using their device and enters their desired property criteria. The device has the function of sending the user's desired criteria to the server. 【0828】 The server collects property data from multiple sources based on the received conditions. This information is obtained through internet databases and APIs. The server analyzes this information and generates property evaluations using an AI model. 【0829】 The emotion analysis device acquires emotional data such as the user's facial expressions and voice, and analyzes their emotional state using a cloud-based emotion analysis API (for example, Azure Emotion API). The analysis results are sent to a server, where the emotional data is integrated into the property evaluation results. 【0830】 This integrated information is displayed on the user's terminal via an information display device. The terminal then presents the user with property information best suited to their emotional evaluation. For example, if the user indicates a desire for a sense of security, the system can provide information in the format of "Property A: Recommendation Level: High, Provides a sense of security." 【0831】 Through this process, users can make more informed decisions when selecting a property. Furthermore, the interactive features provided by the system allow users to easily obtain additional information and conduct more in-depth comparisons. 【0832】 Examples of prompt statements for generative AI models are as follows: 【0833】 "Please display a list of recommended products for users when they are having fun." 【0834】 "Please tell us about products that help users relax when they are feeling stressed." 【0835】 In this way, by utilizing sentiment analysis to provide information tailored to the user's preferences and emotions, highly personalized property selection support can be achieved. 【0836】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0837】 Step 1: 【0838】 The user operates the terminal to launch the property search application and enters the desired property criteria (area, rent, floor plan, year built, etc.). The entered criteria are formatted into a structured data format within the terminal and prepared for transmission to the server. 【0839】 Step 2: 【0840】 The server uses the desired conditions received from the terminal to collect property data from multiple sources on the internet. Specifically, it obtains information that matches the conditions through a property information database and external APIs. In doing so, it utilizes scraping techniques and API access to collect the latest and most accurate data, which is then stored in an internal database. 【0841】 Step 3: 【0842】 The server uses a generative AI model to evaluate properties based on collected property data. The AI ​​model calculates a score for each property using a dataset that includes factors such as market price reasonableness, property amenities, and age. This evaluation result is then passed on to the next process. 【0843】 Step 4: 【0844】 The emotion analysis device collects user facial expression data and voice input and sends it to a server. Specifically, it acquires data from the device's camera and microphone, and this data is processed by an emotion analysis API (e.g., Azure Emotion API) to generate data indicating emotions. 【0845】 Step 5: 【0846】 The server adjusts property evaluation results based on sentiment analysis. If the user's emotional state is positive, it makes specific adjustments, such as setting a higher recommendation level. By applying emotion-based filtering and ranking, it creates information optimized for each individual user. 【0847】 Step 6: 【0848】 The integrated evaluation information sent from the server is presented to the terminal. Specifically, the terminal displays property information in a visually easy-to-understand format. Property details and recommendation levels are displayed at a time and in a format that is easy for the user to accept, helping them make a selection. 【0849】 Step 7: 【0850】 Users can compare properties based on the information displayed on their device and select the most suitable one. If they require further details, they can query the server again to obtain additional information. This allows users to thoroughly consider properties until they are satisfied. 【0851】 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. 【0852】 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. 【0853】 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. 【0854】 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. 【0855】 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. 【0856】 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. 【0857】 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. 【0858】 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. 【0859】 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." 【0860】 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. 【0861】 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. 【0862】 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. 【0863】 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. 【0864】 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. 【0865】 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. 【0866】 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. 【0867】 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. 【0868】 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. 【0869】 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. 【0870】 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. 【0871】 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 as being incorporated by reference. 【0872】 The following is further disclosed regarding the embodiments described above. 【0873】 (Claim 1) 【0874】 A means for users to input their desired conditions, 【0875】 A means for collecting data from multiple sources based on the aforementioned desired conditions, 【0876】 A means for analyzing the aforementioned data and evaluating the property, 【0877】 A means for presenting the aforementioned evaluation results to the user, 【0878】 A system that includes this. 【0879】 (Claim 2) 【0880】 The system according to claim 1, further comprising means for providing a user with a property risk assessment. 【0881】 (Claim 3) 【0882】 The system according to claim 1, further comprising means for providing additional information to the user in an interactive manner. 【0883】 "Example 1" 【0884】 (Claim 1) 【0885】 A device for receiving user requests and conditions, 【0886】 A device that acquires information from an external data source based on the aforementioned desired conditions, 【0887】 A device that integrates the aforementioned information and performs an evaluation, 【0888】 A device that uses a generative artificial intelligence model for evaluation, 【0889】 A device that visualizes and displays the evaluation results to the user, 【0890】 A system that includes this. 【0891】 (Claim 2) 【0892】 The system according to claim 1, comprising a program for providing the results of a property risk assessment. 【0893】 (Claim 3) 【0894】 The system according to claim 1, further comprising a device for interactively acquiring additional information in response to user requests. 【0895】 "Application Example 1" 【0896】 (Claim 1) 【0897】 A means for users to input their desired conditions, 【0898】 A means for collecting data from multiple sources based on the aforementioned desired conditions, 【0899】 A means for analyzing the aforementioned data and evaluating the property using an evaluation algorithm, 【0900】 Means for presenting the aforementioned evaluation results to the user audibly and visually, 【0901】 A means for performing speech recognition and speech synthesis to analyze user voice commands and generate responses, 【0902】 A system that includes this. 【0903】 (Claim 2) 【0904】 The system according to claim 1, further comprising means for providing a user with a property risk assessment. 【0905】 (Claim 3) 【0906】 The system according to claim 1, further comprising means for providing additional information to the user in an interactive manner and updating property conditions based on the interaction. 【0907】 "Example 2 of combining an emotion engine" 【0908】 (Claim 1) 【0909】 A device for users to input search criteria, 【0910】 A device that acquires information from multiple information sources based on the aforementioned search conditions, 【0911】 A device that analyzes the aforementioned information and evaluates the target, 【0912】 A device that incorporates evaluation results into a generating AI model and integrates them with user emotion data, 【0913】 A device that presents the aforementioned integrated information to the user, 【0914】 A system that includes this. 【0915】 (Claim 2) 【0916】 The system according to claim 1, further comprising a device that provides the user with adjusted evaluation information based on their emotional state. 【0917】 (Claim 3) 【0918】 The system according to claim 1, further comprising a device for providing additional information to the user in an interactive manner. 【0919】 "Application example 2 when combining with an emotional engine" 【0920】 (Claim 1) 【0921】 A device for users to input their desired conditions, 【0922】 A device for collecting information from multiple information sources based on the aforementioned desired conditions, 【0923】 A device that analyzes the aforementioned information and evaluates the property, 【0924】 A device for presenting the evaluation results to the user, 【0925】 A device for analyzing user emotions, 【0926】 A device that adjusts the presentation of information based on the aforementioned emotion analysis results, 【0927】 A system that includes this. 【0928】 (Claim 2) 【0929】 The system according to claim 1, further comprising a device for providing a user with a property risk assessment. 【0930】 (Claim 3) 【0931】 The system according to claim 1, further comprising a device for providing additional information to the user in an interactive manner. [Explanation of symbols] 【0932】 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

[Claim 1] A means for users to input their desired conditions, A means for collecting data from multiple sources based on the aforementioned desired conditions, A means for analyzing the aforementioned data and evaluating the property, A means for presenting the aforementioned evaluation results to the user, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for providing a user with a property risk assessment. [Claim 3] The system according to claim 1, further comprising means for providing additional information to the user in an interactive manner.

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