system

Abstract

We provide the system. [Solution] An input method for receiving information from the user, A storage means for saving the input information as data, An analysis means that analyzes stored data and generates suggestions that respond to user requests, An output means for providing the generated suggestions 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, and includes 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 as a 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】 Preparations for a wedding have a number of adjustment matters, and there is a problem that it is particularly burdensome for busy couples. Also, due to the variety of elements to be considered during the preparation process, there is a tendency to consume a large amount of time and labor. As a result, the number of couples who cancel their weddings is increasing, and there is a risk of leading to a shrinkage of the bridal industry, which is also cited as an issue. 【Means for Solving the Problems】 【0005】 This invention solves the above problems by providing a system that inputs information from users, stores and analyzes it as data, and generates and provides suggestions. Specifically, it streamlines various wedding preparation tasks by including an analysis means that automatically generates suggestions according to the user's preferences and requests. Furthermore, by providing a means for re-analyzing the suggestions based on user feedback, it supports fine-tuning and reduces the burden on the user. 【0006】 A "user" refers to a person or couple who uses the system to prepare for their wedding. 【0007】 "Input means" refers to interfaces or devices that allow users to provide necessary information to the system. 【0008】 "Storage means" refers to an element that has the function of recording and retaining information entered by the user in data format. 【0009】 "Analysis means" refers to a function that processes data to create suggestions tailored to the user's requests and preferences based on the stored data. 【0010】 "Output means" refers to devices or interfaces used to communicate the suggestions generated as a result of the analysis to the user. 【0011】 "Suggestions" refer to the options and plans that the system automatically generates for elements related to wedding preparations (e.g., attire, invitations, seating charts, etc.). 【0012】 "Feedback" refers to the responses and opinions that users provide to a proposal, and the system uses this feedback to readjust the proposal. 【0013】 "Re-analysis" refers to the process of re-analyzing and adjusting previously generated suggestions based on user feedback. [Brief explanation of the drawing] 【0014】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【MODE FOR CARRYING OUT THE INVENTION】 【0015】 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. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 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." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 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. 【0025】 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). 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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". 【0035】 The system implementing this invention is equipped with a generative AI designed to efficiently carry out wedding preparations. Below, an embodiment of the system and the processing flow of its program are described in natural language. 【0036】 User information input and data collection 【0037】 Users can input wedding-related information in a questionnaire format using devices such as smartphones and PCs. This information includes guest lists, wedding concepts, and preferred styles. This input information is transmitted from the device to a server via the internet and securely recorded by storage devices. 【0038】 Data analysis and proposal generation 【0039】 The server uses stored data to perform analysis. This analysis utilizes AI to analyze user input and automatically generates suggestions across multiple elements, such as costume recommendations, invitation designs, venue layouts, and background music selections. These suggestions are individually adjusted and optimized according to the user's preferences. 【0040】 Proposal submission and feedback reception 【0041】 The generated proposals are provided to the user via an output device. The user can review the proposals on their device and provide feedback on each element, offering opinions and requests. This feedback is further incorporated by a re-analysis device, and the server readjusts the proposals. Through this process, an optimal wedding plan that more closely matches the user's wishes is created. 【0042】 Specific example 【0043】 For example, if a user desires a "warm atmosphere incorporating the beauty of autumn nature," the system can suggest invitation designs with corresponding color schemes and present venue layouts using natural floral arrangements and wooden decorations. Furthermore, the system can automatically adjust meal plans, including vegetarian options, to suit the preferences of specific guests. 【0044】 In this way, this system highly automates various wedding preparations, allowing users to plan and execute their ideal wedding without feeling burdened by their busy daily lives. 【0045】 The following describes the processing flow. 【0046】 Step 1: 【0047】 Users access the survey form via their device and enter the required information. Specifically, they enter the date of the ceremony, guest list, concept, preferred colors and style, etc. 【0048】 Step 2: 【0049】 The terminal sends the entered information to the server. The transmitted data is stored in a database on the server and prepared for subsequent processing. 【0050】 Step 3: 【0051】 The server analyzes the received data and generates AI-generated suggestions based on the user's preferences and wedding concept. This analysis includes multiple elements such as attire, invitations, venue layout, and background music. 【0052】 Step 4: 【0053】 The server sends the generated suggestions to the user's device. The user then reviews these suggestions on their device and checks whether they match their preferences. 【0054】 Step 5: 【0055】 Users provide feedback on the proposal. This feedback can include specific requests, such as design changes or preferred options. 【0056】 Step 6: 【0057】 The server re-analyzes the data based on user feedback and adjusts the proposal. This re-analysis generates a final plan that reflects the user's requests. 【0058】 Step 7: 【0059】 The final proposal is sent to the terminal for the user to review and approve. If the user is satisfied at this step, the system proceeds to execute the necessary orders and preparations. 【0060】 (Example 1) 【0061】 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." 【0062】 In modern society, wedding preparations require a great deal of time and effort, and it is difficult to create the optimal plan from among many options. Therefore, there is a need for an efficient system that can meet the diverse and individual needs of various users. 【0063】 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. 【0064】 In this invention, the server includes a user input device, a storage device for storing the input information as an information set, and an analysis device for processing the recorded information and automatically generating suggestions that respond to the user's requests. This enables the automation, proposal, and optimization of appropriate wedding plans tailored to the individual user's wishes. 【0065】 "User device" refers to a device used by a user to input information, such as a smartphone or PC. 【0066】 A "storage device" is a device for storing input information as a collection of information, and typically uses a database to manage this information. 【0067】 An "analysis device" is a device that processes recorded information and automatically generates suggestions that respond to user requests, using machine learning algorithms to analyze data. 【0068】 A "providing device" is a device that provides the generated proposal to the user, and typically transmits the information via the internet so that the user can confirm it. 【0069】 A "re-analysis device" is a device used to adjust the proposed content based on the responses received from users, and it optimizes the proposal by analyzing the feedback. 【0070】 A "portable device" is a terminal that a user can carry with them, and this mainly includes smartphones and tablets. 【0071】 A "generative AI model" is an artificial intelligence model that analyzes data based on machine learning algorithms to generate and optimize suggestions. 【0072】 The system for implementing the invention is an information processing system designed to streamline the wedding planning process. The specific form of this system is described below. 【0073】 Users input wedding-related information using devices such as smartphones or PCs. These devices transmit this input information to a server via the internet. The server uses a database management system (DBMS) to securely record the received information for data storage. 【0074】 The server utilizes a generative AI model to analyze the recorded data. This AI model uses machine learning libraries such as TENSORFLOW® and PyTorch to analyze user preferences and trends. Based on the analysis results, the server automatically generates various suggestions related to weddings. These suggestions include choices for attire, invitation designs, venue layouts, and background music selections. 【0075】 For example, if a user requests a "warm atmosphere incorporating the beauty of autumn nature," the server will propose a design that takes this request into account. A specific example of a prompt would be: "We are planning a wedding with a warm atmosphere incorporating the beauty of autumn nature. Please propose a plan that will satisfy our guests, using natural floral arrangements and wooden decorations, and including a vegetarian menu." 【0076】 This allows the server to provide users with their ideal wedding plan while optimizing the planning process with minimal effort. Users can efficiently create and optimize their plans without feeling burdened by their busy schedules. 【0077】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0078】 Step 1: 【0079】 Users input wedding-related information using devices such as smartphones and PCs. This information includes guest lists, wedding themes, and preferred styles. The entered data is sent to a server via the internet. Specifically, information is sent by operating the user interface on the device's form and pressing the "Submit" button. Input consists of options selected by the user, and output is the transfer of data to the server. 【0080】 Step 2: 【0081】 The server stores information received from the terminal using a database management system (DBMS). Here, data is securely recorded and managed. The server parses the received data in JSON format and stores the information in the appropriate tables. The input is data in JSON format, and the output is structured database entries. 【0082】 Step 3: 【0083】 The server utilizes a generative AI model to analyze the stored data. This involves using machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. This analysis generates feature vectors and automatically produces diverse suggestions through pattern matching. The input is structured data stored in a database, and the output is automatically generated wedding plan suggestions. 【0084】 Step 4: 【0085】 The server converts the generated proposals into HTML or PDF format and sends them to the terminal to provide them to the user. The terminal receives these and displays them in a format that the user can review. Specifically, the user can review each proposal by displaying the data from the server in a browser or PDF viewer. The input is proposal data generated by an AI model, and the output is a visually presented plan. 【0086】 Step 5: 【0087】 The user sends feedback on the proposal to the server via their device. The server incorporates this feedback using a re-analysis mechanism and readjusts the proposal. This results in the provision of an optimal proposal that reflects the user's opinion. Specifically, the process is completed by entering feedback using the feedback form on the device and pressing the "Send" button again. The input is the user's feedback information, and the output is the improved proposal data. 【0088】 (Application Example 1) 【0089】 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." 【0090】 Currently, wedding planning involves many steps, requiring users to invest a significant amount of time and effort. Furthermore, the difficulty in visualizing proposals makes it challenging for users to fully understand and make informed decisions. Additionally, there is a need to quickly and efficiently incorporate user feedback. A method is needed to address these challenges and enable user-friendly, intuitive planning by utilizing a virtual reality environment. 【0091】 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. 【0092】 In this invention, the server includes acquisition means for obtaining information from the user, storage means for storing the acquired information as data, analysis means for analyzing the stored data and creating suggestions based on the user's requests, display means for providing a virtual reality environment, detection means for detecting the user's actions within the virtual reality environment, and collection means for collecting feedback through the virtual reality environment. This allows the user to visually experience the suggested content using the virtual reality environment and provide rapid feedback. The user's feedback is immediately reflected in the suggestions, enabling more personalized wedding planning. 【0093】 "Means of acquisition" refers to the part equipped with functions for collecting information from users. 【0094】 A "storage mechanism" is a system for safely and efficiently storing collected data. 【0095】 "Analysis means" refers to a method for analyzing stored data and generating suggestions that meet user requirements. 【0096】 A "display means" is a device that allows a user to access a virtual reality environment and visually confirm the proposed content. 【0097】 "Detection means" refers to technologies for identifying user actions and operations within a virtual reality environment. 【0098】 "Methods of data collection" refers to methods for obtaining user feedback and using that feedback to improve the proposed content. 【0099】 The system implementing this invention is designed to efficiently carry out wedding preparations in a virtual reality environment. Users can input wedding-related information as data using their own devices and visually confirm the plan generated through the virtual environment. 【0100】 The server uses acquisition means to obtain information from the user. The acquired information is securely stored by retention means. The stored data is analyzed using analysis means, and specific suggestions based on the user's requests are generated by a generative AI model. For example, based on the wedding theme and guest list, optimal venue design, decoration plan, and catering plan are proposed. 【0101】 Users can experience these suggestions within a virtual reality environment via display means and directly manipulate the visualized results in the virtual space. The system uses detection means to identify user actions and operations, enabling real-time interaction within the virtual environment. User feedback is collected by collection means and immediately used to readjust the suggestions. 【0102】 The hardware used includes VR head-mounted displays and high-spec PCs, while the software utilizes Unity (game engine), Python, and TensorFlow. This allows users to intuitively understand and customize the overall picture of their wedding through an immersive experience. 【0103】 For example, if a user requests a wedding with a "warm atmosphere themed around autumn nature," the generating AI model will suggest venue color schemes and material selections accordingly. The user can then review the plan presented in virtual reality and provide feedback such as, "I'd like to change this material to something else." 【0104】 An example of a prompt to input into the generating AI model would be: "Please suggest relevant color schemes and materials so that the user can experience a wedding venue decoration design themed around autumn nature in VR. Also, update it immediately based on any changes in feedback." 【0105】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0106】 Step 1: 【0107】 The user enters wedding-related information via a terminal. This input data includes the number of guests, the wedding theme, and preferred style. This information is transmitted from the terminal to the server via a data acquisition method. The data obtained from the input is then pre-formatted for storage. 【0108】 Step 2: 【0109】 The server stores the acquired user information in cloud storage using a retention mechanism. During storage, the data is encrypted or compressed as needed. The stored information is saved in a structured format so that it can be used for later analysis. 【0110】 Step 3: 【0111】 Based on the stored data, the server performs data analysis using Python and TensorFlow scripts as analytical tools. This allows the generative AI model to generate appropriate wedding plans. The analysis process outputs suggestions that reflect the user's preferences. 【0112】 Step 4: 【0113】 The server provides the generated proposals to the user through a display mechanism. Specifically, a VR environment is built using the Unity engine, and the proposed wedding designs and layouts are visually displayed within it. The user views this through a head-mounted display. 【0114】 Step 5: 【0115】 Users try out the displayed virtual reality suggestions and provide feedback. This feedback is recorded by detection devices that track actions within the virtual environment and directly input from the user into a data collection system. This feedback clarifies requests and opinions regarding the suggestions. 【0116】 Step 6: 【0117】 The server re-analyzes the feedback collected from users and generates new suggestions. The re-analysis process processes the data according to the user's requested changes, leading to the optimal suggestion. As a result, a more satisfying plan is provided to the user. 【0118】 Step 7: 【0119】 Finally, the refined proposal is presented to the user for approval. The approved plan is then output as a detailed plan for implementation. This prepares the user to concretely carry out their planned wedding. 【0120】 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. 【0121】 The system in this invention is a wedding preparation support system that incorporates an emotion engine that recognizes the user's emotions. The following describes in detail how this system is implemented. 【0122】 System Configuration 【0123】 The system has a complex structure that includes a user terminal, a server, and an emotion engine. The user uses the terminal to input information necessary for their wedding and communicates their requests and preferences in a questionnaire format. The emotion engine analyzes the user's facial expressions, tone of voice, and word choice during input and when reviewing suggestions to identify their emotions. This emotion information is transferred to the server and used by the analysis system. 【0124】 Program processing 【0125】 The server analyzes the user's input data, including emotional information received from the emotion engine. The analysis then works to generate more effective and appropriate suggestions based on the user's emotions. For example, if the user is showing tension or anxiety, the suggestions will be adjusted to be more reassuring or include approaches to reduce stress. 【0126】 The generated suggestions are sent to the user's device, where the user can review them. A re-analysis mechanism is used to dynamically adjust the suggestions, taking into account user feedback and associated emotional information. This allows for further fine-tuning based on the emotional state the user expressed in response to the suggestions. 【0127】 Specific example 【0128】 For example, if a user enters that they want a wedding that is "glamorous yet calming," the emotion engine will detect the user's subtle emotional response. If it recognizes that the user felt excited by a particular floral design, the server will generate suggestions that reflect that. On the other hand, if the user expresses anxiety about the background music suggestions, the system will add more relaxing music options to the list. 【0129】 In this way, the system, incorporating an emotion engine, provides an ideal wedding preparation process while being attentive to the user's emotions. Users receive more personalized support and, as a result, achieve a high level of satisfaction. 【0130】 The following describes the processing flow. 【0131】 Step 1: 【0132】 Users access the system through their devices and input personal information and wedding preferences in a questionnaire format. During this process, the device's camera and microphone are used to record the user's facial expressions and voice while they are inputting the information. 【0133】 Step 2: 【0134】 The device sends survey responses and recorded sentiment data to the server. The transmitted data is stored on the server as a dataset containing the user's basic information and sentiment. 【0135】 Step 3: 【0136】 The server analyzes the received data, and the emotion engine analyzes the user's facial expressions and tone of voice to determine their emotional state. For example, if the user is smiling, it identifies feelings such as joy, and if they are frowning, it identifies feelings such as dissatisfaction. 【0137】 Step 4: 【0138】 The analysis tool combines user preferences and emotional information to generate suggestions. For example, if a user expresses delight with a floral arrangement design, suggestions centered around that design will be generated. 【0139】 Step 5: 【0140】 The server generates suggestions and sends them to the terminal, presenting the suggestions to the user. The user reviews these suggestions through the terminal, and their emotional response to each suggestion is recorded again. 【0141】 Step 6: 【0142】 Users provide feedback on the proposal, and emotional information is sent from their device. This feedback includes specific requests and suggestions for changes. 【0143】 Step 7: 【0144】 The server's re-analysis mechanism adjusts suggestions based on the latest sentiment information and feedback. The adjusted suggestions are then regenerated to be in a format that best satisfies the user. 【0145】 Step 8: 【0146】 The finalized proposal is sent to the user's device for review and approval. Once approved, the necessary orders and reservations for wedding preparations are automatically arranged. 【0147】 (Example 2) 【0148】 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." 【0149】 In wedding planning, there is a lack of personalized suggestions that take into account the user's emotions. Therefore, there is a need for methodologies that can provide ideal wedding plans while reducing the anxiety and stress that users experience. 【0150】 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. 【0151】 In this invention, the server includes means for inputting information from the user and analyzing emotional information, means for storing the input information and emotional information, and means for analyzing the stored data and generating suggestions based on the user's emotions. This makes it possible to provide the user with a personalized wedding plan that is sensitive to their emotions. 【0152】 An "input method" is a means that has the ability to receive information related to weddings from users and analyze it, including emotional information. 【0153】 "Information storage means" refers to means of appropriately storing user input information and emotional information, and maintaining a state in which it can be used for subsequent analysis and suggestion generation. 【0154】 "Analysis means" refers to the means of performing the necessary processing to generate optimal wedding proposals based on stored user information and emotional data. 【0155】 "Output means" refers to means that have the function of providing the generated wedding proposals to the user and collecting feedback from the user. 【0156】 "Transmission means" refers to a means for effectively transmitting multiple suggestions generated by the analysis means to the user's terminal. 【0157】 A "re-analysis method" is a means of re-evaluating a proposal based on user feedback and emotional information, and processing it to make adjustments as necessary. 【0158】 The embodiment of this invention aims to assist in wedding preparations while taking the user's emotions into consideration. The system comprises a server, a terminal, and an emotion engine. The user inputs wedding information via the terminal, and based on this, the system provides personalized suggestions. 【0159】 The server uses Python-based natural language processing and machine learning models to process the input user data and sentiment information. Data analysis libraries such as TensorFlow and Pandas are used for processing. The sentiment engine is used to analyze facial expressions and voice tone, thereby detecting the user's subtle emotional state. 【0160】 For example, if a user inputs that they want a wedding with a "calm atmosphere," the emotion engine analyzes how the user feels about a particular piece of music. If, for instance, it detects that the user is feeling anxious while listening to a specific piece of background music, the server will select more relaxing music and add it to the suggestions. 【0161】 As an example of a prompt, you could input something like, "Generate a relaxing wedding plan based on the user's emotions," into the generation AI model to more effectively customize the suggestions. 【0162】 This technology allows users to receive wedding plans tailored to their individual emotional needs, enabling a high-quality and satisfying experience. 【0163】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0164】 Step 1: 【0165】 The user enters information. The user uses a device to enter their wishes and requests regarding the wedding. The information entered includes the theme, number of participants, budget, etc. The device receives this information, and an emotion engine analyzes the user's facial expressions and voice in real time, sending the emotion data to the server. 【0166】 Step 2: 【0167】 The server receives and stores the data. The server records the input information and sentiment data sent by the user and stores it appropriately using information storage means. This data is used as foundational data necessary for subsequent suggestion generation. 【0168】 Step 3: 【0169】 The server analyzes the data. Using analytical tools, the server performs a detailed analysis of stored user information and sentiment data. In this process, TensorFlow and Pandas in Python are used to identify data relationships and user sentiment tendencies, and the data is processed to generate optimal suggestions. The output consists of parameters and conditions used by the generative AI model. 【0170】 Step 4: 【0171】 The server generates proposals. Based on the analysis results, a generation AI model is used to generate wedding plans that match the user's emotions and desires. At this time, a prompt such as "Generate proposals for a relaxing wedding" is input to the AI ​​model. The generated proposals are the specific plans presented to the user. 【0172】 Step 5: 【0173】 Users review the proposals and provide feedback. Users check the proposals via their devices and evaluate how well they match their preferences. The evaluation is sent to the server via the device and stored as reference data for future proposal generation. 【0174】 Step 6: 【0175】 The server readjusts the suggestions. The server re-analyzes user feedback and newly collected sentiment information to improve the content of the suggestions. Using the re-analysis method, the AI ​​model updates the suggestions to better match the user's needs. The adjusted suggestions are sent back to the terminal for final confirmation by the user. 【0176】 (Application Example 2) 【0177】 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". 【0178】 Conventional event support systems have a problem in that they do not adequately adjust suggestions to take into account the user's emotions, resulting in insufficient recommendations for individual users. Furthermore, the accuracy of personalized suggestions is low, which leads to insufficient user satisfaction. 【0179】 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. 【0180】 In this invention, the server includes information acquisition means for acquiring user information, data storage means for storing the input information as data, and suggestion generation means for generating and adjusting suggestions based on the stored data and the user's emotions. This makes it possible to provide individually optimized suggestions that reflect the user's emotions. 【0181】 "Information acquisition methods" refer to the means of receiving information from users. They play a role in acquiring data related to users' emotions and requests. 【0182】 A "data storage method" is a means of properly storing acquired information. It is used for information management and preparation for subsequent analysis processing. 【0183】 A "proposal generation method" is a means of analyzing stored data and generating suggestions that respond to user requests and emotions. It executes a process to provide the user with the most suitable content. 【0184】 An "information output means" is a means of providing the generated suggestions to the user. It plays a role in conveying information through visual or auditory feedback. 【0185】 An "emotion analysis tool" is a means of recognizing and analyzing a user's emotions. It identifies the emotional state based on the input information and the user's responses. 【0186】 A "proposal adjustment mechanism" is a means of adaptively adjusting proposals generated based on the results of sentiment analysis. It dynamically changes the content of the proposals to improve user satisfaction. 【0187】 A "re-analysis mechanism" is a means of receiving user feedback and re-evaluating and adjusting the proposed content. It operates with the aim of providing the optimal proposal that aligns with the user's intentions. 【0188】 This invention provides a system that recognizes a user's emotions and makes personalized suggestions based on those emotions. The details of the system that implements this application are described below. 【0189】 The server first collects information from the user using information acquisition methods. For example, by having the user input their event requests and preferences, and capturing their facial expressions and tone of voice at that time, it is possible to understand their emotional state. The information is stored using data storage methods and referenced in subsequent processing as needed. 【0190】 Next, the information stored in the data storage means is analyzed using the suggestion generation means while performing user sentiment analysis. The sentiment analysis means constructs the most suitable suggestion for the situation based on the user's input information and sentiment data. The suggestion adjustment means plays the role of improving the suggestion content according to the analysis results, making it more appropriate to the user's requirements. 【0191】 Finally, the information output device provides the generated suggestions to the user's terminal and outputs the information using visual or auditory means. When the user provides feedback on the provided suggestions, this feedback is also taken into consideration by the re-analysis device and used to further improve the quality of future suggestions. 【0192】 This system can be installed in, for example, a home robot to help prepare for special events within the home (e.g., a birthday party). If the user inputs "I'd like a party with a calm atmosphere," the emotion analysis system will read the user's positive emotions and, based on that, suggest appropriate decorations and music. 【0193】 Examples of prompt messages include the following: 【0194】 "Please suggest ideas to liven up the party atmosphere. We'd like to know what kind of decorations and music would make users feel comfortable." 【0195】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0196】 Step 1: 【0197】 The user accesses the device and inputs their event preferences and requests into the information acquisition system. At this time, emotional data such as the user's facial expressions and tone of voice are also captured. The input information and emotional data become the output of this step and are passed on to the next process. 【0198】 Step 2: 【0199】 The server temporarily stores the received information and sentiment data using data storage means. This stored data becomes the basic dataset for analysis. Here, data processing is performed to consistently store the input user information and sentiment data. 【0200】 Step 3: 【0201】 The server retrieves the stored data and analyzes the information using a suggestion generation mechanism. In this data calculation, the user's emotional state is considered using an emotion analysis mechanism to generate suggestions best suited to the user's needs. Stored data is used as input to perform emotion recognition, deepening the understanding of the user. 【0202】 Step 4: 【0203】 Before providing suggestions to the user, a suggestion adjustment mechanism is activated. The server dynamically adjusts the generated suggestions based on the acquired sentiment data. In this step, the optimal suggestions are narrowed down using a generation AI model, preparing to output suggestions that contribute to improving user satisfaction. 【0204】 Step 5: 【0205】 The adjusted proposal is sent to the user's terminal via an information output device. The user reviews the proposal on their terminal and considers the event details through visual or audio feedback. The output in this step is proposal information in a format that is easily understandable to the user. 【0206】 Step 6: 【0207】 Users provide feedback on the suggestions they receive. The feedback information entered on the terminal is sent to the server and used for re-analysis to improve future suggestions. The input here includes the user's satisfaction level and further requests, which the server stores and analyzes for re-analysis. 【0208】 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. 【0209】 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. 【0210】 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. 【0211】 [Second Embodiment] 【0212】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0213】 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. 【0214】 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). 【0215】 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. 【0216】 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. 【0217】 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). 【0218】 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. 【0219】 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. 【0220】 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. 【0221】 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. 【0222】 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. 【0223】 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". 【0224】 The system implementing this invention is equipped with a generative AI designed to efficiently carry out wedding preparations. Below, an embodiment of the system and the processing flow of its program are described in natural language. 【0225】 User information input and data collection 【0226】 Users can input wedding-related information in a questionnaire format using devices such as smartphones and PCs. This information includes guest lists, wedding concepts, and preferred styles. This input information is transmitted from the device to a server via the internet and securely recorded by storage devices. 【0227】 Data analysis and proposal generation 【0228】 The server uses stored data to perform analysis. This analysis utilizes AI to analyze user input and automatically generates suggestions across multiple elements, such as costume recommendations, invitation designs, venue layouts, and background music selections. These suggestions are individually adjusted and optimized according to the user's preferences. 【0229】 Proposal submission and feedback reception 【0230】 The generated proposals are provided to the user via an output device. The user can review the proposals on their device and provide feedback on each element, offering opinions and requests. This feedback is further incorporated by a re-analysis device, and the server readjusts the proposals. Through this process, an optimal wedding plan that more closely matches the user's wishes is created. 【0231】 Specific example 【0232】 For example, if a user desires a "warm atmosphere incorporating the beauty of autumn nature," the system can suggest invitation designs with corresponding color schemes and present venue layouts using natural floral arrangements and wooden decorations. Furthermore, the system can automatically adjust meal plans, including vegetarian options, to suit the preferences of specific guests. 【0233】 In this way, this system highly automates various wedding preparations, allowing users to plan and execute their ideal wedding without feeling burdened by their busy daily lives. 【0234】 The following describes the processing flow. 【0235】 Step 1: 【0236】 Users access the survey form via their device and enter the required information. Specifically, they enter the date of the ceremony, guest list, concept, preferred colors and style, etc. 【0237】 Step 2: 【0238】 The terminal sends the entered information to the server. The transmitted data is stored in a database on the server and prepared for subsequent processing. 【0239】 Step 3: 【0240】 The server analyzes the received data and generates AI-generated suggestions based on the user's preferences and wedding concept. This analysis includes multiple elements such as attire, invitations, venue layout, and background music. 【0241】 Step 4: 【0242】 The server sends the generated suggestions to the user's device. The user then reviews these suggestions on their device and checks whether they match their preferences. 【0243】 Step 5: 【0244】 Users provide feedback on the proposal. This feedback can include specific requests, such as design changes or preferred options. 【0245】 Step 6: 【0246】 The server re-analyzes the data based on user feedback and adjusts the proposal. This re-analysis generates a final plan that reflects the user's requests. 【0247】 Step 7: 【0248】 The final proposal is sent to the terminal for the user to review and approve. If the user is satisfied at this step, the system proceeds to execute the necessary orders and preparations. 【0249】 (Example 1) 【0250】 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". 【0251】 In modern society, wedding preparations require a great deal of time and effort, and it is difficult to create the optimal plan from among many options. Therefore, there is a need for an efficient system that can meet the diverse and individual needs of various users. 【0252】 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. 【0253】 In this invention, the server includes a user input device, a storage device for storing the input information as an information set, and an analysis device for processing the recorded information and automatically generating suggestions that respond to the user's requests. This enables the automation, proposal, and optimization of appropriate wedding plans tailored to the individual user's wishes. 【0254】 "User device" refers to a device used by a user to input information, such as a smartphone or PC. 【0255】 A "storage device" is a device for storing input information as a collection of information, and typically uses a database to manage this information. 【0256】 An "analysis device" is a device that processes recorded information and automatically generates suggestions that respond to user requests, using machine learning algorithms to analyze data. 【0257】 A "providing device" is a device that provides the generated proposal to the user, and typically transmits the information via the internet so that the user can confirm it. 【0258】 A "re-analysis device" is a device used to adjust the proposed content based on the responses received from users, and it optimizes the proposal by analyzing the feedback. 【0259】 A "portable device" is a terminal that a user can carry with them, and this mainly includes smartphones and tablets. 【0260】 A "generative AI model" is an artificial intelligence model that analyzes data based on machine learning algorithms to generate and optimize suggestions. 【0261】 The system for implementing the invention is an information processing system designed to streamline the wedding planning process. The specific form of this system is described below. 【0262】 Users input wedding-related information using devices such as smartphones or PCs. These devices transmit this input information to a server via the internet. The server uses a database management system (DBMS) to securely record the received information for data storage. 【0263】 The server utilizes a generative AI model to analyze the recorded data. This AI model uses machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. Based on the analysis results, the server automatically generates various suggestions related to weddings. These suggestions include choices for attire, invitation designs, venue layouts, and background music selections. 【0264】 For example, if a user requests a "warm atmosphere incorporating the beauty of autumn nature," the server will propose a design that takes this request into account. A specific example of a prompt would be: "We are planning a wedding with a warm atmosphere incorporating the beauty of autumn nature. Please propose a plan that will satisfy our guests, using natural floral arrangements and wooden decorations, and including a vegetarian menu." 【0265】 This allows the server to provide users with their ideal wedding plan while optimizing the planning process with minimal effort. Users can efficiently create and optimize their plans without feeling burdened by their busy schedules. 【0266】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0267】 Step 1: 【0268】 Users input wedding-related information using devices such as smartphones and PCs. This information includes guest lists, wedding themes, and preferred styles. The entered data is sent to a server via the internet. Specifically, information is sent by operating the user interface on the device's form and pressing the "Submit" button. Input consists of options selected by the user, and output is the transfer of data to the server. 【0269】 Step 2: 【0270】 The server stores information received from the terminal using a database management system (DBMS). Here, data is securely recorded and managed. The server parses the received data in JSON format and stores the information in the appropriate tables. The input is data in JSON format, and the output is structured database entries. 【0271】 Step 3: 【0272】 The server utilizes a generative AI model to analyze the stored data. This involves using machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. This analysis generates feature vectors and automatically produces diverse suggestions through pattern matching. The input is structured data stored in a database, and the output is automatically generated wedding plan suggestions. 【0273】 Step 4: 【0274】 The server converts the generated proposals into HTML or PDF format and sends them to the terminal to provide them to the user. The terminal receives these and displays them in a format that the user can review. Specifically, the user can review each proposal by displaying the data from the server in a browser or PDF viewer. The input is proposal data generated by an AI model, and the output is a visually presented plan. 【0275】 Step 5: 【0276】 The user sends feedback on the proposal to the server via their device. The server incorporates this feedback using a re-analysis mechanism and readjusts the proposal. This results in the provision of an optimal proposal that reflects the user's opinion. Specifically, the process is completed by entering feedback using the feedback form on the device and pressing the "Send" button again. The input is the user's feedback information, and the output is the improved proposal data. 【0277】 (Application Example 1) 【0278】 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." 【0279】 Currently, preparing for a wedding requires many steps, and users need to spend a great deal of time and effort. Also, due to the difficulty of visualizing proposals, it is difficult for users to fully understand the proposal content and make decisions. Furthermore, it is required to quickly and efficiently reflect user feedback. By utilizing a virtual reality environment, a method is needed to solve these problems and enable intuitive planning that is not laborious for users. 【0280】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means. 【0281】 In this invention, the server includes an acquisition means for acquiring information from a user, a holding means for holding the acquired information as data, an analysis means for analyzing the held data and creating a proposal based on the user's request, a display means for providing a virtual reality environment, a detection means for detecting the user's actions within the virtual reality environment, and a collection means for collecting feedback through the virtual reality environment. Thereby, the user can visually experience the proposal content using the virtual reality environment and provide quick feedback. The user's feedback is immediately reflected in the proposal, enabling more personalized wedding planning. 【0282】 The "acquisition means" is a part equipped with a function for collecting information from a user. 【0283】 The "holding means" is a mechanism for safely and efficiently storing the collected data. 【0284】 The "analysis means" is a method for analyzing the stored data and generating a proposal according to the user's request. 【0285】 The "display means" is a device for the user to access the virtual reality environment and visually confirm the proposal content. 【0286】 The "detection means" is a technology for identifying the actions and operations of users within a virtual reality environment. 【0287】 The "collection means" is a method for obtaining feedback from users and improving the proposed content based on it. 【0288】 The system for implementing this invention is designed to efficiently prepare for a wedding ceremony in a virtual reality environment. Users can input wedding-related information as data using their own terminals and visually confirm the plan generated through the virtual environment. 【0289】 The server uses acquisition means to obtain information from users. The acquired information is securely stored by the storage means. The stored data is analyzed using analysis means, and a specific proposal based on the user's requirements is created by the generated AI model. For example, based on the theme of the wedding ceremony and the guest list, an optimal venue design, decoration plan, and menu plan are proposed. 【0290】 Users can experience these proposals within the virtual reality environment via the display means and directly operate the visualized results in the virtual space. The system uses detection means to identify the actions and operations of users, enabling real-time interaction within the virtual environment. Feedback from users is obtained by the collection means and immediately utilized for readjusting the proposed content. 【0291】 Hardware used includes VR head-mounted displays and high-spec PCs, and software such as Unity (game engine), Python, and TensorFlow is used. Through these, users can intuitively understand and customize the overall picture of the wedding ceremony through an immersive experience. 【0292】 For example, if a user requests a wedding with a "warm atmosphere themed around autumn nature," the generating AI model will suggest venue color schemes and material selections accordingly. The user can then review the plan presented in virtual reality and provide feedback such as, "I'd like to change this material to something else." 【0293】 An example of a prompt to input into the generating AI model would be: "Please suggest relevant color schemes and materials so that the user can experience a wedding venue decoration design themed around autumn nature in VR. Also, update it immediately based on any changes in feedback." 【0294】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0295】 Step 1: 【0296】 The user enters wedding-related information via a terminal. This input data includes the number of guests, the wedding theme, and preferred style. This information is transmitted from the terminal to the server via a data acquisition method. The data obtained from the input is then pre-formatted for storage. 【0297】 Step 2: 【0298】 The server stores the acquired user information in cloud storage using a retention mechanism. During storage, the data is encrypted or compressed as needed. The stored information is saved in a structured format so that it can be used for later analysis. 【0299】 Step 3: 【0300】 Based on the stored data, the server performs data analysis using Python and TensorFlow scripts as analytical tools. This allows the generative AI model to generate appropriate wedding plans. The analysis process outputs suggestions that reflect the user's preferences. 【0301】 Step 4: 【0302】 The server provides the generated proposal to the user through the display means. Specifically, a VR environment is constructed using the Unity engine, and the proposed wedding design and layout are visually displayed therein. The user checks this through a head-mounted display. 【0303】 Step 5: 【0304】 The user tries the proposed virtual reality proposal and provides feedback. The feedback is recorded by the detection means for operations within the virtual environment and input from the user directly into the collection means. Through this feedback, the desires and opinions regarding the proposal are clarified. 【0305】 Step 6: 【0306】 The server analyzes the feedback collected from the user again and generates a new proposal. In the re-analysis means, data processing is performed according to the user's desired changes, and an optimal proposal is derived. As a result, a plan satisfactory to the user is provided. 【0307】 Step 7: 【0308】 Finally, the adjusted proposal is presented to the user for approval. The approved plan is output as a detailed plan for execution. Thereby, the user is prepared to specifically implement the planned wedding. 【0309】 Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions. 【0310】 The system in this invention is a wedding preparation support system that incorporates an emotion engine that recognizes the user's emotions. The following describes in detail how this system is implemented. 【0311】 System Configuration 【0312】 The system has a complex structure that includes a user terminal, a server, and an emotion engine. The user uses the terminal to input information necessary for their wedding and communicates their requests and preferences in a questionnaire format. The emotion engine analyzes the user's facial expressions, tone of voice, and word choice during input and when reviewing suggestions to identify their emotions. This emotion information is transferred to the server and used by the analysis system. 【0313】 Program processing 【0314】 The server analyzes the user's input data, including emotional information received from the emotion engine. The analysis then works to generate more effective and appropriate suggestions based on the user's emotions. For example, if the user is showing tension or anxiety, the suggestions will be adjusted to be more reassuring or include approaches to reduce stress. 【0315】 The generated suggestions are sent to the user's device, where the user can review them. A re-analysis mechanism is used to dynamically adjust the suggestions, taking into account user feedback and associated emotional information. This allows for further fine-tuning based on the emotional state the user expressed in response to the suggestions. 【0316】 Specific example 【0317】 For example, if a user enters that they want a wedding that is "glamorous yet calming," the emotion engine will detect the user's subtle emotional response. If it recognizes that the user felt excited by a particular floral design, the server will generate suggestions that reflect that. On the other hand, if the user expresses anxiety about the background music suggestions, the system will add more relaxing music options to the list. 【0318】 In this way, the system, incorporating an emotion engine, provides an ideal wedding preparation process while being attentive to the user's emotions. Users receive more personalized support and, as a result, achieve a high level of satisfaction. 【0319】 The following describes the processing flow. 【0320】 Step 1: 【0321】 Users access the system through their devices and input personal information and wedding preferences in a questionnaire format. During this process, the device's camera and microphone are used to record the user's facial expressions and voice while they are inputting the information. 【0322】 Step 2: 【0323】 The device sends survey responses and recorded sentiment data to the server. The transmitted data is stored on the server as a dataset containing the user's basic information and sentiment. 【0324】 Step 3: 【0325】 The server analyzes the received data, and the emotion engine analyzes the user's facial expressions and tone of voice to determine their emotional state. For example, if the user is smiling, it identifies feelings such as joy, and if they are frowning, it identifies feelings such as dissatisfaction. 【0326】 Step 4: 【0327】 The analysis tool combines user preferences and emotional information to generate suggestions. For example, if a user expresses delight with a floral arrangement design, suggestions centered around that design will be generated. 【0328】 Step 5: 【0329】 The server generates suggestions and sends them to the terminal, presenting the suggestions to the user. The user reviews these suggestions through the terminal, and their emotional response to each suggestion is recorded again. 【0330】 Step 6: 【0331】 Users provide feedback on the proposal, and emotional information is sent from their device. This feedback includes specific requests and suggestions for changes. 【0332】 Step 7: 【0333】 The server's re-analysis mechanism adjusts suggestions based on the latest sentiment information and feedback. The adjusted suggestions are then regenerated to be in a format that best satisfies the user. 【0334】 Step 8: 【0335】 The finalized proposal is sent to the user's device for review and approval. Once approved, the necessary orders and reservations for wedding preparations are automatically arranged. 【0336】 (Example 2) 【0337】 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". 【0338】 In wedding planning, there is a lack of personalized suggestions that take into account the user's emotions. Therefore, there is a need for methodologies that can provide ideal wedding plans while reducing the anxiety and stress that users experience. 【0339】 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. 【0340】 In this invention, the server includes means for inputting information from the user and analyzing emotional information, means for storing the input information and emotional information, and means for analyzing the stored data and generating suggestions based on the user's emotions. This makes it possible to provide the user with a personalized wedding plan that is sensitive to their emotions. 【0341】 An "input method" is a means that has the ability to receive information related to weddings from users and analyze it, including emotional information. 【0342】 "Information storage means" refers to means of appropriately storing user input information and emotional information, and maintaining a state in which it can be used for subsequent analysis and suggestion generation. 【0343】 "Analysis means" refers to the means of performing the necessary processing to generate optimal wedding proposals based on stored user information and emotional data. 【0344】 "Output means" refers to means that have the function of providing the generated wedding proposals to the user and collecting feedback from the user. 【0345】 "Transmission means" refers to a means for effectively transmitting multiple suggestions generated by the analysis means to the user's terminal. 【0346】 A "re-analysis method" is a means of re-evaluating a proposal based on user feedback and emotional information, and processing it to make adjustments as necessary. 【0347】 The embodiment of this invention aims to assist in wedding preparations while taking the user's emotions into consideration. The system comprises a server, a terminal, and an emotion engine. The user inputs wedding information via the terminal, and based on this, the system provides personalized suggestions. 【0348】 The server uses Python-based natural language processing and machine learning models to process the input user data and sentiment information. Data analysis libraries such as TensorFlow and Pandas are used for processing. The sentiment engine is used to analyze facial expressions and voice tone, thereby detecting the user's subtle emotional state. 【0349】 For example, if a user inputs that they want a wedding with a "calm atmosphere," the emotion engine analyzes how the user feels about a particular piece of music. If, for instance, it detects that the user is feeling anxious while listening to a specific piece of background music, the server will select more relaxing music and add it to the suggestions. 【0350】 As an example of a prompt, you could input something like, "Generate a relaxing wedding plan based on the user's emotions," into the generation AI model to more effectively customize the suggestions. 【0351】 This technology allows users to receive wedding plans tailored to their individual emotional needs, enabling a high-quality and satisfying experience. 【0352】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0353】 Step 1: 【0354】 The user enters information. The user uses a device to enter their wishes and requests regarding the wedding. The information entered includes the theme, number of participants, budget, etc. The device receives this information, and an emotion engine analyzes the user's facial expressions and voice in real time, sending the emotion data to the server. 【0355】 Step 2: 【0356】 The server receives and stores the data. The server records the input information and sentiment data sent by the user and stores it appropriately using information storage means. This data is used as foundational data necessary for subsequent suggestion generation. 【0357】 Step 3: 【0358】 The server analyzes the data. Using analytical tools, the server performs a detailed analysis of stored user information and sentiment data. In this process, TensorFlow and Pandas in Python are used to identify data relationships and user sentiment tendencies, and the data is processed to generate optimal suggestions. The output consists of parameters and conditions used by the generative AI model. 【0359】 Step 4: 【0360】 The server generates proposals. Based on the analysis results, a generation AI model is used to generate wedding plans that match the user's emotions and desires. At this time, a prompt such as "Generate proposals for a relaxing wedding" is input to the AI ​​model. The generated proposals are the specific plans presented to the user. 【0361】 Step 5: 【0362】 Users review the proposals and provide feedback. Users check the proposals via their devices and evaluate how well they match their preferences. The evaluation is sent to the server via the device and stored as reference data for future proposal generation. 【0363】 Step 6: 【0364】 The server readjusts the suggestions. The server re-analyzes user feedback and newly collected sentiment information to improve the content of the suggestions. Using the re-analysis method, the AI ​​model updates the suggestions to better match the user's needs. The adjusted suggestions are sent back to the terminal for final confirmation by the user. 【0365】 (Application Example 2) 【0366】 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." 【0367】 Conventional event support systems have a problem in that they do not adequately adjust suggestions to take into account the user's emotions, resulting in insufficient recommendations for individual users. Furthermore, the accuracy of personalized suggestions is low, which leads to insufficient user satisfaction. 【0368】 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. 【0369】 In this invention, the server includes information acquisition means for acquiring user information, data storage means for storing the input information as data, and suggestion generation means for generating and adjusting suggestions based on the stored data and the user's emotions. This makes it possible to provide individually optimized suggestions that reflect the user's emotions. 【0370】 "Information acquisition methods" refer to the means of receiving information from users. They play a role in acquiring data related to users' emotions and requests. 【0371】 A "data storage method" is a means of properly storing acquired information. It is used for information management and preparation for subsequent analysis processing. 【0372】 A "proposal generation method" is a means of analyzing stored data and generating suggestions that respond to user requests and emotions. It executes a process to provide the user with the most suitable content. 【0373】 An "information output means" is a means of providing the generated suggestions to the user. It plays a role in conveying information through visual or auditory feedback. 【0374】 An "emotion analysis tool" is a means of recognizing and analyzing a user's emotions. It identifies the emotional state based on the input information and the user's responses. 【0375】 A "proposal adjustment mechanism" is a means of adaptively adjusting proposals generated based on the results of sentiment analysis. It dynamically changes the content of the proposals to improve user satisfaction. 【0376】 A "re-analysis mechanism" is a means of receiving user feedback and re-evaluating and adjusting the proposed content. It operates with the aim of providing the optimal proposal that aligns with the user's intentions. 【0377】 This invention provides a system that recognizes a user's emotions and makes personalized suggestions based on those emotions. The details of the system that implements this application are described below. 【0378】 The server first collects information from the user using information acquisition methods. For example, by having the user input their event requests and preferences, and capturing their facial expressions and tone of voice at that time, it is possible to understand their emotional state. The information is stored using data storage methods and referenced in subsequent processing as needed. 【0379】 Next, the information stored in the data storage means is analyzed using the suggestion generation means while performing user sentiment analysis. The sentiment analysis means constructs the most suitable suggestion for the situation based on the user's input information and sentiment data. The suggestion adjustment means plays the role of improving the suggestion content according to the analysis results, making it more appropriate to the user's requirements. 【0380】 Finally, the information output device provides the generated suggestions to the user's terminal and outputs the information using visual or auditory means. When the user provides feedback on the provided suggestions, this feedback is also taken into consideration by the re-analysis device and used to further improve the quality of future suggestions. 【0381】 This system can be installed in, for example, a home robot to help prepare for special events within the home (e.g., a birthday party). If the user inputs "I'd like a party with a calm atmosphere," the emotion analysis system will read the user's positive emotions and, based on that, suggest appropriate decorations and music. 【0382】 Examples of prompt messages include the following: 【0383】 "Please suggest ideas to liven up the party atmosphere. We'd like to know what kind of decorations and music would make users feel comfortable." 【0384】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0385】 Step 1: 【0386】 The user accesses the device and inputs their event preferences and requests into the information acquisition system. At this time, emotional data such as the user's facial expressions and tone of voice are also captured. The input information and emotional data become the output of this step and are passed on to the next process. 【0387】 Step 2: 【0388】 The server temporarily stores the received information and sentiment data using data storage means. This stored data becomes the basic dataset for analysis. Here, data processing is performed to consistently store the input user information and sentiment data. 【0389】 Step 3: 【0390】 The server retrieves the stored data and analyzes the information using a suggestion generation mechanism. In this data calculation, the user's emotional state is considered using an emotion analysis mechanism to generate suggestions best suited to the user's needs. Stored data is used as input to perform emotion recognition, deepening the understanding of the user. 【0391】 Step 4: 【0392】 Before providing suggestions to the user, a suggestion adjustment mechanism is activated. The server dynamically adjusts the generated suggestions based on the acquired sentiment data. In this step, the optimal suggestions are narrowed down using a generation AI model, preparing to output suggestions that contribute to improving user satisfaction. 【0393】 Step 5: 【0394】 The adjusted proposal is sent to the user's terminal via an information output device. The user reviews the proposal on their terminal and considers the event details through visual or audio feedback. The output in this step is proposal information in a format that is easily understandable to the user. 【0395】 Step 6: 【0396】 Users provide feedback on the suggestions they receive. The feedback information entered on the terminal is sent to the server and used for re-analysis to improve future suggestions. The input here includes the user's satisfaction level and further requests, which the server stores and analyzes for re-analysis. 【0397】 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. 【0398】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0399】 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. 【0400】 [Third Embodiment] 【0401】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0402】 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. 【0403】 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). 【0404】 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. 【0405】 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. 【0406】 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). 【0407】 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. 【0408】 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. 【0409】 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. 【0410】 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. 【0411】 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. 【0412】 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". 【0413】 The system implementing this invention is equipped with a generative AI designed to efficiently carry out wedding preparations. Below, an embodiment of the system and the processing flow of its program are described in natural language. 【0414】 User information input and data collection 【0415】 Users can input wedding-related information in a questionnaire format using devices such as smartphones and PCs. This information includes guest lists, wedding concepts, and preferred styles. This input information is transmitted from the device to a server via the internet and securely recorded by storage devices. 【0416】 Data analysis and proposal generation 【0417】 The server uses stored data to perform analysis. This analysis utilizes AI to analyze user input and automatically generates suggestions across multiple elements, such as costume recommendations, invitation designs, venue layouts, and background music selections. These suggestions are individually adjusted and optimized according to the user's preferences. 【0418】 Proposal submission and feedback reception 【0419】 The generated proposals are provided to the user via an output device. The user can review the proposals on their device and provide feedback on each element, offering opinions and requests. This feedback is further incorporated by a re-analysis device, and the server readjusts the proposals. Through this process, an optimal wedding plan that more closely matches the user's wishes is created. 【0420】 Specific example 【0421】 For example, if a user desires a "warm atmosphere incorporating the beauty of autumn nature," the system can suggest invitation designs with corresponding color schemes and present venue layouts using natural floral arrangements and wooden decorations. Furthermore, the system can automatically adjust meal plans, including vegetarian options, to suit the preferences of specific guests. 【0422】 In this way, this system highly automates various wedding preparations, allowing users to plan and execute their ideal wedding without feeling burdened by their busy daily lives. 【0423】 The following describes the processing flow. 【0424】 Step 1: 【0425】 Users access the survey form via their device and enter the required information. Specifically, they enter the date of the ceremony, guest list, concept, preferred colors and style, etc. 【0426】 Step 2: 【0427】 The terminal sends the entered information to the server. The transmitted data is stored in a database on the server and prepared for subsequent processing. 【0428】 Step 3: 【0429】 The server analyzes the received data and generates AI-generated suggestions based on the user's preferences and wedding concept. This analysis includes multiple elements such as attire, invitations, venue layout, and background music. 【0430】 Step 4: 【0431】 The server sends the generated suggestions to the user's device. The user then reviews these suggestions on their device and checks whether they match their preferences. 【0432】 Step 5: 【0433】 Users provide feedback on the proposal. This feedback can include specific requests, such as design changes or preferred options. 【0434】 Step 6: 【0435】 The server re-analyzes the data based on user feedback and adjusts the proposal. This re-analysis generates a final plan that reflects the user's requests. 【0436】 Step 7: 【0437】 The final proposal is sent to the terminal for the user to review and approve. If the user is satisfied at this step, the system proceeds to execute the necessary orders and preparations. 【0438】 (Example 1) 【0439】 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." 【0440】 In modern society, wedding preparations require a great deal of time and effort, and it is difficult to create the optimal plan from among many options. Therefore, there is a need for an efficient system that can meet the diverse and individual needs of various users. 【0441】 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. 【0442】 In this invention, the server includes a user input device, a storage device for storing the input information as an information set, and an analysis device for processing the recorded information and automatically generating suggestions that respond to the user's requests. This enables the automation, proposal, and optimization of appropriate wedding plans tailored to the individual user's wishes. 【0443】 "User device" refers to a device used by a user to input information, such as a smartphone or PC. 【0444】 A "storage device" is a device for storing input information as a collection of information, and typically uses a database to manage this information. 【0445】 An "analysis device" is a device that processes recorded information and automatically generates suggestions that respond to user requests, using machine learning algorithms to analyze data. 【0446】 A "providing device" is a device that provides the generated proposal to the user, and typically transmits the information via the internet so that the user can confirm it. 【0447】 A "re-analysis device" is a device used to adjust the proposed content based on the responses received from users, and it optimizes the proposal by analyzing the feedback. 【0448】 A "portable device" is a terminal that a user can carry with them, and this mainly includes smartphones and tablets. 【0449】 A "generative AI model" is an artificial intelligence model that analyzes data based on machine learning algorithms to generate and optimize suggestions. 【0450】 The system for implementing the invention is an information processing system designed to streamline the wedding planning process. The specific form of this system is described below. 【0451】 Users input wedding-related information using devices such as smartphones or PCs. These devices transmit this input information to a server via the internet. The server uses a database management system (DBMS) to securely record the received information for data storage. 【0452】 The server utilizes a generative AI model to analyze the recorded data. This AI model uses machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. Based on the analysis results, the server automatically generates various suggestions related to weddings. These suggestions include choices for attire, invitation designs, venue layouts, and background music selections. 【0453】 For example, if a user requests a "warm atmosphere incorporating the beauty of autumn nature," the server will propose a design that takes this request into account. A specific example of a prompt would be: "We are planning a wedding with a warm atmosphere incorporating the beauty of autumn nature. Please propose a plan that will satisfy our guests, using natural floral arrangements and wooden decorations, and including a vegetarian menu." 【0454】 This allows the server to provide users with their ideal wedding plan while optimizing the planning process with minimal effort. Users can efficiently create and optimize their plans without feeling burdened by their busy schedules. 【0455】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0456】 Step 1: 【0457】 Users input wedding-related information using devices such as smartphones and PCs. This information includes guest lists, wedding themes, and preferred styles. The entered data is sent to a server via the internet. Specifically, information is sent by operating the user interface on the device's form and pressing the "Submit" button. Input consists of options selected by the user, and output is the transfer of data to the server. 【0458】 Step 2: 【0459】 The server stores information received from the terminal using a database management system (DBMS). Here, data is securely recorded and managed. The server parses the received data in JSON format and stores the information in the appropriate tables. The input is data in JSON format, and the output is structured database entries. 【0460】 Step 3: 【0461】 The server utilizes a generative AI model to analyze the stored data. This involves using machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. This analysis generates feature vectors and automatically produces diverse suggestions through pattern matching. The input is structured data stored in a database, and the output is automatically generated wedding plan suggestions. 【0462】 Step 4: 【0463】 The server converts the generated proposals into HTML or PDF format and sends them to the terminal to provide them to the user. The terminal receives these and displays them in a format that the user can review. Specifically, the user can review each proposal by displaying the data from the server in a browser or PDF viewer. The input is proposal data generated by an AI model, and the output is a visually presented plan. 【0464】 Step 5: 【0465】 The user sends feedback on the proposal to the server via their device. The server incorporates this feedback using a re-analysis mechanism and readjusts the proposal. This results in the provision of an optimal proposal that reflects the user's opinion. Specifically, the process is completed by entering feedback using the feedback form on the device and pressing the "Send" button again. The input is the user's feedback information, and the output is the improved proposal data. 【0466】 (Application Example 1) 【0467】 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." 【0468】 Currently, wedding planning involves many steps, requiring users to invest a significant amount of time and effort. Furthermore, the difficulty in visualizing proposals makes it challenging for users to fully understand and make informed decisions. Additionally, there is a need to quickly and efficiently incorporate user feedback. A method is needed to address these challenges and enable user-friendly, intuitive planning by utilizing a virtual reality environment. 【0469】 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. 【0470】 In this invention, the server includes acquisition means for obtaining information from the user, storage means for storing the acquired information as data, analysis means for analyzing the stored data and creating suggestions based on the user's requests, display means for providing a virtual reality environment, detection means for detecting the user's actions within the virtual reality environment, and collection means for collecting feedback through the virtual reality environment. This allows the user to visually experience the suggested content using the virtual reality environment and provide rapid feedback. The user's feedback is immediately reflected in the suggestions, enabling more personalized wedding planning. 【0471】 "Means of acquisition" refers to the part equipped with functions for collecting information from users. 【0472】 A "storage mechanism" is a system for safely and efficiently storing collected data. 【0473】 "Analysis means" refers to a method for analyzing stored data and generating suggestions that meet user requirements. 【0474】 A "display means" is a device that allows a user to access a virtual reality environment and visually confirm the proposed content. 【0475】 "Detection means" refers to technologies for identifying user actions and operations within a virtual reality environment. 【0476】 "Methods of data collection" refers to methods for obtaining user feedback and using that feedback to improve the proposed content. 【0477】 The system implementing this invention is designed to efficiently carry out wedding preparations in a virtual reality environment. Users can input wedding-related information as data using their own devices and visually confirm the plan generated through the virtual environment. 【0478】 The server uses acquisition means to obtain information from the user. The acquired information is securely stored by retention means. The stored data is analyzed using analysis means, and specific suggestions based on the user's requests are generated by a generative AI model. For example, based on the wedding theme and guest list, optimal venue design, decoration plan, and catering plan are proposed. 【0479】 Users can experience these suggestions within a virtual reality environment via display means and directly manipulate the visualized results in the virtual space. The system uses detection means to identify user actions and operations, enabling real-time interaction within the virtual environment. User feedback is collected by collection means and immediately used to readjust the suggestions. 【0480】 The hardware used includes VR head-mounted displays and high-spec PCs, while the software utilizes Unity (game engine), Python, and TensorFlow. This allows users to intuitively understand and customize the overall picture of their wedding through an immersive experience. 【0481】 For example, if a user requests a wedding with a "warm atmosphere themed around autumn nature," the generating AI model will suggest venue color schemes and material selections accordingly. The user can then review the plan presented in virtual reality and provide feedback such as, "I'd like to change this material to something else." 【0482】 An example of a prompt to input into the generating AI model would be: "Please suggest relevant color schemes and materials so that the user can experience a wedding venue decoration design themed around autumn nature in VR. Also, update it immediately based on any changes in feedback." 【0483】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0484】 Step 1: 【0485】 The user enters wedding-related information via a terminal. This input data includes the number of guests, the wedding theme, and preferred style. This information is transmitted from the terminal to the server via a data acquisition method. The data obtained from the input is then pre-formatted for storage. 【0486】 Step 2: 【0487】 The server stores the acquired user information in cloud storage using a retention mechanism. During storage, the data is encrypted or compressed as needed. The stored information is saved in a structured format so that it can be used for later analysis. 【0488】 Step 3: 【0489】 Based on the stored data, the server performs data analysis using Python and TensorFlow scripts as analytical tools. This allows the generative AI model to generate appropriate wedding plans. The analysis process outputs suggestions that reflect the user's preferences. 【0490】 Step 4: 【0491】 The server provides the generated proposals to the user through a display mechanism. Specifically, a VR environment is built using the Unity engine, and the proposed wedding designs and layouts are visually displayed within it. The user views this through a head-mounted display. 【0492】 Step 5: 【0493】 Users try out the displayed virtual reality suggestions and provide feedback. This feedback is recorded by detection devices that track actions within the virtual environment and directly input from the user into a data collection system. This feedback clarifies requests and opinions regarding the suggestions. 【0494】 Step 6: 【0495】 The server re-analyzes the feedback collected from users and generates new suggestions. The re-analysis process processes the data according to the user's requested changes, leading to the optimal suggestion. As a result, a more satisfying plan is provided to the user. 【0496】 Step 7: 【0497】 Finally, the refined proposal is presented to the user for approval. The approved plan is then output as a detailed plan for implementation. This prepares the user to concretely carry out their planned wedding. 【0498】 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. 【0499】 The system in this invention is a wedding preparation support system that incorporates an emotion engine that recognizes the user's emotions. The following describes in detail how this system is implemented. 【0500】 System Configuration 【0501】 The system has a complex structure that includes a user terminal, a server, and an emotion engine. The user uses the terminal to input information necessary for their wedding and communicates their requests and preferences in a questionnaire format. The emotion engine analyzes the user's facial expressions, tone of voice, and word choice during input and when reviewing suggestions to identify their emotions. This emotion information is transferred to the server and used by the analysis system. 【0502】 Program processing 【0503】 The server analyzes the user's input data, including emotional information received from the emotion engine. The analysis then works to generate more effective and appropriate suggestions based on the user's emotions. For example, if the user is showing tension or anxiety, the suggestions will be adjusted to be more reassuring or include approaches to reduce stress. 【0504】 The generated suggestions are sent to the user's device, where the user can review them. A re-analysis mechanism is used to dynamically adjust the suggestions, taking into account user feedback and associated emotional information. This allows for further fine-tuning based on the emotional state the user expressed in response to the suggestions. 【0505】 Specific example 【0506】 For example, if a user enters that they want a wedding that is "glamorous yet calming," the emotion engine will detect the user's subtle emotional response. If it recognizes that the user felt excited by a particular floral design, the server will generate suggestions that reflect that. On the other hand, if the user expresses anxiety about the background music suggestions, the system will add more relaxing music options to the list. 【0507】 In this way, the system, incorporating an emotion engine, provides an ideal wedding preparation process while being attentive to the user's emotions. Users receive more personalized support and, as a result, achieve a high level of satisfaction. 【0508】 The following describes the processing flow. 【0509】 Step 1: 【0510】 Users access the system through their devices and input personal information and wedding preferences in a questionnaire format. During this process, the device's camera and microphone are used to record the user's facial expressions and voice while they are inputting the information. 【0511】 Step 2: 【0512】 The device sends survey responses and recorded sentiment data to the server. The transmitted data is stored on the server as a dataset containing the user's basic information and sentiment. 【0513】 Step 3: 【0514】 The server analyzes the received data, and the emotion engine analyzes the user's facial expressions and tone of voice to determine their emotional state. For example, if the user is smiling, it identifies feelings such as joy, and if they are frowning, it identifies feelings such as dissatisfaction. 【0515】 Step 4: 【0516】 The analysis tool combines user preferences and emotional information to generate suggestions. For example, if a user expresses delight with a floral arrangement design, suggestions centered around that design will be generated. 【0517】 Step 5: 【0518】 The server generates suggestions and sends them to the terminal, presenting the suggestions to the user. The user reviews these suggestions through the terminal, and their emotional response to each suggestion is recorded again. 【0519】 Step 6: 【0520】 Users provide feedback on the proposal, and emotional information is sent from their device. This feedback includes specific requests and suggestions for changes. 【0521】 Step 7: 【0522】 The server's re-analysis mechanism adjusts suggestions based on the latest sentiment information and feedback. The adjusted suggestions are then regenerated to be in a format that best satisfies the user. 【0523】 Step 8: 【0524】 The finalized proposal is sent to the user's device for review and approval. Once approved, the necessary orders and reservations for wedding preparations are automatically arranged. 【0525】 (Example 2) 【0526】 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." 【0527】 In wedding planning, there is a lack of personalized suggestions that take into account the user's emotions. Therefore, there is a need for methodologies that can provide ideal wedding plans while reducing the anxiety and stress that users experience. 【0528】 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. 【0529】 In this invention, the server includes means for inputting information from the user and analyzing emotional information, means for storing the input information and emotional information, and means for analyzing the stored data and generating suggestions based on the user's emotions. This makes it possible to provide the user with a personalized wedding plan that is sensitive to their emotions. 【0530】 An "input method" is a means that has the ability to receive information related to weddings from users and analyze it, including emotional information. 【0531】 "Information storage means" refers to means of appropriately storing user input information and emotional information, and maintaining a state in which it can be used for subsequent analysis and suggestion generation. 【0532】 "Analysis means" refers to the means of performing the necessary processing to generate optimal wedding proposals based on stored user information and emotional data. 【0533】 "Output means" refers to means that have the function of providing the generated wedding proposals to the user and collecting feedback from the user. 【0534】 "Transmission means" refers to a means for effectively transmitting multiple suggestions generated by the analysis means to the user's terminal. 【0535】 A "re-analysis method" is a means of re-evaluating a proposal based on user feedback and emotional information, and processing it to make adjustments as necessary. 【0536】 The embodiment of this invention aims to assist in wedding preparations while taking the user's emotions into consideration. The system comprises a server, a terminal, and an emotion engine. The user inputs wedding information via the terminal, and based on this, the system provides personalized suggestions. 【0537】 The server uses Python-based natural language processing and machine learning models to process the input user data and sentiment information. Data analysis libraries such as TensorFlow and Pandas are used for processing. The sentiment engine is used to analyze facial expressions and voice tone, thereby detecting the user's subtle emotional state. 【0538】 For example, if a user inputs that they want a wedding with a "calm atmosphere," the emotion engine analyzes how the user feels about a particular piece of music. If, for instance, it detects that the user is feeling anxious while listening to a specific piece of background music, the server will select more relaxing music and add it to the suggestions. 【0539】 As an example of a prompt, you could input something like, "Generate a relaxing wedding plan based on the user's emotions," into the generation AI model to more effectively customize the suggestions. 【0540】 This technology allows users to receive wedding plans tailored to their individual emotional needs, enabling a high-quality and satisfying experience. 【0541】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0542】 Step 1: 【0543】 The user enters information. The user uses a device to enter their wishes and requests regarding the wedding. The information entered includes the theme, number of participants, budget, etc. The device receives this information, and an emotion engine analyzes the user's facial expressions and voice in real time, sending the emotion data to the server. 【0544】 Step 2: 【0545】 The server receives and stores the data. The server records the input information and sentiment data sent by the user and stores it appropriately using information storage means. This data is used as foundational data necessary for subsequent suggestion generation. 【0546】 Step 3: 【0547】 The server analyzes the data. Using analytical tools, the server performs a detailed analysis of stored user information and sentiment data. In this process, TensorFlow and Pandas in Python are used to identify data relationships and user sentiment tendencies, and the data is processed to generate optimal suggestions. The output consists of parameters and conditions used by the generative AI model. 【0548】 Step 4: 【0549】 The server generates proposals. Based on the analysis results, a generation AI model is used to generate wedding plans that match the user's emotions and desires. At this time, a prompt such as "Generate proposals for a relaxing wedding" is input to the AI ​​model. The generated proposals are the specific plans presented to the user. 【0550】 Step 5: 【0551】 Users review the proposals and provide feedback. Users check the proposals via their devices and evaluate how well they match their preferences. The evaluation is sent to the server via the device and stored as reference data for future proposal generation. 【0552】 Step 6: 【0553】 The server readjusts the suggestions. The server re-analyzes user feedback and newly collected sentiment information to improve the content of the suggestions. Using the re-analysis method, the AI ​​model updates the suggestions to better match the user's needs. The adjusted suggestions are sent back to the terminal for final confirmation by the user. 【0554】 (Application Example 2) 【0555】 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." 【0556】 Conventional event support systems have a problem in that they do not adequately adjust suggestions to take into account the user's emotions, resulting in insufficient recommendations for individual users. Furthermore, the accuracy of personalized suggestions is low, which leads to insufficient user satisfaction. 【0557】 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. 【0558】 In this invention, the server includes information acquisition means for acquiring user information, data storage means for storing the input information as data, and suggestion generation means for generating and adjusting suggestions based on the stored data and the user's emotions. This makes it possible to provide individually optimized suggestions that reflect the user's emotions. 【0559】 "Information acquisition methods" refer to the means of receiving information from users. They play a role in acquiring data related to users' emotions and requests. 【0560】 A "data storage method" is a means of properly storing acquired information. It is used for information management and preparation for subsequent analysis processing. 【0561】 A "proposal generation method" is a means of analyzing stored data and generating suggestions that respond to user requests and emotions. It executes a process to provide the user with the most suitable content. 【0562】 An "information output means" is a means of providing the generated suggestions to the user. It plays a role in conveying information through visual or auditory feedback. 【0563】 An "emotion analysis tool" is a means of recognizing and analyzing a user's emotions. It identifies the emotional state based on the input information and the user's responses. 【0564】 A "proposal adjustment mechanism" is a means of adaptively adjusting proposals generated based on the results of sentiment analysis. It dynamically changes the content of the proposals to improve user satisfaction. 【0565】 A "re-analysis mechanism" is a means of receiving user feedback and re-evaluating and adjusting the proposed content. It operates with the aim of providing the optimal proposal that aligns with the user's intentions. 【0566】 This invention provides a system that recognizes a user's emotions and makes personalized suggestions based on those emotions. The details of the system that implements this application are described below. 【0567】 The server first collects information from the user using information acquisition methods. For example, by having the user input their event requests and preferences, and capturing their facial expressions and tone of voice at that time, it is possible to understand their emotional state. The information is stored using data storage methods and referenced in subsequent processing as needed. 【0568】 Next, the information stored in the data storage means is analyzed using the suggestion generation means while performing user sentiment analysis. The sentiment analysis means constructs the most suitable suggestion for the situation based on the user's input information and sentiment data. The suggestion adjustment means plays the role of improving the suggestion content according to the analysis results, making it more appropriate to the user's requirements. 【0569】 Finally, the information output device provides the generated suggestions to the user's terminal and outputs the information using visual or auditory means. When the user provides feedback on the provided suggestions, this feedback is also taken into consideration by the re-analysis device and used to further improve the quality of future suggestions. 【0570】 This system can be installed in, for example, a home robot to help prepare for special events within the home (e.g., a birthday party). If the user inputs "I'd like a party with a calm atmosphere," the emotion analysis system will read the user's positive emotions and, based on that, suggest appropriate decorations and music. 【0571】 Examples of prompt messages include the following: 【0572】 "Please suggest ideas to liven up the party atmosphere. We'd like to know what kind of decorations and music would make users feel comfortable." 【0573】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0574】 Step 1: 【0575】 The user accesses the device and inputs their event preferences and requests into the information acquisition system. At this time, emotional data such as the user's facial expressions and tone of voice are also captured. The input information and emotional data become the output of this step and are passed on to the next process. 【0576】 Step 2: 【0577】 The server temporarily stores the received information and sentiment data using data storage means. This stored data becomes the basic dataset for analysis. Here, data processing is performed to consistently store the input user information and sentiment data. 【0578】 Step 3: 【0579】 The server retrieves the stored data and analyzes the information using a suggestion generation mechanism. In this data calculation, the user's emotional state is considered using an emotion analysis mechanism to generate suggestions best suited to the user's needs. Stored data is used as input to perform emotion recognition, deepening the understanding of the user. 【0580】 Step 4: 【0581】 Before providing suggestions to the user, a suggestion adjustment mechanism is activated. The server dynamically adjusts the generated suggestions based on the acquired sentiment data. In this step, the optimal suggestions are narrowed down using a generation AI model, preparing to output suggestions that contribute to improving user satisfaction. 【0582】 Step 5: 【0583】 The adjusted proposal is sent to the user's terminal via an information output device. The user reviews the proposal on their terminal and considers the event details through visual or audio feedback. The output in this step is proposal information in a format that is easily understandable to the user. 【0584】 Step 6: 【0585】 Users provide feedback on the suggestions they receive. The feedback information entered on the terminal is sent to the server and used for re-analysis to improve future suggestions. The input here includes the user's satisfaction level and further requests, which the server stores and analyzes for re-analysis. 【0586】 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. 【0587】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0588】 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. 【0589】 [Fourth Embodiment] 【0590】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0591】 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. 【0592】 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). 【0593】 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. 【0594】 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. 【0595】 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). 【0596】 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. 【0597】 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. 【0598】 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. 【0599】 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. 【0600】 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. 【0601】 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. 【0602】 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". 【0603】 The system implementing this invention is equipped with a generative AI designed to efficiently carry out wedding preparations. Below, an embodiment of the system and the processing flow of its program are described in natural language. 【0604】 User information input and data collection 【0605】 Users can input wedding-related information in a questionnaire format using devices such as smartphones and PCs. This information includes guest lists, wedding concepts, and preferred styles. This input information is transmitted from the device to a server via the internet and securely recorded by storage devices. 【0606】 Data analysis and proposal generation 【0607】 The server uses stored data to perform analysis. This analysis utilizes AI to analyze user input and automatically generates suggestions across multiple elements, such as costume recommendations, invitation designs, venue layouts, and background music selections. These suggestions are individually adjusted and optimized according to the user's preferences. 【0608】 Proposal submission and feedback reception 【0609】 The generated proposals are provided to the user via an output device. The user can review the proposals on their device and provide feedback on each element, offering opinions and requests. This feedback is further incorporated by a re-analysis device, and the server readjusts the proposals. Through this process, an optimal wedding plan that more closely matches the user's wishes is created. 【0610】 Specific example 【0611】 For example, if a user desires a "warm atmosphere incorporating the beauty of autumn nature," the system can suggest invitation designs with corresponding color schemes and present venue layouts using natural floral arrangements and wooden decorations. Furthermore, the system can automatically adjust meal plans, including vegetarian options, to suit the preferences of specific guests. 【0612】 In this way, this system highly automates various wedding preparations, allowing users to plan and execute their ideal wedding without feeling burdened by their busy daily lives. 【0613】 The following describes the processing flow. 【0614】 Step 1: 【0615】 Users access the survey form via their device and enter the required information. Specifically, they enter the date of the ceremony, guest list, concept, preferred colors and style, etc. 【0616】 Step 2: 【0617】 The terminal sends the entered information to the server. The transmitted data is stored in a database on the server and prepared for subsequent processing. 【0618】 Step 3: 【0619】 The server analyzes the received data and generates AI-generated suggestions based on the user's preferences and wedding concept. This analysis includes multiple elements such as attire, invitations, venue layout, and background music. 【0620】 Step 4: 【0621】 The server sends the generated suggestions to the user's device. The user then reviews these suggestions on their device and checks whether they match their preferences. 【0622】 Step 5: 【0623】 Users provide feedback on the proposal. This feedback can include specific requests, such as design changes or preferred options. 【0624】 Step 6: 【0625】 The server re-analyzes the data based on user feedback and adjusts the proposal. This re-analysis generates a final plan that reflects the user's requests. 【0626】 Step 7: 【0627】 The final proposal is sent to the terminal for the user to review and approve. If the user is satisfied at this step, the system proceeds to execute the necessary orders and preparations. 【0628】 (Example 1) 【0629】 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". 【0630】 In modern society, wedding preparations require a great deal of time and effort, and it is difficult to create the optimal plan from among many options. Therefore, there is a need for an efficient system that can meet the diverse and individual needs of various users. 【0631】 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. 【0632】 In this invention, the server includes a user input device, a storage device for storing the input information as an information set, and an analysis device for processing the recorded information and automatically generating suggestions that respond to the user's requests. This enables the automation, proposal, and optimization of appropriate wedding plans tailored to the individual user's wishes. 【0633】 "User device" refers to a device used by a user to input information, such as a smartphone or PC. 【0634】 A "storage device" is a device for storing input information as a collection of information, and typically uses a database to manage this information. 【0635】 An "analysis device" is a device that processes recorded information and automatically generates suggestions that respond to user requests, using machine learning algorithms to analyze data. 【0636】 A "providing device" is a device that provides the generated proposal to the user, and typically transmits the information via the internet so that the user can confirm it. 【0637】 A "re-analysis device" is a device used to adjust the proposed content based on the responses received from users, and it optimizes the proposal by analyzing the feedback. 【0638】 A "portable device" is a terminal that a user can carry with them, and this mainly includes smartphones and tablets. 【0639】 A "generative AI model" is an artificial intelligence model that analyzes data based on machine learning algorithms to generate and optimize suggestions. 【0640】 The system for implementing the invention is an information processing system designed to streamline the wedding planning process. The specific form of this system is described below. 【0641】 Users input wedding-related information using devices such as smartphones or PCs. These devices transmit this input information to a server via the internet. The server uses a database management system (DBMS) to securely record the received information for data storage. 【0642】 The server utilizes a generative AI model to analyze the recorded data. This AI model uses machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. Based on the analysis results, the server automatically generates various suggestions related to weddings. These suggestions include choices for attire, invitation designs, venue layouts, and background music selections. 【0643】 For example, if a user requests a "warm atmosphere incorporating the beauty of autumn nature," the server will propose a design that takes this request into account. A specific example of a prompt would be: "We are planning a wedding with a warm atmosphere incorporating the beauty of autumn nature. Please propose a plan that will satisfy our guests, using natural floral arrangements and wooden decorations, and including a vegetarian menu." 【0644】 This allows the server to provide users with their ideal wedding plan while optimizing the planning process with minimal effort. Users can efficiently create and optimize their plans without feeling burdened by their busy schedules. 【0645】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0646】 Step 1: 【0647】 Users input wedding-related information using devices such as smartphones and PCs. This information includes guest lists, wedding themes, and preferred styles. The entered data is sent to a server via the internet. Specifically, information is sent by operating the user interface on the device's form and pressing the "Submit" button. Input consists of options selected by the user, and output is the transfer of data to the server. 【0648】 Step 2: 【0649】 The server stores information received from the terminal using a database management system (DBMS). Here, data is securely recorded and managed. The server parses the received data in JSON format and stores the information in the appropriate tables. The input is data in JSON format, and the output is structured database entries. 【0650】 Step 3: 【0651】 The server utilizes a generative AI model to analyze the stored data. This involves using machine learning libraries such as TensorFlow and PyTorch to analyze user preferences and trends. This analysis generates feature vectors and automatically produces diverse suggestions through pattern matching. The input is structured data stored in a database, and the output is automatically generated wedding plan suggestions. 【0652】 Step 4: 【0653】 The server converts the generated proposals into HTML or PDF format and sends them to the terminal to provide them to the user. The terminal receives these and displays them in a format that the user can review. Specifically, the user can review each proposal by displaying the data from the server in a browser or PDF viewer. The input is proposal data generated by an AI model, and the output is a visually presented plan. 【0654】 Step 5: 【0655】 The user sends feedback on the proposal to the server via their device. The server incorporates this feedback using a re-analysis mechanism and readjusts the proposal. This results in the provision of an optimal proposal that reflects the user's opinion. Specifically, the process is completed by entering feedback using the feedback form on the device and pressing the "Send" button again. The input is the user's feedback information, and the output is the improved proposal data. 【0656】 (Application Example 1) 【0657】 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". 【0658】 Currently, wedding planning involves many steps, requiring users to invest a significant amount of time and effort. Furthermore, the difficulty in visualizing proposals makes it challenging for users to fully understand and make informed decisions. Additionally, there is a need to quickly and efficiently incorporate user feedback. A method is needed to address these challenges and enable user-friendly, intuitive planning by utilizing a virtual reality environment. 【0659】 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. 【0660】 In this invention, the server includes acquisition means for obtaining information from the user, storage means for storing the acquired information as data, analysis means for analyzing the stored data and creating suggestions based on the user's requests, display means for providing a virtual reality environment, detection means for detecting the user's actions within the virtual reality environment, and collection means for collecting feedback through the virtual reality environment. This allows the user to visually experience the suggested content using the virtual reality environment and provide rapid feedback. The user's feedback is immediately reflected in the suggestions, enabling more personalized wedding planning. 【0661】 "Means of acquisition" refers to the part equipped with functions for collecting information from users. 【0662】 A "storage mechanism" is a system for safely and efficiently storing collected data. 【0663】 "Analysis means" refers to a method for analyzing stored data and generating suggestions that meet user requirements. 【0664】 A "display means" is a device that allows a user to access a virtual reality environment and visually confirm the proposed content. 【0665】 "Detection means" refers to technologies for identifying user actions and operations within a virtual reality environment. 【0666】 "Methods of data collection" refers to methods for obtaining user feedback and using that feedback to improve the proposed content. 【0667】 The system implementing this invention is designed to efficiently carry out wedding preparations in a virtual reality environment. Users can input wedding-related information as data using their own devices and visually confirm the plan generated through the virtual environment. 【0668】 The server uses acquisition means to obtain information from the user. The acquired information is securely stored by retention means. The stored data is analyzed using analysis means, and specific suggestions based on the user's requests are generated by a generative AI model. For example, based on the wedding theme and guest list, optimal venue design, decoration plan, and catering plan are proposed. 【0669】 Users can experience these suggestions within a virtual reality environment via display means and directly manipulate the visualized results in the virtual space. The system uses detection means to identify user actions and operations, enabling real-time interaction within the virtual environment. User feedback is collected by collection means and immediately used to readjust the suggestions. 【0670】 The hardware used includes VR head-mounted displays and high-spec PCs, while the software utilizes Unity (game engine), Python, and TensorFlow. This allows users to intuitively understand and customize the overall picture of their wedding through an immersive experience. 【0671】 For example, if a user requests a wedding with a "warm atmosphere themed around autumn nature," the generating AI model will suggest venue color schemes and material selections accordingly. The user can then review the plan presented in virtual reality and provide feedback such as, "I'd like to change this material to something else." 【0672】 An example of a prompt to input into the generating AI model would be: "Please suggest relevant color schemes and materials so that the user can experience a wedding venue decoration design themed around autumn nature in VR. Also, update it immediately based on any changes in feedback." 【0673】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0674】 Step 1: 【0675】 The user enters wedding-related information via a terminal. This input data includes the number of guests, the wedding theme, and preferred style. This information is transmitted from the terminal to the server via a data acquisition method. The data obtained from the input is then pre-formatted for storage. 【0676】 Step 2: 【0677】 The server stores the acquired user information in cloud storage using a retention mechanism. During storage, the data is encrypted or compressed as needed. The stored information is saved in a structured format so that it can be used for later analysis. 【0678】 Step 3: 【0679】 Based on the stored data, the server performs data analysis using Python and TensorFlow scripts as analytical tools. This allows the generative AI model to generate appropriate wedding plans. The analysis process outputs suggestions that reflect the user's preferences. 【0680】 Step 4: 【0681】 The server provides the generated proposals to the user through a display mechanism. Specifically, a VR environment is built using the Unity engine, and the proposed wedding designs and layouts are visually displayed within it. The user views this through a head-mounted display. 【0682】 Step 5: 【0683】 Users try out the displayed virtual reality suggestions and provide feedback. This feedback is recorded by detection devices that track actions within the virtual environment and directly input from the user into a data collection system. This feedback clarifies requests and opinions regarding the suggestions. 【0684】 Step 6: 【0685】 The server re-analyzes the feedback collected from users and generates new suggestions. The re-analysis process processes the data according to the user's requested changes, leading to the optimal suggestion. As a result, a more satisfying plan is provided to the user. 【0686】 Step 7: 【0687】 Finally, the refined proposal is presented to the user for approval. The approved plan is then output as a detailed plan for implementation. This prepares the user to concretely carry out their planned wedding. 【0688】 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. 【0689】 The system in this invention is a wedding preparation support system that incorporates an emotion engine that recognizes the user's emotions. The following describes in detail how this system is implemented. 【0690】 System Configuration 【0691】 The system has a complex structure that includes a user terminal, a server, and an emotion engine. The user uses the terminal to input information necessary for their wedding and communicates their requests and preferences in a questionnaire format. The emotion engine analyzes the user's facial expressions, tone of voice, and word choice during input and when reviewing suggestions to identify their emotions. This emotion information is transferred to the server and used by the analysis system. 【0692】 Program processing 【0693】 The server analyzes the user's input data, including emotional information received from the emotion engine. The analysis then works to generate more effective and appropriate suggestions based on the user's emotions. For example, if the user is showing tension or anxiety, the suggestions will be adjusted to be more reassuring or include approaches to reduce stress. 【0694】 The generated suggestions are sent to the user's device, where the user can review them. A re-analysis mechanism is used to dynamically adjust the suggestions, taking into account user feedback and associated emotional information. This allows for further fine-tuning based on the emotional state the user expressed in response to the suggestions. 【0695】 Specific example 【0696】 For example, if a user enters that they want a wedding that is "glamorous yet calming," the emotion engine will detect the user's subtle emotional response. If it recognizes that the user felt excited by a particular floral design, the server will generate suggestions that reflect that. On the other hand, if the user expresses anxiety about the background music suggestions, the system will add more relaxing music options to the list. 【0697】 In this way, the system, incorporating an emotion engine, provides an ideal wedding preparation process while being attentive to the user's emotions. Users receive more personalized support and, as a result, achieve a high level of satisfaction. 【0698】 The following describes the processing flow. 【0699】 Step 1: 【0700】 Users access the system through their devices and input personal information and wedding preferences in a questionnaire format. During this process, the device's camera and microphone are used to record the user's facial expressions and voice while they are inputting the information. 【0701】 Step 2: 【0702】 The device sends survey responses and recorded sentiment data to the server. The transmitted data is stored on the server as a dataset containing the user's basic information and sentiment. 【0703】 Step 3: 【0704】 The server analyzes the received data, and the emotion engine analyzes the user's facial expressions and tone of voice to determine their emotional state. For example, if the user is smiling, it identifies feelings such as joy, and if they are frowning, it identifies feelings such as dissatisfaction. 【0705】 Step 4: 【0706】 The analysis tool combines user preferences and emotional information to generate suggestions. For example, if a user expresses delight with a floral arrangement design, suggestions centered around that design will be generated. 【0707】 Step 5: 【0708】 The server generates suggestions and sends them to the terminal, presenting the suggestions to the user. The user reviews these suggestions through the terminal, and their emotional response to each suggestion is recorded again. 【0709】 Step 6: 【0710】 Users provide feedback on the proposal, and emotional information is sent from their device. This feedback includes specific requests and suggestions for changes. 【0711】 Step 7: 【0712】 The server's re-analysis mechanism adjusts suggestions based on the latest sentiment information and feedback. The adjusted suggestions are then regenerated to be in a format that best satisfies the user. 【0713】 Step 8: 【0714】 The finalized proposal is sent to the user's device for review and approval. Once approved, the necessary orders and reservations for wedding preparations are automatically arranged. 【0715】 (Example 2) 【0716】 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". 【0717】 In wedding planning, there is a lack of personalized suggestions that take into account the user's emotions. Therefore, there is a need for methodologies that can provide ideal wedding plans while reducing the anxiety and stress that users experience. 【0718】 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. 【0719】 In this invention, the server includes means for inputting information from the user and analyzing emotional information, means for storing the input information and emotional information, and means for analyzing the stored data and generating suggestions based on the user's emotions. This makes it possible to provide the user with a personalized wedding plan that is sensitive to their emotions. 【0720】 An "input method" is a means that has the ability to receive information related to weddings from users and analyze it, including emotional information. 【0721】 "Information storage means" refers to means of appropriately storing user input information and emotional information, and maintaining a state in which it can be used for subsequent analysis and suggestion generation. 【0722】 "Analysis means" refers to the means of performing the necessary processing to generate optimal wedding proposals based on stored user information and emotional data. 【0723】 "Output means" refers to means that have the function of providing the generated wedding proposals to the user and collecting feedback from the user. 【0724】 "Transmission means" refers to a means for effectively transmitting multiple suggestions generated by the analysis means to the user's terminal. 【0725】 A "re-analysis method" is a means of re-evaluating a proposal based on user feedback and emotional information, and processing it to make adjustments as necessary. 【0726】 The embodiment of this invention aims to assist in wedding preparations while taking the user's emotions into consideration. The system comprises a server, a terminal, and an emotion engine. The user inputs wedding information via the terminal, and based on this, the system provides personalized suggestions. 【0727】 The server uses Python-based natural language processing and machine learning models to process the input user data and sentiment information. Data analysis libraries such as TensorFlow and Pandas are used for processing. The sentiment engine is used to analyze facial expressions and voice tone, thereby detecting the user's subtle emotional state. 【0728】 For example, if a user inputs that they want a wedding with a "calm atmosphere," the emotion engine analyzes how the user feels about a particular piece of music. If, for instance, it detects that the user is feeling anxious while listening to a specific piece of background music, the server will select more relaxing music and add it to the suggestions. 【0729】 As an example of a prompt, you could input something like, "Generate a relaxing wedding plan based on the user's emotions," into the generation AI model to more effectively customize the suggestions. 【0730】 This technology allows users to receive wedding plans tailored to their individual emotional needs, enabling a high-quality and satisfying experience. 【0731】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0732】 Step 1: 【0733】 The user enters information. The user uses a device to enter their wishes and requests regarding the wedding. The information entered includes the theme, number of participants, budget, etc. The device receives this information, and an emotion engine analyzes the user's facial expressions and voice in real time, sending the emotion data to the server. 【0734】 Step 2: 【0735】 The server receives and stores the data. The server records the input information and sentiment data sent by the user and stores it appropriately using information storage means. This data is used as foundational data necessary for subsequent suggestion generation. 【0736】 Step 3: 【0737】 The server analyzes the data. Using analytical tools, the server performs a detailed analysis of stored user information and sentiment data. In this process, TensorFlow and Pandas in Python are used to identify data relationships and user sentiment tendencies, and the data is processed to generate optimal suggestions. The output consists of parameters and conditions used by the generative AI model. 【0738】 Step 4: 【0739】 The server generates proposals. Based on the analysis results, a generation AI model is used to generate wedding plans that match the user's emotions and desires. At this time, a prompt such as "Generate proposals for a relaxing wedding" is input to the AI ​​model. The generated proposals are the specific plans presented to the user. 【0740】 Step 5: 【0741】 Users review the proposals and provide feedback. Users check the proposals via their devices and evaluate how well they match their preferences. The evaluation is sent to the server via the device and stored as reference data for future proposal generation. 【0742】 Step 6: 【0743】 The server readjusts the suggestions. The server re-analyzes user feedback and newly collected sentiment information to improve the content of the suggestions. Using the re-analysis method, the AI ​​model updates the suggestions to better match the user's needs. The adjusted suggestions are sent back to the terminal for final confirmation by the user. 【0744】 (Application Example 2) 【0745】 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". 【0746】 Conventional event support systems have a problem in that they do not adequately adjust suggestions to take into account the user's emotions, resulting in insufficient recommendations for individual users. Furthermore, the accuracy of personalized suggestions is low, which leads to insufficient user satisfaction. 【0747】 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. 【0748】 In this invention, the server includes information acquisition means for acquiring user information, data storage means for storing the input information as data, and suggestion generation means for generating and adjusting suggestions based on the stored data and the user's emotions. This makes it possible to provide individually optimized suggestions that reflect the user's emotions. 【0749】 "Information acquisition methods" refer to the means of receiving information from users. They play a role in acquiring data related to users' emotions and requests. 【0750】 A "data storage method" is a means of properly storing acquired information. It is used for information management and preparation for subsequent analysis processing. 【0751】 A "proposal generation method" is a means of analyzing stored data and generating suggestions that respond to user requests and emotions. It executes a process to provide the user with the most suitable content. 【0752】 An "information output means" is a means of providing the generated suggestions to the user. It plays a role in conveying information through visual or auditory feedback. 【0753】 An "emotion analysis tool" is a means of recognizing and analyzing a user's emotions. It identifies the emotional state based on the input information and the user's responses. 【0754】 A "proposal adjustment mechanism" is a means of adaptively adjusting proposals generated based on the results of sentiment analysis. It dynamically changes the content of the proposals to improve user satisfaction. 【0755】 A "re-analysis mechanism" is a means of receiving user feedback and re-evaluating and adjusting the proposed content. It operates with the aim of providing the optimal proposal that aligns with the user's intentions. 【0756】 This invention provides a system that recognizes a user's emotions and makes personalized suggestions based on those emotions. The details of the system that implements this application are described below. 【0757】 The server first collects information from the user using information acquisition methods. For example, by having the user input their event requests and preferences, and capturing their facial expressions and tone of voice at that time, it is possible to understand their emotional state. The information is stored using data storage methods and referenced in subsequent processing as needed. 【0758】 Next, the information stored in the data storage means is analyzed using the suggestion generation means while performing user sentiment analysis. The sentiment analysis means constructs the most suitable suggestion for the situation based on the user's input information and sentiment data. The suggestion adjustment means plays the role of improving the suggestion content according to the analysis results, making it more appropriate to the user's requirements. 【0759】 Finally, the information output device provides the generated suggestions to the user's terminal and outputs the information using visual or auditory means. When the user provides feedback on the provided suggestions, this feedback is also taken into consideration by the re-analysis device and used to further improve the quality of future suggestions. 【0760】 This system can be installed in, for example, a home robot to help prepare for special events within the home (e.g., a birthday party). If the user inputs "I'd like a party with a calm atmosphere," the emotion analysis system will read the user's positive emotions and, based on that, suggest appropriate decorations and music. 【0761】 Examples of prompt messages include the following: 【0762】 "Please suggest ideas to liven up the party atmosphere. We'd like to know what kind of decorations and music would make users feel comfortable." 【0763】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0764】 Step 1: 【0765】 The user accesses the device and inputs their event preferences and requests into the information acquisition system. At this time, emotional data such as the user's facial expressions and tone of voice are also captured. The input information and emotional data become the output of this step and are passed on to the next process. 【0766】 Step 2: 【0767】 The server temporarily stores the received information and sentiment data using data storage means. This stored data becomes the basic dataset for analysis. Here, data processing is performed to consistently store the input user information and sentiment data. 【0768】 Step 3: 【0769】 The server retrieves the stored data and analyzes the information using a suggestion generation mechanism. In this data calculation, the user's emotional state is considered using an emotion analysis mechanism to generate suggestions best suited to the user's needs. Stored data is used as input to perform emotion recognition, deepening the understanding of the user. 【0770】 Step 4: 【0771】 Before providing suggestions to the user, a suggestion adjustment mechanism is activated. The server dynamically adjusts the generated suggestions based on the acquired sentiment data. In this step, the optimal suggestions are narrowed down using a generation AI model, preparing to output suggestions that contribute to improving user satisfaction. 【0772】 Step 5: 【0773】 The adjusted proposal is sent to the user's terminal via an information output device. The user reviews the proposal on their terminal and considers the event details through visual or audio feedback. The output in this step is proposal information in a format that is easily understandable to the user. 【0774】 Step 6: 【0775】 Users provide feedback on the suggestions they receive. The feedback information entered on the terminal is sent to the server and used for re-analysis to improve future suggestions. The input here includes the user's satisfaction level and further requests, which the server stores and analyzes for re-analysis. 【0776】 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. 【0777】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0778】 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 robot 414. 【0779】 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. 【0780】 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. 【0781】 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. 【0782】 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. 【0783】 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. 【0784】 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." 【0785】 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. 【0786】 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. 【0787】 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. 【0788】 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. 【0789】 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. 【0790】 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. 【0791】 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. 【0792】 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. 【0793】 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. 【0794】 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. 【0795】 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. 【0796】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0797】 The following is further disclosed regarding the embodiments described above. 【0798】 (Claim 1) 【0799】 An input method for receiving information from the user, 【0800】 A storage means for saving the input information as data, 【0801】 An analysis means that analyzes stored data and generates suggestions that respond to user requests, 【0802】 An output means for providing the generated suggestions to the user, 【0803】 A system that includes this. 【0804】 (Claim 2) 【0805】 The system according to claim 1, comprising an analysis means for generating multiple suggestions based on user preferences, and a means for transmitting each suggestion to the user's mobile terminal. 【0806】 (Claim 3) 【0807】 The system according to claim 1, further comprising a reanalysis means for receiving user feedback and adjusting the proposed content. 【0808】 "Example 1" 【0809】 (Claim 1) 【0810】 A user-facing device for inputting information from users, 【0811】 A storage device that stores the input information as an information set, 【0812】 An analysis device that processes recorded information and automatically generates suggestions that respond to user requests, 【0813】 A device that provides the generated proposals to the user, 【0814】 A re-analysis device that receives feedback from users and adjusts the proposed content, 【0815】 An information processing system that includes this. 【0816】 (Claim 2) 【0817】 The information processing system according to claim 1, comprising an analysis device that generates multiple suggestions based on the user's preferences, and a device that transmits each suggestion to the user's mobile device. 【0818】 (Claim 3) 【0819】 The information processing system according to claim 1, further comprising an analysis device that analyzes a stored set of information using a generative AI model and optimizes each proposal. 【0820】 "Application Example 1" 【0821】 (Claim 1) 【0822】 A means of obtaining information from users, 【0823】 A means for storing the acquired information as data, 【0824】 An analytical tool that analyzes retained data and generates suggestions based on user requests, 【0825】 A means of presenting the generated proposals to users, 【0826】 A display means for providing a virtual reality environment, 【0827】 A detection means for detecting user behavior within a virtual reality environment, 【0828】 A means of collecting feedback through a virtual reality environment, 【0829】 A system that includes this. 【0830】 (Claim 2) 【0831】 The system according to claim 1, comprising an analytical means for generating multiple suggestions based on user preferences, a means for enabling operation in a virtual environment, and a means for transmitting each suggestion to the user's mobile terminal. 【0832】 (Claim 3) 【0833】 The system according to claim 1, further comprising a means for obtaining user feedback and reanalyzing the proposed content to adjust it, and a means for optimizing the proposed content using an experience in a virtual environment. 【0834】 "Example 2 of combining an emotion engine" 【0835】 (Claim 1) 【0836】 An input method that takes user information and analyzes emotional information in real time, 【0837】 Information storage means for storing input information and emotional information as data, 【0838】 An analytical means that analyzes stored data and generates suggestions based on the user's emotions, 【0839】 An output means for providing the generated suggestions to the user and collecting feedback, 【0840】 A system that includes this. 【0841】 (Claim 2) 【0842】 The system according to claim 1, comprising a transmission means for generating multiple suggestions optimized according to the user's emotions and sending them to the user's terminal. 【0843】 (Claim 3) 【0844】 The system according to claim 1, further comprising a reanalysis means for receiving user feedback and sentiment information and dynamically adjusting the suggested content. 【0845】 "Application example 2 of combining emotional engines" 【0846】 (Claim 1) 【0847】 A means of acquiring information for inputting information from the user, 【0848】 A data storage means for saving the input information as data, 【0849】 A proposal generation means that analyzes stored data to generate proposals that respond to user requests, 【0850】 An information output means for providing the generated proposal to the user, 【0851】 A means of analyzing user emotions, 【0852】 A proposal adjustment method that adjusts proposals based on the results of sentiment analysis, 【0853】 A system that includes this. 【0854】 (Claim 2) 【0855】 The system according to claim 1, comprising information provision means for generating multiple suggestions based on user preferences and transmitting them to the user's mobile information terminal. 【0856】 (Claim 3) 【0857】 The system according to claim 1, further comprising a reanalysis means for receiving user feedback and dynamically adjusting the proposed content. [Explanation of symbols] 【0858】 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] An input method for receiving information from the user, A storage means for saving the input information as data, An analysis means that analyzes stored data and generates suggestions that respond to user requests, An output means for providing the generated suggestions to the user, A system that includes this. [Claim 2] The system according to claim 1, comprising an analysis means for generating multiple suggestions based on user preferences, and a means for transmitting each suggestion to the user's mobile terminal. [Claim 3] The system according to claim 1, further comprising a reanalysis means for receiving user feedback and adjusting the proposed content.

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