system

Abstract

We provide the system. [Solution] A generation method that analyzes user input information and generates a travel plan, A proposal system that suggests accommodation, transportation, meals, and activities based on analyzed information, The proposed plan details will be shared via communication methods, and support measures will be provided to assist with payment. A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Unexamined Patent Application Publication No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 There is a problem that the process of planning a trip or a meal is complicated and many information sources have to be referred to. Since users need to spend time and effort adjusting each element, stress and errors associated with the planning are likely to occur. Also, there is a problem that it is difficult to easily find an optimal plan corresponding to individual desires, and the efficiency and flexibility of the planning are insufficient. 【Means for Solving the Problems】 【0005】 This invention simplifies the planning process by providing a generation means that generates travel plans by analyzing user input information. Furthermore, it presents the user with an optimal plan through a suggestion means that proposes various options for accommodation, transportation, meals, and activities based on the analyzed information. By easily sharing the plan via communication means and supporting payment, the process from planning to execution is made seamless. It also has a function to regenerate the suggested content based on user feedback and suggests clothing and items to bring considering weather information, thereby increasing the flexibility and accuracy of plans to meet diverse needs. 【0006】 "User input information" refers to data including user requests and conditions related to travel and meal planning. 【0007】 "Analysis" is the process of information processing that involves understanding information provided by the user and extracting the necessary elements. 【0008】 "Generation means" refers to a function that automatically creates travel plan options based on user input information. 【0009】 The "proposal means" refers to a part of a system that presents generated travel plans to users and offers options including accommodation, transportation, meals, and activities. 【0010】 "Communication methods" refer to technologies and functions that enable users to share travel plans and exchange information with each other. 【0011】 "Support measures" refer to support functions that facilitate the confirmation and payment of travel plans. 【0012】 "Feedback" refers to the opinions and suggestions for improvement that users provide regarding a proposed plan. 【0013】 "Regeneration" is the process of updating or modifying travel plans based on user feedback to present new options. 【0014】 "Weather information" refers to meteorological data considered for efficient travel planning. 【0015】 "Clothing and items" refer to clothing and items recommended based on the climate at the travel destination and the planned activities. 【Brief Description of Drawings】 【0016】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple 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 Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined. 【Mode for Carrying Out the Invention】 【0017】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0018】 First, the language used in the following description will be explained. 【0019】 In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0020】 In the following embodiments, the signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0021】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0022】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0023】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0024】 [First Embodiment] 【0025】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0026】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0027】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0028】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0029】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0030】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0031】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0032】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0033】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0034】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0035】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0036】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0037】 This invention is a system that allows users to efficiently plan trips and meals. Users input their travel requests and conditions through a specific interface. This information is received and analyzed by a server. The server uses natural language processing technology to break down the user's input into categories and extract the elements necessary for travel planning. 【0038】 The server uses a generative AI model to build a travel plan based on the extracted elements. This plan includes accommodation, transportation, dining options, and activities, gathering information by referencing internal databases and external APIs. Furthermore, the server integrates the latest weather information to suggest appropriate clothing and items to bring to the user. This information is automatically adjusted based on the user's travel destination and planned activities. 【0039】 The generated plan is presented to the user by the server, and the user can view its contents via chat, LINE, etc. The user can review the proposed plan and return any revisions or feedback to the server. The server receives the feedback, regenerates the plan if necessary, and makes a new proposal. 【0040】 After the user finally confirms their plan, the device provides functionality to share that plan and also assists with payment by allowing users to split expenses with companions using payment methods such as PayPay. 【0041】 For example, if a user requests, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person," the server analyzes the request and suggests suitable beach resorts, surrounding facilities, activities, and access methods. It also provides optimal options based on the budget and offers clothing suggestions based on the weather. In this way, it is possible to efficiently create flexible travel plans that meet the user's wishes. 【0042】 The following describes the processing flow. 【0043】 Step 1: 【0044】 Users enter and submit their travel and dining preferences through a chat interface. For example, they might enter specific requests such as, "I'd like to go see the autumn leaves, but my budget is 10,000 yen per person." 【0045】 Step 2: 【0046】 The server receives the user's input message. Using a natural language processing engine, it parses the message and extracts elements such as destination, budget, and schedule. 【0047】 Step 3: 【0048】 Based on the information extracted by the server, it generates a travel plan that includes appropriate accommodations, transportation, dining options, and activities, referencing internal databases and external APIs. It also obtains the latest weather information and recommends appropriate clothing and items to bring. 【0049】 Step 4: 【0050】 The server generates a travel plan and presents it to the user. The plan results are sent to the user via chat or LINE, and the details of each option are explained. 【0051】 Step 5: 【0052】 Users review the proposed plan and submit feedback if they have any new requests or changes. They might specify a particular request, such as "I'd like to reduce accommodation costs." 【0053】 Step 6: 【0054】 The server receives feedback from the user and regenerates the travel plan. It adjusts the plan, taking into account specified conditions and new requests. If necessary, it proposes new options again. 【0055】 Step 7: 【0056】 The user reviews the proposed plan and confirms its contents once they are satisfied. They can then share the plan using LINE. 【0057】 Step 8: 【0058】 The device supports PayPay payments based on the travel plan presented to the user. It also provides a function to split expenses with travel companions and simplify the payment process. 【0059】 (Example 1) 【0060】 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." 【0061】 In modern times, planning trips and meals often requires significant time and effort for gathering information and constructing plans, making it particularly difficult to quickly create plans that take into account diverse conditions and requests. Furthermore, providing appropriate suggestions based on the weather at the travel destination and the user's budget is not easy. Therefore, the present invention aims to efficiently automate these planning processes and quickly provide optimal plans tailored to the user's needs. 【0062】 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. 【0063】 In this invention, the server includes means for analyzing user input information and extracting travel planning elements using natural language processing technology; means for generating a travel plan using a generative artificial intelligence model based on the analyzed elements; means for suggesting accommodation, transportation, meals, and activities by referring to an internal database and external information acquisition means; means for suggesting clothing and belongings by integrating weather information; and means for providing the generated travel plan to the user via communication means and supporting payment processing. This enables the user to quickly and flexibly generate an optimal travel plan that meets their individual needs and to proceed with planning efficiently. 【0064】 "User input information" refers to data regarding travel and dining conditions, preferences, and requests provided by users through a dedicated interface. 【0065】 "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to efficiently analyze user input and extract meaning. 【0066】 "Travel planning elements" refer to information necessary to create a travel plan, such as destination, itinerary, budget, and activities. 【0067】 A "generative artificial intelligence model" is an algorithm or program that generates text or data based on input data, and is used to autonomously construct proposed content. 【0068】 An "internal database" is a collection of information stored within the system, including historical data and registered items necessary for generating plans. 【0069】 "Means of acquiring external information" refers to mechanisms and methods for obtaining necessary information from external data sources, and includes the use of APIs and web services. 【0070】 "Accommodation, transportation, meals, and activities" refer to the various options and services offered to the user in a travel plan, and each element is a factor that constitutes the overall plan. 【0071】 "Weather information" refers to local weather data that should be considered when planning a trip, and is used to adjust clothing and activity plans. 【0072】 "Communication methods" refer to the methods and technologies used to transmit generated plans to users, including email, messaging services, and application notifications. 【0073】 "Means to support payment processing" refers to mechanisms that facilitate payments related to travel planned by users, and include payment services and bill-splitting functions. 【0074】 This invention is a system that helps users efficiently plan trips and meals. Users input their travel destination, budget, itinerary, and other requirements in text format using a dedicated application installed on their smartphone or computer. This input information is then transmitted to the server as "user input information." 【0075】 The server uses "natural language processing techniques" to analyze this input information. Common natural language processing libraries (e.g., Python's NLTK or spaCy) can be used here. The server then extracts elements of the travel plan and prepares them for further processing. 【0076】 Based on the extracted data, the server generates travel plans using a "generative artificial intelligence model." Specific models that can be used include, for example, deep learning-based text generation models (e.g., OpenAI's GPT series). The model is pre-trained on a large amount of travel-related information and creates the optimal plan tailored to the user's needs. 【0077】 Furthermore, the server utilizes both an "internal database" and "external information acquisition methods" to gather necessary information. The internal database stores past travel plans and information on popular tourist destinations. External data is obtained using specific APIs (e.g., travel site APIs and weather information APIs). 【0078】 The generated plan includes accommodation, transportation, meal options, and activity suggestions. The server also takes weather information into account and suggests appropriate clothing and items to bring. 【0079】 The completed plan will be provided to the user via "communication methods." Specifically, the plan details will be sent via the messaging service or email used by the user. Furthermore, "payment processing support methods" will be included to facilitate payment processing and assist in cost sharing among companions. 【0080】 As a concrete example, a user can send a request to the system using a prompt statement like the following: 【0081】 "I want to go to the beach for my summer vacation trip. I'm thinking of a budget of under 20,000 yen per person." 【0082】 By using this system, users can quickly generate travel plans tailored to their individual needs and effectively prepare for their trips. 【0083】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0084】 Step 1: 【0085】 Users enter their travel and dining requests using a dedicated application. This input is sent to the application as text prompts. Specifically, a user might enter a request such as, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person." This input data serves as the starting point for system processing. 【0086】 Step 2: 【0087】 The server receives prompt messages from the user and parses them using natural language processing techniques. Here, a text analysis library is used to segment the information and extract travel planning elements such as "destination," "budget," and "dates." The input is the prompt message, and the output is a set of parsed elements. This analysis allows the user's requests to be stored on the server as structured data. 【0088】 Step 3: 【0089】 The server generates travel plans using a generative artificial intelligence model based on elements extracted through natural language processing. Specifically, it leverages a dataset pre-trained by a machine learning model to propose plans that match the user's criteria. The input is a set of analyzed elements, and the output is the generated travel plan. The generative artificial intelligence model generates the text necessary for creating the plan and elaborates on the proposed content. 【0090】 Step 4: 【0091】 The server supplements the plan generated for presentation to the user using an internal database and external information retrieval methods. Specifically, it collects information such as accommodation, transportation, dining options, and weather data. The input is a provisional travel plan, and the output is a detailed, completed final plan. Information is retrieved in real time via external APIs and reflected in the plan. 【0092】 Step 5: 【0093】 The server uses communication methods to deliver the final travel plan to the user. Here, content is sent via the user's preferred messaging service or email. The input is the detailed, completed final plan, and the output is the travel plan information provided to the user. The user can review the received plan and send feedback to the server if necessary. 【0094】 Step 6: 【0095】 When a user submits feedback on a provided plan, the server analyzes the feedback and regenerates the plan based on the new conditions. The input is the user's feedback, and the output is the updated travel plan. The server then presents the regenerated plan to the user again and repeats the process to provide the best possible recommendation. 【0096】 (Application Example 1) 【0097】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0098】 In today's world, planning trips and outings involves researching vast amounts of information individually and combining the best options, a time-consuming and laborious task. Furthermore, a system that can flexibly accommodate changes and adjustments to plans is needed. Additionally, plan development must consider practical factors such as environmental conditions and budget constraints. Therefore, the challenge lies in providing a system that effectively and efficiently creates travel plans according to user needs, while also managing costs and considering environmental factors. 【0099】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0100】 In this invention, the server includes an automatic generation means for analyzing user requirements and generating a travel plan, a recommendation means for suggesting accommodations, transportation, meal options, and activities based on the analyzed information, a payment means for sharing the suggested travel content and assisting with financial settlement, and an environment adaptation means for integrating weather information into the travel plan and guiding users on appropriate clothing and belongings. As a result, users can easily create a travel plan that can be managed as a whole based on their requests entered once, enabling real-time adjustments and optimal resource allocation. 【0101】 "An automated generation method that analyzes user requirements and generates travel plans" refers to a function that interprets the travel requests and conditions entered by the user and mechanically creates an overall travel plan based on them. 【0102】 "Recommendation methods that suggest accommodations, transportation, dining options, and activities based on analyzed information" refers to a function that can effectively select and present hotels, transportation, dining options, and activities necessary for travel, based on interpreted user request data. 【0103】 "A payment method that shares proposed travel itineraries and supports financial settlement" refers to a function that allows users to share generated travel plans with travel companions and others, and supports payment procedures for easily processing and managing travel-related expenses. 【0104】 "An environmental adaptation tool that integrates weather information into travel plans and guides users on appropriate clothing and belongings" refers to a function that incorporates weather data for the planned travel destination into the travel plan and guides users on what clothes to wear and what items to carry accordingly. 【0105】 The specific system for implementing this invention is designed to allow users to easily create travel plans. Users launch a dedicated application on their smart device and input specific requirements such as travel destination, budget, and desired activities. 【0106】 The server processes the information received from the user using the Google® Cloud NLP API to extract key attributes. Based on this information, the server generates a travel plan using the OpenAI GPT API. The generated plan includes accommodation, transportation, meal options, and activities. 【0107】 Weather data is collected via the Weather API and integrated into travel plans. This allows the server to guide users on appropriate clothing and items to bring. The suggested plan can also be easily shared with travel companions. Payments are made via electronic payment functions available on the device. 【0108】 For example, if a user enters into the application that they "want to plan a family trip to Kyoto during spring break," the server will suggest family-friendly accommodations, tourist attractions, and Japanese restaurants in Kyoto. It will also provide advice on appropriate clothing for the spring weather. 【0109】 An example of a prompt to input into the generating AI model would be: "Create a suitable travel plan based on the following information: destination is Kyoto, family of 4, budget is under 100,000 yen, accommodation is 2 nights and 3 days, meals will be mainly Japanese." 【0110】 In this way, users can efficiently create complex travel plans and enjoy a comfortable and harmonious travel experience based on the suggestions provided. 【0111】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0112】 Step 1: 【0113】 The user uses the terminal's application to enter details about their travel destination, budget, and desired activities. This entered information is then sent to the system. Specifically, the user provides the necessary information through text boxes or voice input, and the terminal's communication module transmits it to the server. 【0114】 Step 2: 【0115】 The server analyzes the user's input information using the Google Cloud NLP API to extract important keywords and phrases. The input data is processed in text format, and travel-related elements (destination, budget, activities) are extracted. This analysis identifies specific travel needs. 【0116】 Step 3: 【0117】 The server invokes the OpenAI GPT API based on the analyzed information and uses a generative AI model to create a travel plan. By generating specific prompts and supplying them to the AI ​​model, it outputs an outline of appropriate accommodations, transportation, dining options, and activities. The server then generates a travel proposal based on these results. 【0118】 Step 4: 【0119】 The server retrieves weather information from an external Weather API and integrates it into the travel plan. After obtaining the weather data, it suggests appropriate clothing and items to the user based on that data. Here, specific clothing choices are made according to the weather conditions. 【0120】 Step 5: 【0121】 The generated travel plan is displayed to the user via their device. The user reviews this plan and sends feedback and modifications to the server. This allows for custom adjustments to suit the user's needs. 【0122】 Step 6: 【0123】 Ultimately, the server regenerates the travel plan as needed based on user feedback and releases an updated version. The feedback is analyzed, and the plan is further improved using the regeneration AI model. 【0124】 Step 7: 【0125】 The confirmed plan is supported by a system that includes financial settlement, enabling electronic payment via the terminal. Users can easily complete the payment process and share their travel plans with their companions. This process is secure and fast. 【0126】 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. 【0127】 This invention is a system that allows users to receive emotionally-informed suggestions while planning trips and meals. Users input their desired travel content and conditions through a chat interface. The server receives the user's input and analyzes the user's emotions using an emotion engine. 【0128】 The emotion engine uses natural language processing and machine learning algorithms to identify emotions from user text and voice data. This identified emotion information is incorporated as a key element in generating travel plans. For example, if a user indicates a desire to relax, the server will suggest quiet accommodations and relaxing activities. 【0129】 The server combines analysis results from the emotion engine with a generative AI model to create an optimal travel plan tailored to the user's preferences and emotions. This plan includes accommodation, transportation, and meal options, as well as activities that align with the user's feelings. It also takes weather information into account and provides advice on appropriate clothing and items to bring. 【0130】 The generated plan is presented to the user via the server, and the user can review and modify its contents. The server collects user feedback, re-analyzes changes in emotional state if necessary, and makes new suggestions. 【0131】 Finally, once the user finalizes their travel plan, the device provides a function to easily share that information via LINE and other apps, and also supports splitting expenses with travel companions through PayPay payment support. 【0132】 As a concrete example, if a user requests a relaxing trip because they are tired from work, the emotion engine will analyze the user's level of fatigue, and the server will suggest spa resorts or activities suitable for relaxation to alleviate stress. In this way, detailed planning that reflects emotions becomes possible. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 Users input and submit their travel conditions and preferences via the chat interface on their device. This may include expressions of specific emotions. 【0136】 Step 2: 【0137】 The server receives a text message from the user. The received content is parsed using natural language processing to extract basic travel-related information (destination, budget, itinerary, etc.). 【0138】 Step 3: 【0139】 The server uses an emotion engine to analyze the user's message to determine their emotions. Based on keywords and context, it identifies emotional states such as "I want to relax" or "I want to have a fun experience." 【0140】 Step 4: 【0141】 The server generates a travel plan, including accommodation, transportation, dining options, and activities, based on extracted emotions and basic information. This process involves referencing external APIs to obtain the latest information while also taking weather conditions into consideration. 【0142】 Step 5: 【0143】 The server generates a travel plan and presents it to the user. The plan details include activity suggestions tailored to the user's mood and clothing advice. 【0144】 Step 6: 【0145】 The user reviews the presented plan and sends feedback to the server via their device if necessary. This feedback may include further requests or new emotional expressions. 【0146】 Step 7: 【0147】 The server receives user feedback and, if necessary, reuses the emotion engine to regenerate plans based on the changed emotions. 【0148】 Step 8: 【0149】 The user finalizes their travel plan. After confirmation, the device shares the plan via LINE and provides a function to support splitting the cost with travel companions using PayPay. 【0150】 (Example 2) 【0151】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0152】 Traditional travel planning systems had the problem of not adequately considering the user's emotional state and only being able to offer uniform plans. Furthermore, if the suggested plan did not match the user's feelings or needs, the user had to make many modifications themselves, which negatively impacted the user experience. In addition, there was a lack of convenient features such as cost sharing among travel companions and easy sharing methods. 【0153】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0154】 In this invention, the server includes an analysis means for analyzing the user's emotional information and generating a travel plan, a suggestion means for proposing accommodation, transportation, meals, and activities using the analyzed information and a generated AI model, and a support means for sharing the proposed plan via communication means and assisting with payment. This enables the proposal of flexible and appropriate travel plans that correspond to the user's emotional state, improving user convenience and experience. 【0155】 "Emotional information" refers to information indicating the emotional state of a user, extracted from their text and voice data. 【0156】 The "analysis means" is a system that analyzes emotional information from user input and processes it to generate a travel plan. 【0157】 A "generative AI model" is an artificial intelligence algorithm that generates plans in natural language based on the user's desired conditions. 【0158】 A "suggestion mechanism" is a system that, based on analyzed information, suggests accommodation, transportation, meals, and activities in a way that is suitable for the user. 【0159】 "Support mechanisms" refer to systems that allow users to share generated plans with others via communication channels and provide support for payment methods. 【0160】 "Communication means" refers to methods and technologies for transmitting information to another terminal or system. 【0161】 This invention is a system that proposes travel plans that take the user's emotions into consideration. First, the user inputs their preferences and conditions regarding travel and meals via a chat interface through their terminal. The terminal then transmits this information to a server. Specifically, the hardware used is a computer or smartphone with communication capabilities. 【0162】 The server activates an emotion engine based on the received information. This emotion engine uses natural language processing and machine learning algorithms to analyze emotional information from the user's text and voice data. The analyzed emotions are passed to a generative AI model, which generates a travel plan based on the user's preferences and emotions. 【0163】 The specific software used includes natural language processing libraries and machine learning frameworks. A standard AI model platform is used for the generative AI model, and it operates based on input in the form of a prompt such as "Please suggest a travel plan that seeks relaxation." 【0164】 The server presents the generated travel plan to the user, allowing them to review its contents. When the user modifies the plan or provides feedback, the server performs necessary processing, such as sentiment analysis, again and makes new suggestions. The finalized plan is shared via messaging apps such as LINE through the device, and payment services such as PayPay are used to share expenses with travel companions. 【0165】 This design allows users to easily obtain a customized travel plan tailored to their emotional state, and enables them to adapt flexibly during the planning process. 【0166】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0167】 Step 1: 【0168】 The user uses the terminal's chat interface to input their travel and dining preferences and requirements via text or voice. The terminal sends this input data to the server. In this step, the input is the user's preferences and requirements, and the output is the input data in the format the server receives. 【0169】 Step 2: 【0170】 The server passes the received user input data to the emotion engine. The emotion engine uses natural language processing and machine learning algorithms to analyze the user's emotions. Specifically, it extracts keywords from text data and analyzes voice data, outputting emotional information such as wanting to relax or wanting to be excited as a result. The input for this step is the user's raw input data, and the output is the analyzed emotional information. 【0171】 Step 3: 【0172】 The server inputs the analyzed emotional information into a generative AI model to generate a travel plan. Here, the AI ​​is given specific instructions as a prompt, such as "Please suggest a travel plan that focuses on relaxation." The generative AI model combines the emotional information with the user's desired conditions to output a travel plan that includes accommodation, activities, transportation, etc. The input for this step is emotional information and a prompt, and the output is a specific travel plan. 【0173】 Step 4: 【0174】 The server presents the generated travel plan to the user. The user reviews this plan via their device and provides feedback on any necessary modifications. This information is sent back to the server, where sentiment analysis may be performed again, and new suggestions are generated. The input for this step is the initial travel plan, and the output is the revised plan incorporating the user's feedback. 【0175】 Step 5: 【0176】 Once the user confirms their travel plan, the device provides a function to share this information via messaging apps such as LINE. The device also allows for cost sharing with travel companions using payment apps such as PayPay. The input for this step is the confirmed travel plan, and the output is the shared information and payment details. 【0177】 (Application Example 2) 【0178】 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". 【0179】 Traditional travel and meal planning systems have a problem in that they do not adequately consider the user's emotional state, resulting in users not being able to obtain the optimal plan they are looking for. Furthermore, the inefficient payment and sharing of created plans leads to user inconvenience. 【0180】 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. 【0181】 This invention includes a generation means for analyzing user input information and generating a travel plan, a presentation means for suggesting accommodations, transportation, meals, and activities based on the analyzed information, a payment support means for sharing the suggested plan content via communication and supporting electronic payment, and an emotion analysis means for analyzing the user's emotions using an emotion analysis engine and generating an optimal travel plan based on the analysis results. This enables the generation of optimal travel and meal plans based on the user's emotions, as well as efficient payment and information sharing. 【0182】 "Generation means" refers to a part of a system that provides the function of generating a travel plan by analyzing user input information. 【0183】 A "presentation means" refers to a part of a system that has the function of suggesting accommodations, transportation, meals, and activities to the user based on the analyzed information. 【0184】 A "payment support mechanism" is part of a system that shares the proposed plan details through communication and also has the function of supporting electronic payments by the user. 【0185】 "Emotional analysis means" refers to a part of a system that uses an emotional analysis engine to analyze the user's emotional state and reflects the results in the generation of a travel plan. 【0186】 The server receives input information from the user, analyzes that information using a generation mechanism, and generates a travel plan. This generation mechanism is implemented using a programming language such as Python and utilizes natural language processing libraries to process user input. For example, if the user enters their wishes as text, the content is analyzed, and the user's emotional state is identified by an emotion analysis mechanism. 【0187】 The sentiment analysis utilizes machine learning algorithms and can leverage Python's sentiment analysis library. This allows the system to identify emotions from user input and generate an optimal travel plan based on the results. The server then uses this sentiment information to propose a plan tailored to the user, including accommodation, transportation, meals, and activities. 【0188】 The proposed plan is transmitted to the user's device via a communication method. This allows the user to review the travel plan on a device such as a smartphone and modify it as needed. Furthermore, it is possible to electronically pay for the proposed travel plan through a payment support system. Payments are processed quickly and securely using the API of an electronic payment service. 【0189】 For example, if a user inputs "I'd like suggestions for a travel plan to relieve stress," the emotion analysis tool will identify the user's emotion as stress and suggest travel destinations and activities suitable for relaxation. Examples of prompts include "I'd like suggestions for a travel plan that will relieve stress" or "Please suggest a relaxing meal." In this way, emotion-based planning using a generative AI model is possible. 【0190】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0191】 Step 1: 【0192】 The user enters their travel preferences. Using the chat interface displayed on the device, the user enters the details and conditions of their trip in text format. This input information is sent to the server. 【0193】 Step 2: 【0194】 The server receives user input and analyzes the input information using sentiment analysis tools. It obtains user text data as input and identifies emotions using a natural language processing library. The resulting sentiment data is then used in the next step. 【0195】 Step 3: 【0196】 The server generates an optimal travel plan based on analyzed emotional data and the user's preferences through a generation mechanism. Utilizing a generation AI model, it proposes a plan that includes accommodation, transportation, meals, and activities. At this stage, emotionally sensitive options are generated. 【0197】 Step 4: 【0198】 The server generates a travel plan and sends it to the user's terminal. Using communication methods, the travel plan is displayed in a visualized format on the user's terminal, providing information so that the user can review the contents and make corrections if necessary. 【0199】 Step 5: 【0200】 The user reviews and makes a final decision on their travel plan. They check the suggested plan on their device and determine if it is optimal. If there are any problems with the plan, they re-enter the information and a correction request is sent to the server. 【0201】 Step 6: 【0202】 Once the user has finalized their travel plan, the server processes the payment electronically through payment support mechanisms. The total cost of the travel plan is calculated and approved by the user; the payment is then securely processed through the payment service using the API. 【0203】 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. 【0204】 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. 【0205】 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. 【0206】 [Second Embodiment] 【0207】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0208】 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. 【0209】 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). 【0210】 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. 【0211】 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. 【0212】 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). 【0213】 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. 【0214】 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. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 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". 【0219】 This invention is a system that allows users to efficiently plan trips and meals. Users input their travel requests and conditions through a specific interface. This information is received and analyzed by a server. The server uses natural language processing technology to break down the user's input into categories and extract the elements necessary for travel planning. 【0220】 The server uses a generative AI model to build a travel plan based on the extracted elements. This plan includes accommodation, transportation, dining options, and activities, gathering information by referencing internal databases and external APIs. Furthermore, the server integrates the latest weather information to suggest appropriate clothing and items to bring to the user. This information is automatically adjusted based on the user's travel destination and planned activities. 【0221】 The generated plan is presented to the user by the server, and the user can view its contents via chat, LINE, etc. The user can review the proposed plan and return any revisions or feedback to the server. The server receives the feedback, regenerates the plan if necessary, and makes a new proposal. 【0222】 After the user finally confirms their plan, the device provides functionality to share that plan and also assists with payment by allowing users to split expenses with companions using payment methods such as PayPay. 【0223】 For example, if a user requests, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person," the server analyzes the request and suggests suitable beach resorts, surrounding facilities, activities, and access methods. It also provides optimal options based on the budget and offers clothing suggestions based on the weather. In this way, it is possible to efficiently create flexible travel plans that meet the user's wishes. 【0224】 The following describes the processing flow. 【0225】 Step 1: 【0226】 Users enter and submit their travel and dining preferences through a chat interface. For example, they might enter specific requests such as, "I'd like to go see the autumn leaves, but my budget is 10,000 yen per person." 【0227】 Step 2: 【0228】 The server receives the user's input message. Using a natural language processing engine, it parses the message and extracts elements such as destination, budget, and schedule. 【0229】 Step 3: 【0230】 Based on the information extracted by the server, it generates a travel plan that includes appropriate accommodations, transportation, dining options, and activities, referencing internal databases and external APIs. It also obtains the latest weather information and recommends appropriate clothing and items to bring. 【0231】 Step 4: 【0232】 The server generates a travel plan and presents it to the user. The plan results are sent to the user via chat or LINE, and the details of each option are explained. 【0233】 Step 5: 【0234】 Users review the proposed plan and submit feedback if they have any new requests or changes. They might specify a particular request, such as "I'd like to reduce accommodation costs." 【0235】 Step 6: 【0236】 The server receives feedback from the user and regenerates the travel plan. It adjusts the plan, taking into account specified conditions and new requests. If necessary, it proposes new options again. 【0237】 Step 7: 【0238】 The user reviews the proposed plan and confirms its contents once they are satisfied. They can then share the plan using LINE. 【0239】 Step 8: 【0240】 The device supports PayPay payments based on the travel plan presented to the user. It also provides a function to split expenses with travel companions and simplify the payment process. 【0241】 (Example 1) 【0242】 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." 【0243】 In modern times, planning trips and meals often requires significant time and effort for gathering information and constructing plans, making it particularly difficult to quickly create plans that take into account diverse conditions and requests. Furthermore, providing appropriate suggestions based on the weather at the travel destination and the user's budget is not easy. Therefore, the present invention aims to efficiently automate these planning processes and quickly provide optimal plans tailored to the user's needs. 【0244】 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. 【0245】 In this invention, the server includes means for analyzing user input information and extracting travel planning elements using natural language processing technology; means for generating a travel plan using a generative artificial intelligence model based on the analyzed elements; means for suggesting accommodation, transportation, meals, and activities by referring to an internal database and external information acquisition means; means for suggesting clothing and belongings by integrating weather information; and means for providing the generated travel plan to the user via communication means and supporting payment processing. This enables the user to quickly and flexibly generate an optimal travel plan that meets their individual needs and to proceed with planning efficiently. 【0246】 "User input information" refers to data regarding travel and dining conditions, preferences, and requests provided by users through a dedicated interface. 【0247】 "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to efficiently analyze user input and extract meaning. 【0248】 "Travel planning elements" refer to information necessary to create a travel plan, such as destination, itinerary, budget, and activities. 【0249】 A "generative artificial intelligence model" is an algorithm or program that generates text or data based on input data, and is used to autonomously construct proposed content. 【0250】 An "internal database" is a collection of information stored within the system, including historical data and registered items necessary for generating plans. 【0251】 "Means of acquiring external information" refers to mechanisms and methods for obtaining necessary information from external data sources, and includes the use of APIs and web services. 【0252】 "Accommodation, transportation, meals, and activities" refer to the various options and services offered to the user in a travel plan, and each element is a factor that constitutes the overall plan. 【0253】 "Weather information" refers to local weather data that should be considered when planning a trip, and is used to adjust clothing and activity plans. 【0254】 "Communication methods" refer to the methods and technologies used to transmit generated plans to users, including email, messaging services, and application notifications. 【0255】 "Means to support payment processing" refers to mechanisms that facilitate payments related to travel planned by users, and include payment services and bill-splitting functions. 【0256】 This invention is a system that helps users efficiently plan trips and meals. Users input their travel destination, budget, itinerary, and other requirements in text format using a dedicated application installed on their smartphone or computer. This input information is then transmitted to the server as "user input information." 【0257】 The server uses "natural language processing techniques" to analyze this input information. Common natural language processing libraries (e.g., Python's NLTK or spaCy) can be used here. The server then extracts elements of the travel plan and prepares them for further processing. 【0258】 Based on the extracted data, the server generates travel plans using a "generative artificial intelligence model." Specific models that can be used include, for example, deep learning-based text generation models (e.g., OpenAI's GPT series). The model is pre-trained on a large amount of travel-related information and creates the optimal plan tailored to the user's needs. 【0259】 Furthermore, the server utilizes both an "internal database" and "external information acquisition methods" to gather necessary information. The internal database stores past travel plans and information on popular tourist destinations. External data is obtained using specific APIs (e.g., travel site APIs and weather information APIs). 【0260】 The generated plan includes accommodation, transportation, meal options, and activity suggestions. The server also takes weather information into account and suggests appropriate clothing and items to bring. 【0261】 The completed plan will be provided to the user via "communication methods." Specifically, the plan details will be sent via the messaging service or email used by the user. Furthermore, "payment processing support methods" will be included to facilitate payment processing and assist in cost sharing among companions. 【0262】 As a concrete example, a user can send a request to the system using a prompt statement like the following: 【0263】 "I want to go to the beach for my summer vacation trip. I'm thinking of a budget of under 20,000 yen per person." 【0264】 By using this system, users can quickly generate travel plans tailored to their individual needs and effectively prepare for their trips. 【0265】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0266】 Step 1: 【0267】 Users enter their travel and dining requests using a dedicated application. This input is sent to the application as text prompts. Specifically, a user might enter a request such as, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person." This input data serves as the starting point for system processing. 【0268】 Step 2: 【0269】 The server receives prompt messages from the user and parses them using natural language processing techniques. Here, a text analysis library is used to segment the information and extract travel planning elements such as "destination," "budget," and "dates." The input is the prompt message, and the output is a set of parsed elements. This analysis allows the user's requests to be stored on the server as structured data. 【0270】 Step 3: 【0271】 The server generates travel plans using a generative artificial intelligence model based on elements extracted through natural language processing. Specifically, it leverages a dataset pre-trained by a machine learning model to propose plans that match the user's criteria. The input is a set of analyzed elements, and the output is the generated travel plan. The generative artificial intelligence model generates the text necessary for creating the plan and elaborates on the proposed content. 【0272】 Step 4: 【0273】 The server supplements the plan generated for presentation to the user using an internal database and external information retrieval methods. Specifically, it collects information such as accommodation, transportation, dining options, and weather data. The input is a provisional travel plan, and the output is a detailed, completed final plan. Information is retrieved in real time via external APIs and reflected in the plan. 【0274】 Step 5: 【0275】 The server uses communication methods to deliver the final travel plan to the user. Here, content is sent via the user's preferred messaging service or email. The input is the detailed, completed final plan, and the output is the travel plan information provided to the user. The user can review the received plan and send feedback to the server if necessary. 【0276】 Step 6: 【0277】 When a user submits feedback on a provided plan, the server analyzes the feedback and regenerates the plan based on the new conditions. The input is the user's feedback, and the output is the updated travel plan. The server then presents the regenerated plan to the user again and repeats the process to provide the best possible recommendation. 【0278】 (Application Example 1) 【0279】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal". 【0280】 In modern times, when making travel or outing plans, it is a time-consuming and laborious task to individually investigate a vast amount of information and combine the optimal options. Also, a system that can flexibly respond to plan changes and adjustments is required. Furthermore, it is necessary to formulate plans considering realistic factors such as environmental conditions and budget constraints. Therefore, it is an issue to provide a system that effectively and efficiently creates travel plans according to user demands and also takes into account cost management and environmental considerations. 【0281】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0282】 In this invention, the server includes an automatic generation means for analyzing requirements from the user and generating a travel plan, a recommendation means for proposing accommodation facilities, transportation means, meal options, and activity contents based on the analyzed information, a settlement means for sharing the proposed travel contents and supporting financial settlement, and an environmental adaptation means for integrating weather information into the travel plan and guiding appropriate clothing and items to bring. Thereby, based on the requirements input by the user once, the user can easily formulate a travel plan that can be comprehensively managed, and real-time adjustment and optimal resource allocation become possible. 【0283】 The "automatic generation means for analyzing requirements from the user and generating a travel plan" is a function that can interpret the requirements and conditions related to travel input by the user and mechanically create an overall travel plan based on them. 【0284】 The "recommendation means for proposing accommodation facilities, transportation means, meal options, and activity contents based on the analyzed information" is a function that can effectively select and present hotels, means of transportation, meal options, and activities necessary for travel based on the interpreted user requirement data. 【0285】 The "means for sharing the proposed travel content and supporting financial settlement" is a function that shares the generated travel plan with companions and others and supports the payment procedures for easily handling and managing travel-related expenses. 【0286】 The "environmental adaptation means for integrating weather information into the travel plan and guiding appropriate clothing and items to bring" is a function that incorporates the weather data of the travel destination into the travel plan and guides the user on the clothing to wear and the items to carry accordingly. 【0287】 The specific system for implementing this invention is designed to enable users to easily create travel plans. The user launches a dedicated application on a smart device and enters specific requirements such as the travel destination, budget, and desired activities. 【0288】 The server performs natural language processing on this information received from the user using the Google Cloud NLP API and extracts important attributes. Based on this information, the server uses the GPT API of OpenAI to generate a travel plan. The generated plan includes accommodation facilities, means of transportation, meal options, and activity details. 【0289】 Weather data is collected through the Weather API and integrated into the travel plan. Thereby, the server guides the user on suitable clothing and items to bring. Also, the proposed plan can be easily shared with companions. Regarding payment, it is carried out through the electronic payment function available on the terminal. 【0290】 As a specific example, when a user enters the desire of "wanting to plan a trip to Kyoto with the family during spring break" into the application, the server proposes family-friendly accommodation facilities, tourist spots, and Japanese restaurants in Kyoto. It also gives advice on clothing suitable for the spring climate. 【0291】 An example of a prompt to input into the generating AI model would be: "Create a suitable travel plan based on the following information: destination is Kyoto, family of 4, budget is under 100,000 yen, accommodation is 2 nights and 3 days, meals will be mainly Japanese." 【0292】 In this way, users can efficiently create complex travel plans and enjoy a comfortable and harmonious travel experience based on the suggestions provided. 【0293】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0294】 Step 1: 【0295】 The user uses the terminal's application to enter details about their travel destination, budget, and desired activities. This entered information is then sent to the system. Specifically, the user provides the necessary information through text boxes or voice input, and the terminal's communication module transmits it to the server. 【0296】 Step 2: 【0297】 The server analyzes the user's input information using the Google Cloud NLP API to extract important keywords and phrases. The input data is processed in text format, and travel-related elements (destination, budget, activities) are extracted. This analysis identifies specific travel needs. 【0298】 Step 3: 【0299】 The server invokes the OpenAI GPT API based on the analyzed information and uses a generative AI model to create a travel plan. By generating specific prompts and supplying them to the AI ​​model, it outputs an outline of appropriate accommodations, transportation, dining options, and activities. The server then generates a travel proposal based on these results. 【0300】 Step 4: 【0301】 The server retrieves weather information from an external Weather API and integrates it into the travel plan. After obtaining the weather data, it proposes appropriate clothing and items to the user based on it. Here, specific selections of outfits according to weather conditions are made. 【0302】 Step 5: 【0303】 The generated travel plan is displayed to the user via the terminal. The user checks this plan and returns opinions or corrections to the server regarding the proposed content. This enables custom adjustments according to the user's needs. 【0304】 Step 6: 【0305】 Finally, the server regenerates the travel plan as necessary based on the user's feedback and releases an updated version. The feedback content is analyzed, and the plan is improved using the regenerated AI model again. 【0306】 Step 7: 【0307】 The confirmed plan is supported by a system including financial settlement, enabling electronic payment in cooperation with the terminal. The user can easily complete the settlement procedure and share the travel plan with companions. This procedure is carried out safely and quickly. 【0308】 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. 【0309】 This invention is a system in which a user can receive proposals considering emotions during the process of planning a trip or a meal. The user inputs the desired trip content and conditions through a chat interface. At this time, the server receives the user's input information and analyzes the user's emotions using the emotion engine. 【0310】 The emotion engine uses natural language processing and machine learning algorithms to identify emotions from user text and voice data. This identified emotion information is incorporated as a key element in generating travel plans. For example, if a user indicates a desire to relax, the server will suggest quiet accommodations and relaxing activities. 【0311】 The server combines analysis results from the emotion engine with a generative AI model to create an optimal travel plan tailored to the user's preferences and emotions. This plan includes accommodation, transportation, and meal options, as well as activities that align with the user's feelings. It also takes weather information into account and provides advice on appropriate clothing and items to bring. 【0312】 The generated plan is presented to the user via the server, and the user can review and modify its contents. The server collects user feedback, re-analyzes changes in emotional state if necessary, and makes new suggestions. 【0313】 Finally, once the user finalizes their travel plan, the device provides a function to easily share that information via LINE and other apps, and also supports splitting expenses with travel companions through PayPay payment support. 【0314】 As a concrete example, if a user requests a relaxing trip because they are tired from work, the emotion engine will analyze the user's level of fatigue, and the server will suggest spa resorts or activities suitable for relaxation to alleviate stress. In this way, detailed planning that reflects emotions becomes possible. 【0315】 The following describes the processing flow. 【0316】 Step 1: 【0317】 Users input and submit their travel conditions and preferences via the chat interface on their device. This may include expressions of specific emotions. 【0318】 Step 2: 【0319】 The server receives a text message from the user. The received content is parsed using natural language processing to extract basic travel-related information (destination, budget, itinerary, etc.). 【0320】 Step 3: 【0321】 The server uses an emotion engine to analyze the user's message to determine their emotions. Based on keywords and context, it identifies emotional states such as "I want to relax" or "I want to have a fun experience." 【0322】 Step 4: 【0323】 The server generates a travel plan, including accommodation, transportation, dining options, and activities, based on extracted emotions and basic information. This process involves referencing external APIs to obtain the latest information while also taking weather conditions into consideration. 【0324】 Step 5: 【0325】 The server generates a travel plan and presents it to the user. The plan details include activity suggestions tailored to the user's mood and clothing advice. 【0326】 Step 6: 【0327】 The user reviews the presented plan and sends feedback to the server via their device if necessary. This feedback may include further requests or new emotional expressions. 【0328】 Step 7: 【0329】 The server receives user feedback and, if necessary, reuses the emotion engine to regenerate plans based on the changed emotions. 【0330】 Step 8: 【0331】 The user finalizes their travel plan. After confirmation, the device shares the plan via LINE and provides a function to support splitting the cost with travel companions using PayPay. 【0332】 (Example 2) 【0333】 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". 【0334】 Traditional travel planning systems had the problem of not adequately considering the user's emotional state and only being able to offer uniform plans. Furthermore, if the suggested plan did not match the user's feelings or needs, the user had to make many modifications themselves, which negatively impacted the user experience. In addition, there was a lack of convenient features such as cost sharing among travel companions and easy sharing methods. 【0335】 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. 【0336】 In this invention, the server includes an analysis means for analyzing the user's emotional information and generating a travel plan, a suggestion means for proposing accommodation, transportation, meals, and activities using the analyzed information and a generated AI model, and a support means for sharing the proposed plan via communication means and assisting with payment. This enables the proposal of flexible and appropriate travel plans that correspond to the user's emotional state, improving user convenience and experience. 【0337】 "Emotional information" refers to information indicating the emotional state of a user, extracted from their text and voice data. 【0338】 The "analysis means" is a system that analyzes emotional information from user input and processes it to generate a travel plan. 【0339】 A "generative AI model" is an artificial intelligence algorithm that generates plans in natural language based on the user's desired conditions. 【0340】 A "suggestion mechanism" is a system that, based on analyzed information, suggests accommodation, transportation, meals, and activities in a way that is suitable for the user. 【0341】 "Support mechanisms" refer to systems that allow users to share generated plans with others via communication channels and provide support for payment methods. 【0342】 "Communication means" refers to methods and technologies for transmitting information to another terminal or system. 【0343】 This invention is a system that proposes travel plans that take the user's emotions into consideration. First, the user inputs their preferences and conditions regarding travel and meals via a chat interface through their terminal. The terminal then transmits this information to a server. Specifically, the hardware used is a computer or smartphone with communication capabilities. 【0344】 The server activates an emotion engine based on the received information. This emotion engine uses natural language processing and machine learning algorithms to analyze emotional information from the user's text and voice data. The analyzed emotions are passed to a generative AI model, which generates a travel plan based on the user's preferences and emotions. 【0345】 The specific software used includes natural language processing libraries and machine learning frameworks. A standard AI model platform is used for the generative AI model, and it operates based on input in the form of a prompt such as "Please suggest a travel plan that seeks relaxation." 【0346】 The server presents the generated travel plan to the user, allowing them to review its contents. When the user modifies the plan or provides feedback, the server performs necessary processing, such as sentiment analysis, again and makes new suggestions. The finalized plan is shared via messaging apps such as LINE through the device, and payment services such as PayPay are used to share expenses with travel companions. 【0347】 This design allows users to easily obtain a customized travel plan tailored to their emotional state, and enables them to adapt flexibly during the planning process. 【0348】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0349】 Step 1: 【0350】 The user uses the terminal's chat interface to input their travel and dining preferences and requirements via text or voice. The terminal sends this input data to the server. In this step, the input is the user's preferences and requirements, and the output is the input data in the format the server receives. 【0351】 Step 2: 【0352】 The server passes the received user input data to the emotion engine. The emotion engine uses natural language processing and machine learning algorithms to analyze the user's emotions. Specifically, it extracts keywords from text data and analyzes voice data, outputting emotional information such as wanting to relax or wanting to be excited as a result. The input for this step is the user's raw input data, and the output is the analyzed emotional information. 【0353】 Step 3: 【0354】 The server inputs the analyzed emotional information into a generative AI model to generate a travel plan. Here, the AI ​​is given specific instructions as a prompt, such as "Please suggest a travel plan that focuses on relaxation." The generative AI model combines the emotional information with the user's desired conditions to output a travel plan that includes accommodation, activities, transportation, etc. The input for this step is emotional information and a prompt, and the output is a specific travel plan. 【0355】 Step 4: 【0356】 The server presents the generated travel plan to the user. The user reviews this plan via their device and provides feedback on any necessary modifications. This information is sent back to the server, where sentiment analysis may be performed again, and new suggestions are generated. The input for this step is the initial travel plan, and the output is the revised plan incorporating the user's feedback. 【0357】 Step 5: 【0358】 Once the user confirms their travel plan, the device provides a function to share this information via messaging apps such as LINE. The device also allows for cost sharing with travel companions using payment apps such as PayPay. The input for this step is the confirmed travel plan, and the output is the shared information and payment details. 【0359】 (Application Example 2) 【0360】 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." 【0361】 Traditional travel and meal planning systems have a problem in that they do not adequately consider the user's emotional state, resulting in users not being able to obtain the optimal plan they are looking for. Furthermore, the inefficient payment and sharing of created plans leads to user inconvenience. 【0362】 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. 【0363】 This invention includes a generation means for analyzing user input information and generating a travel plan, a presentation means for suggesting accommodations, transportation, meals, and activities based on the analyzed information, a payment support means for sharing the suggested plan content via communication and supporting electronic payment, and an emotion analysis means for analyzing the user's emotions using an emotion analysis engine and generating an optimal travel plan based on the analysis results. This enables the generation of optimal travel and meal plans based on the user's emotions, as well as efficient payment and information sharing. 【0364】 "Generation means" refers to a part of a system that provides the function of generating a travel plan by analyzing user input information. 【0365】 A "presentation means" refers to a part of a system that has the function of suggesting accommodations, transportation, meals, and activities to the user based on the analyzed information. 【0366】 A "payment support mechanism" is part of a system that shares the proposed plan details through communication and also has the function of supporting electronic payments by the user. 【0367】 "Emotional analysis means" refers to a part of a system that uses an emotional analysis engine to analyze the user's emotional state and reflects the results in the generation of a travel plan. 【0368】 The server receives input information from the user, analyzes that information using a generation mechanism, and generates a travel plan. This generation mechanism is implemented using a programming language such as Python and utilizes natural language processing libraries to process user input. For example, if the user enters their wishes as text, the content is analyzed, and the user's emotional state is identified by an emotion analysis mechanism. 【0369】 The sentiment analysis utilizes machine learning algorithms and can leverage Python's sentiment analysis library. This allows the system to identify emotions from user input and generate an optimal travel plan based on the results. The server then uses this sentiment information to propose a plan tailored to the user, including accommodation, transportation, meals, and activities. 【0370】 The proposed plan is transmitted to the user's device via a communication method. This allows the user to review the travel plan on a device such as a smartphone and modify it as needed. Furthermore, it is possible to electronically pay for the proposed travel plan through a payment support system. Payments are processed quickly and securely using the API of an electronic payment service. 【0371】 For example, if a user inputs "I'd like suggestions for a travel plan to relieve stress," the emotion analysis tool will identify the user's emotion as stress and suggest travel destinations and activities suitable for relaxation. Examples of prompts include "I'd like suggestions for a travel plan that will relieve stress" or "Please suggest a relaxing meal." In this way, emotion-based planning using a generative AI model is possible. 【0372】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0373】 Step 1: 【0374】 The user enters their travel preferences. Using the chat interface displayed on the device, the user enters the details and conditions of their trip in text format. This input information is sent to the server. 【0375】 Step 2: 【0376】 The server receives user input and analyzes the input information using sentiment analysis tools. It obtains user text data as input and identifies emotions using a natural language processing library. The resulting sentiment data is then used in the next step. 【0377】 Step 3: 【0378】 The server generates an optimal travel plan based on analyzed emotional data and the user's preferences through a generation mechanism. Utilizing a generation AI model, it proposes a plan that includes accommodation, transportation, meals, and activities. At this stage, emotionally sensitive options are generated. 【0379】 Step 4: 【0380】 The server generates a travel plan and sends it to the user's terminal. Using communication methods, the travel plan is displayed in a visualized format on the user's terminal, providing information so that the user can review the contents and make corrections if necessary. 【0381】 Step 5: 【0382】 The user reviews and makes a final decision on their travel plan. They check the suggested plan on their device and determine if it is optimal. If there are any problems with the plan, they re-enter the information and a correction request is sent to the server. 【0383】 Step 6: 【0384】 Once the user has finalized their travel plan, the server processes the payment electronically through payment support mechanisms. The total cost of the travel plan is calculated and approved by the user; the payment is then securely processed through the payment service using the API. 【0385】 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. 【0386】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0387】 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. 【0388】 [Third Embodiment] 【0389】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0390】 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. 【0391】 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). 【0392】 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. 【0393】 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. 【0394】 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). 【0395】 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. 【0396】 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. 【0397】 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. 【0398】 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. 【0399】 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. 【0400】 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". 【0401】 This invention is a system that allows users to efficiently plan trips and meals. Users input their travel requests and conditions through a specific interface. This information is received and analyzed by a server. The server uses natural language processing technology to break down the user's input into categories and extract the elements necessary for travel planning. 【0402】 The server uses a generative AI model to build a travel plan based on the extracted elements. This plan includes accommodation, transportation, dining options, and activities, gathering information by referencing internal databases and external APIs. Furthermore, the server integrates the latest weather information to suggest appropriate clothing and items to bring to the user. This information is automatically adjusted based on the user's travel destination and planned activities. 【0403】 The generated plan is presented to the user by the server, and the user can view its contents via chat, LINE, etc. The user can review the proposed plan and return any revisions or feedback to the server. The server receives the feedback, regenerates the plan if necessary, and makes a new proposal. 【0404】 After the user finally confirms their plan, the device provides functionality to share that plan and also assists with payment by allowing users to split expenses with companions using payment methods such as PayPay. 【0405】 For example, if a user requests, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person," the server analyzes the request and suggests suitable beach resorts, surrounding facilities, activities, and access methods. It also provides optimal options based on the budget and offers clothing suggestions based on the weather. In this way, it is possible to efficiently create flexible travel plans that meet the user's wishes. 【0406】 The following describes the processing flow. 【0407】 Step 1: 【0408】 Users enter and submit their travel and dining preferences through a chat interface. For example, they might enter specific requests such as, "I'd like to go see the autumn leaves, but my budget is 10,000 yen per person." 【0409】 Step 2: 【0410】 The server receives the user's input message. Using a natural language processing engine, it parses the message and extracts elements such as destination, budget, and schedule. 【0411】 Step 3: 【0412】 Based on the information extracted by the server, it generates a travel plan that includes appropriate accommodations, transportation, dining options, and activities, referencing internal databases and external APIs. It also obtains the latest weather information and recommends appropriate clothing and items to bring. 【0413】 Step 4: 【0414】 The server generates a travel plan and presents it to the user. The plan results are sent to the user via chat or LINE, and the details of each option are explained. 【0415】 Step 5: 【0416】 Users review the proposed plan and submit feedback if they have any new requests or changes. They might specify a particular request, such as "I'd like to reduce accommodation costs." 【0417】 Step 6: 【0418】 The server receives feedback from the user and regenerates the travel plan. It adjusts the plan, taking into account specified conditions and new requests. If necessary, it proposes new options again. 【0419】 Step 7: 【0420】 The user reviews the proposed plan and confirms its contents once they are satisfied. They can then share the plan using LINE. 【0421】 Step 8: 【0422】 The device supports PayPay payments based on the travel plan presented to the user. It also provides a function to split expenses with travel companions and simplify the payment process. 【0423】 (Example 1) 【0424】 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." 【0425】 In modern times, planning trips and meals often requires significant time and effort for gathering information and constructing plans, making it particularly difficult to quickly create plans that take into account diverse conditions and requests. Furthermore, providing appropriate suggestions based on the weather at the travel destination and the user's budget is not easy. Therefore, the present invention aims to efficiently automate these planning processes and quickly provide optimal plans tailored to the user's needs. 【0426】 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. 【0427】 In this invention, the server includes means for analyzing user input information and extracting travel planning elements using natural language processing technology; means for generating a travel plan using a generative artificial intelligence model based on the analyzed elements; means for suggesting accommodation, transportation, meals, and activities by referring to an internal database and external information acquisition means; means for suggesting clothing and belongings by integrating weather information; and means for providing the generated travel plan to the user via communication means and supporting payment processing. This enables the user to quickly and flexibly generate an optimal travel plan that meets their individual needs and to proceed with planning efficiently. 【0428】 "User input information" refers to data regarding travel and dining conditions, preferences, and requests provided by users through a dedicated interface. 【0429】 "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to efficiently analyze user input and extract meaning. 【0430】 "Travel planning elements" refer to information necessary to create a travel plan, such as destination, itinerary, budget, and activities. 【0431】 A "generative artificial intelligence model" is an algorithm or program that generates text or data based on input data, and is used to autonomously construct proposed content. 【0432】 An "internal database" is a collection of information stored within the system, including historical data and registered items necessary for generating plans. 【0433】 "Means of acquiring external information" refers to mechanisms and methods for obtaining necessary information from external data sources, and includes the use of APIs and web services. 【0434】 "Accommodation, transportation, meals, and activities" refer to the various options and services offered to the user in a travel plan, and each element is a factor that constitutes the overall plan. 【0435】 "Weather information" refers to local weather data that should be considered when planning a trip, and is used to adjust clothing and activity plans. 【0436】 "Communication methods" refer to the methods and technologies used to transmit generated plans to users, including email, messaging services, and application notifications. 【0437】 "Means to support payment processing" refers to mechanisms that facilitate payments related to travel planned by users, and include payment services and bill-splitting functions. 【0438】 This invention is a system that helps users efficiently plan trips and meals. Users input their travel destination, budget, itinerary, and other requirements in text format using a dedicated application installed on their smartphone or computer. This input information is then transmitted to the server as "user input information." 【0439】 The server uses "natural language processing techniques" to analyze this input information. Common natural language processing libraries (e.g., Python's NLTK or spaCy) can be used here. The server then extracts elements of the travel plan and prepares them for further processing. 【0440】 Based on the extracted data, the server generates travel plans using a "generative artificial intelligence model." Specific models that can be used include, for example, deep learning-based text generation models (e.g., OpenAI's GPT series). The model is pre-trained on a large amount of travel-related information and creates the optimal plan tailored to the user's needs. 【0441】 Furthermore, the server utilizes both an "internal database" and "external information acquisition methods" to gather necessary information. The internal database stores past travel plans and information on popular tourist destinations. External data is obtained using specific APIs (e.g., travel site APIs and weather information APIs). 【0442】 The generated plan includes accommodation, transportation, meal options, and activity suggestions. The server also takes weather information into account and suggests appropriate clothing and items to bring. 【0443】 The completed plan will be provided to the user via "communication methods." Specifically, the plan details will be sent via the messaging service or email used by the user. Furthermore, "payment processing support methods" will be included to facilitate payment processing and assist in cost sharing among companions. 【0444】 As a concrete example, a user can send a request to the system using a prompt statement like the following: 【0445】 "I want to go to the beach for my summer vacation trip. I'm thinking of a budget of under 20,000 yen per person." 【0446】 By using this system, users can quickly generate travel plans tailored to their individual needs and effectively prepare for their trips. 【0447】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0448】 Step 1: 【0449】 Users enter their travel and dining requests using a dedicated application. This input is sent to the application as text prompts. Specifically, a user might enter a request such as, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person." This input data serves as the starting point for system processing. 【0450】 Step 2: 【0451】 The server receives prompt messages from the user and parses them using natural language processing techniques. Here, a text analysis library is used to segment the information and extract travel planning elements such as "destination," "budget," and "dates." The input is the prompt message, and the output is a set of parsed elements. This analysis allows the user's requests to be stored on the server as structured data. 【0452】 Step 3: 【0453】 The server generates travel plans using a generative artificial intelligence model based on elements extracted through natural language processing. Specifically, it leverages a dataset pre-trained by a machine learning model to propose plans that match the user's criteria. The input is a set of analyzed elements, and the output is the generated travel plan. The generative artificial intelligence model generates the text necessary for creating the plan and elaborates on the proposed content. 【0454】 Step 4: 【0455】 The server supplements the plan generated for presentation to the user using an internal database and external information retrieval methods. Specifically, it collects information such as accommodation, transportation, dining options, and weather data. The input is a provisional travel plan, and the output is a detailed, completed final plan. Information is retrieved in real time via external APIs and reflected in the plan. 【0456】 Step 5: 【0457】 The server uses communication methods to deliver the final travel plan to the user. Here, content is sent via the user's preferred messaging service or email. The input is the detailed, completed final plan, and the output is the travel plan information provided to the user. The user can review the received plan and send feedback to the server if necessary. 【0458】 Step 6: 【0459】 When a user submits feedback on a provided plan, the server analyzes the feedback and regenerates the plan based on the new conditions. The input is the user's feedback, and the output is the updated travel plan. The server then presents the regenerated plan to the user again and repeats the process to provide the best possible recommendation. 【0460】 (Application Example 1) 【0461】 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." 【0462】 In today's world, planning trips and outings involves researching vast amounts of information individually and combining the best options, a time-consuming and laborious task. Furthermore, a system that can flexibly accommodate changes and adjustments to plans is needed. Additionally, plan development must consider practical factors such as environmental conditions and budget constraints. Therefore, the challenge lies in providing a system that effectively and efficiently creates travel plans according to user needs, while also managing costs and considering environmental factors. 【0463】 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. 【0464】 In this invention, the server includes an automatic generation means for analyzing user requirements and generating a travel plan, a recommendation means for suggesting accommodations, transportation, meal options, and activities based on the analyzed information, a payment means for sharing the suggested travel content and assisting with financial settlement, and an environment adaptation means for integrating weather information into the travel plan and guiding users on appropriate clothing and belongings. As a result, users can easily create a travel plan that can be managed as a whole based on their requests entered once, enabling real-time adjustments and optimal resource allocation. 【0465】 "An automated generation method that analyzes user requirements and generates travel plans" refers to a function that interprets the travel requests and conditions entered by the user and mechanically creates an overall travel plan based on them. 【0466】 "Recommendation methods that suggest accommodations, transportation, dining options, and activities based on analyzed information" refers to a function that can effectively select and present hotels, transportation, dining options, and activities necessary for travel, based on interpreted user request data. 【0467】 "A payment method that shares proposed travel itineraries and supports financial settlement" refers to a function that allows users to share generated travel plans with travel companions and others, and supports payment procedures for easily processing and managing travel-related expenses. 【0468】 "An environmental adaptation tool that integrates weather information into travel plans and guides users on appropriate clothing and belongings" refers to a function that incorporates weather data for the planned travel destination into the travel plan and guides users on what clothes to wear and what items to carry accordingly. 【0469】 The specific system for implementing this invention is designed to allow users to easily create travel plans. Users launch a dedicated application on their smart device and input specific requirements such as travel destination, budget, and desired activities. 【0470】 The server uses the Google Cloud NLP API to process the information received from the user in natural language and extract important attributes. Based on this information, the server uses the OpenAI GPT API to generate a travel plan. The generated plan includes accommodation, transportation, meal options, and activities. 【0471】 Weather data is collected via the Weather API and integrated into travel plans. This allows the server to guide users on appropriate clothing and items to bring. The suggested plan can also be easily shared with travel companions. Payments are made via electronic payment functions available on the device. 【0472】 For example, if a user enters into the application that they "want to plan a family trip to Kyoto during spring break," the server will suggest family-friendly accommodations, tourist attractions, and Japanese restaurants in Kyoto. It will also provide advice on appropriate clothing for the spring weather. 【0473】 An example of a prompt to input into the generating AI model would be: "Create a suitable travel plan based on the following information: destination is Kyoto, family of 4, budget is under 100,000 yen, accommodation is 2 nights and 3 days, meals will be mainly Japanese." 【0474】 In this way, users can efficiently create complex travel plans and enjoy a comfortable and harmonious travel experience based on the suggestions provided. 【0475】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0476】 Step 1: 【0477】 The user uses the terminal's application to enter details about their travel destination, budget, and desired activities. This entered information is then sent to the system. Specifically, the user provides the necessary information through text boxes or voice input, and the terminal's communication module transmits it to the server. 【0478】 Step 2: 【0479】 The server analyzes the user's input information using the Google Cloud NLP API to extract important keywords and phrases. The input data is processed in text format, and travel-related elements (destination, budget, activities) are extracted. This analysis identifies specific travel needs. 【0480】 Step 3: 【0481】 The server invokes the OpenAI GPT API based on the analyzed information and uses a generative AI model to create a travel plan. By generating specific prompts and supplying them to the AI ​​model, it outputs an outline of appropriate accommodations, transportation, dining options, and activities. The server then generates a travel proposal based on these results. 【0482】 Step 4: 【0483】 The server retrieves weather information from an external Weather API and integrates it into the travel plan. After obtaining the weather data, it suggests appropriate clothing and items to the user based on that data. Here, specific clothing choices are made according to the weather conditions. 【0484】 Step 5: 【0485】 The generated travel plan is displayed to the user via their device. The user reviews this plan and sends feedback and modifications to the server. This allows for custom adjustments to suit the user's needs. 【0486】 Step 6: 【0487】 Ultimately, the server regenerates the travel plan as needed based on user feedback and releases an updated version. The feedback is analyzed, and the plan is further improved using the regeneration AI model. 【0488】 Step 7: 【0489】 The confirmed plan is supported by a system that includes financial settlement, enabling electronic payment via the terminal. Users can easily complete the payment process and share their travel plans with their companions. This process is secure and fast. 【0490】 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. 【0491】 This invention is a system that allows users to receive emotionally-informed suggestions while planning trips and meals. Users input their desired travel content and conditions through a chat interface. The server receives the user's input and analyzes the user's emotions using an emotion engine. 【0492】 The emotion engine uses natural language processing and machine learning algorithms to identify emotions from user text and voice data. This identified emotion information is incorporated as a key element in generating travel plans. For example, if a user indicates a desire to relax, the server will suggest quiet accommodations and relaxing activities. 【0493】 The server combines analysis results from the emotion engine with a generative AI model to create an optimal travel plan tailored to the user's preferences and emotions. This plan includes accommodation, transportation, and meal options, as well as activities that align with the user's feelings. It also takes weather information into account and provides advice on appropriate clothing and items to bring. 【0494】 The generated plan is presented to the user via the server, and the user can review and modify its contents. The server collects user feedback, re-analyzes changes in emotional state if necessary, and makes new suggestions. 【0495】 Finally, once the user finalizes their travel plan, the device provides a function to easily share that information via LINE and other apps, and also supports splitting expenses with travel companions through PayPay payment support. 【0496】 As a concrete example, if a user requests a relaxing trip because they are tired from work, the emotion engine will analyze the user's level of fatigue, and the server will suggest spa resorts or activities suitable for relaxation to alleviate stress. In this way, detailed planning that reflects emotions becomes possible. 【0497】 The following describes the processing flow. 【0498】 Step 1: 【0499】 Users input and submit their travel conditions and preferences via the chat interface on their device. This may include expressions of specific emotions. 【0500】 Step 2: 【0501】 The server receives a text message from the user. The received content is parsed using natural language processing to extract basic travel-related information (destination, budget, itinerary, etc.). 【0502】 Step 3: 【0503】 The server uses an emotion engine to analyze the user's message to determine their emotions. Based on keywords and context, it identifies emotional states such as "I want to relax" or "I want to have a fun experience." 【0504】 Step 4: 【0505】 The server generates a travel plan, including accommodation, transportation, dining options, and activities, based on extracted emotions and basic information. This process involves referencing external APIs to obtain the latest information while also taking weather conditions into consideration. 【0506】 Step 5: 【0507】 The server generates a travel plan and presents it to the user. The plan details include activity suggestions tailored to the user's mood and clothing advice. 【0508】 Step 6: 【0509】 The user reviews the presented plan and sends feedback to the server via their device if necessary. This feedback may include further requests or new emotional expressions. 【0510】 Step 7: 【0511】 The server receives user feedback and, if necessary, reuses the emotion engine to regenerate plans based on the changed emotions. 【0512】 Step 8: 【0513】 The user finalizes their travel plan. After confirmation, the device shares the plan via LINE and provides a function to support splitting the cost with travel companions using PayPay. 【0514】 (Example 2) 【0515】 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." 【0516】 Traditional travel planning systems had the problem of not adequately considering the user's emotional state and only being able to offer uniform plans. Furthermore, if the suggested plan did not match the user's feelings or needs, the user had to make many modifications themselves, which negatively impacted the user experience. In addition, there was a lack of convenient features such as cost sharing among travel companions and easy sharing methods. 【0517】 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. 【0518】 In this invention, the server includes an analysis means for analyzing the user's emotional information and generating a travel plan, a suggestion means for proposing accommodation, transportation, meals, and activities using the analyzed information and a generated AI model, and a support means for sharing the proposed plan via communication means and assisting with payment. This enables the proposal of flexible and appropriate travel plans that correspond to the user's emotional state, improving user convenience and experience. 【0519】 "Emotional information" refers to information indicating the emotional state of a user, extracted from their text and voice data. 【0520】 The "analysis means" is a system that analyzes emotional information from user input and processes it to generate a travel plan. 【0521】 A "generative AI model" is an artificial intelligence algorithm that generates plans in natural language based on the user's desired conditions. 【0522】 A "suggestion mechanism" is a system that, based on analyzed information, suggests accommodation, transportation, meals, and activities in a way that is suitable for the user. 【0523】 "Support mechanisms" refer to systems that allow users to share generated plans with others via communication channels and provide support for payment methods. 【0524】 "Communication means" refers to methods and technologies for transmitting information to another terminal or system. 【0525】 This invention is a system that proposes travel plans that take the user's emotions into consideration. First, the user inputs their preferences and conditions regarding travel and meals via a chat interface through their terminal. The terminal then transmits this information to a server. Specifically, the hardware used is a computer or smartphone with communication capabilities. 【0526】 The server activates an emotion engine based on the received information. This emotion engine uses natural language processing and machine learning algorithms to analyze emotional information from the user's text and voice data. The analyzed emotions are passed to a generative AI model, which generates a travel plan based on the user's preferences and emotions. 【0527】 The specific software used includes natural language processing libraries and machine learning frameworks. A standard AI model platform is used for the generative AI model, and it operates based on input in the form of a prompt such as "Please suggest a travel plan that seeks relaxation." 【0528】 The server presents the generated travel plan to the user, allowing them to review its contents. When the user modifies the plan or provides feedback, the server performs necessary processing, such as sentiment analysis, again and makes new suggestions. The finalized plan is shared via messaging apps such as LINE through the device, and payment services such as PayPay are used to share expenses with travel companions. 【0529】 This design allows users to easily obtain a customized travel plan tailored to their emotional state, and enables them to adapt flexibly during the planning process. 【0530】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0531】 Step 1: 【0532】 The user uses the terminal's chat interface to input their travel and dining preferences and requirements via text or voice. The terminal sends this input data to the server. In this step, the input is the user's preferences and requirements, and the output is the input data in the format the server receives. 【0533】 Step 2: 【0534】 The server passes the received user input data to the emotion engine. The emotion engine uses natural language processing and machine learning algorithms to analyze the user's emotions. Specifically, it extracts keywords from text data and analyzes voice data, outputting emotional information such as wanting to relax or wanting to be excited as a result. The input for this step is the user's raw input data, and the output is the analyzed emotional information. 【0535】 Step 3: 【0536】 The server inputs the analyzed emotional information into a generative AI model to generate a travel plan. Here, the AI ​​is given specific instructions as a prompt, such as "Please suggest a travel plan that focuses on relaxation." The generative AI model combines the emotional information with the user's desired conditions to output a travel plan that includes accommodation, activities, transportation, etc. The input for this step is emotional information and a prompt, and the output is a specific travel plan. 【0537】 Step 4: 【0538】 The server presents the generated travel plan to the user. The user reviews this plan via their device and provides feedback on any necessary modifications. This information is sent back to the server, where sentiment analysis may be performed again, and new suggestions are generated. The input for this step is the initial travel plan, and the output is the revised plan incorporating the user's feedback. 【0539】 Step 5: 【0540】 Once the user confirms their travel plan, the device provides a function to share this information via messaging apps such as LINE. The device also allows for cost sharing with travel companions using payment apps such as PayPay. The input for this step is the confirmed travel plan, and the output is the shared information and payment details. 【0541】 (Application Example 2) 【0542】 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." 【0543】 Traditional travel and meal planning systems have a problem in that they do not adequately consider the user's emotional state, resulting in users not being able to obtain the optimal plan they are looking for. Furthermore, the inefficient payment and sharing of created plans leads to user inconvenience. 【0544】 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. 【0545】 This invention includes a generation means for analyzing user input information and generating a travel plan, a presentation means for suggesting accommodations, transportation, meals, and activities based on the analyzed information, a payment support means for sharing the suggested plan content via communication and supporting electronic payment, and an emotion analysis means for analyzing the user's emotions using an emotion analysis engine and generating an optimal travel plan based on the analysis results. This enables the generation of optimal travel and meal plans based on the user's emotions, as well as efficient payment and information sharing. 【0546】 "Generation means" refers to a part of a system that provides the function of generating a travel plan by analyzing user input information. 【0547】 A "presentation means" refers to a part of a system that has the function of suggesting accommodations, transportation, meals, and activities to the user based on the analyzed information. 【0548】 A "payment support mechanism" is part of a system that shares the proposed plan details through communication and also has the function of supporting electronic payments by the user. 【0549】 "Emotional analysis means" refers to a part of a system that uses an emotional analysis engine to analyze the user's emotional state and reflects the results in the generation of a travel plan. 【0550】 The server receives input information from the user, analyzes that information using a generation mechanism, and generates a travel plan. This generation mechanism is implemented using a programming language such as Python and utilizes natural language processing libraries to process user input. For example, if the user enters their wishes as text, the content is analyzed, and the user's emotional state is identified by an emotion analysis mechanism. 【0551】 The sentiment analysis utilizes machine learning algorithms and can leverage Python's sentiment analysis library. This allows the system to identify emotions from user input and generate an optimal travel plan based on the results. The server then uses this sentiment information to propose a plan tailored to the user, including accommodation, transportation, meals, and activities. 【0552】 The proposed plan is transmitted to the user's device via a communication method. This allows the user to review the travel plan on a device such as a smartphone and modify it as needed. Furthermore, it is possible to electronically pay for the proposed travel plan through a payment support system. Payments are processed quickly and securely using the API of an electronic payment service. 【0553】 For example, if a user inputs "I'd like suggestions for a travel plan to relieve stress," the emotion analysis tool will identify the user's emotion as stress and suggest travel destinations and activities suitable for relaxation. Examples of prompts include "I'd like suggestions for a travel plan that will relieve stress" or "Please suggest a relaxing meal." In this way, emotion-based planning using a generative AI model is possible. 【0554】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0555】 Step 1: 【0556】 The user enters their travel preferences. Using the chat interface displayed on the device, the user enters the details and conditions of their trip in text format. This input information is sent to the server. 【0557】 Step 2: 【0558】 The server receives user input and analyzes the input information using sentiment analysis tools. It obtains user text data as input and identifies emotions using a natural language processing library. The resulting sentiment data is then used in the next step. 【0559】 Step 3: 【0560】 The server generates an optimal travel plan based on analyzed emotional data and the user's preferences through a generation mechanism. Utilizing a generation AI model, it proposes a plan that includes accommodation, transportation, meals, and activities. At this stage, emotionally sensitive options are generated. 【0561】 Step 4: 【0562】 The server generates a travel plan and sends it to the user's terminal. Using communication methods, the travel plan is displayed in a visualized format on the user's terminal, providing information so that the user can review the contents and make corrections if necessary. 【0563】 Step 5: 【0564】 The user reviews and makes a final decision on their travel plan. They check the suggested plan on their device and determine if it is optimal. If there are any problems with the plan, they re-enter the information and a correction request is sent to the server. 【0565】 Step 6: 【0566】 Once the user has finalized their travel plan, the server processes the payment electronically through payment support mechanisms. The total cost of the travel plan is calculated and approved by the user; the payment is then securely processed through the payment service using the API. 【0567】 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. 【0568】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0569】 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. 【0570】 [Fourth Embodiment] 【0571】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0572】 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. 【0573】 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). 【0574】 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. 【0575】 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. 【0576】 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). 【0577】 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. 【0578】 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. 【0579】 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. 【0580】 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. 【0581】 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. 【0582】 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. 【0583】 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". 【0584】 This invention is a system that allows users to efficiently plan trips and meals. Users input their travel requests and conditions through a specific interface. This information is received and analyzed by a server. The server uses natural language processing technology to break down the user's input into categories and extract the elements necessary for travel planning. 【0585】 The server uses a generative AI model to build a travel plan based on the extracted elements. This plan includes accommodation, transportation, dining options, and activities, gathering information by referencing internal databases and external APIs. Furthermore, the server integrates the latest weather information to suggest appropriate clothing and items to bring to the user. This information is automatically adjusted based on the user's travel destination and planned activities. 【0586】 The generated plan is presented to the user by the server, and the user can view its contents via chat, LINE, etc. The user can review the proposed plan and return any revisions or feedback to the server. The server receives the feedback, regenerates the plan if necessary, and makes a new proposal. 【0587】 After the user finally confirms their plan, the device provides functionality to share that plan and also assists with payment by allowing users to split expenses with companions using payment methods such as PayPay. 【0588】 For example, if a user requests, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person," the server analyzes the request and suggests suitable beach resorts, surrounding facilities, activities, and access methods. It also provides optimal options based on the budget and offers clothing suggestions based on the weather. In this way, it is possible to efficiently create flexible travel plans that meet the user's wishes. 【0589】 The following describes the processing flow. 【0590】 Step 1: 【0591】 Users enter and submit their travel and dining preferences through a chat interface. For example, they might enter specific requests such as, "I'd like to go see the autumn leaves, but my budget is 10,000 yen per person." 【0592】 Step 2: 【0593】 The server receives the user's input message. Using a natural language processing engine, it parses the message and extracts elements such as destination, budget, and schedule. 【0594】 Step 3: 【0595】 Based on the information extracted by the server, it generates a travel plan that includes appropriate accommodations, transportation, dining options, and activities, referencing internal databases and external APIs. It also obtains the latest weather information and recommends appropriate clothing and items to bring. 【0596】 Step 4: 【0597】 The server generates a travel plan and presents it to the user. The plan results are sent to the user via chat or LINE, and the details of each option are explained. 【0598】 Step 5: 【0599】 Users review the proposed plan and submit feedback if they have any new requests or changes. They might specify a particular request, such as "I'd like to reduce accommodation costs." 【0600】 Step 6: 【0601】 The server receives feedback from the user and regenerates the travel plan. It adjusts the plan, taking into account specified conditions and new requests. If necessary, it proposes new options again. 【0602】 Step 7: 【0603】 The user reviews the proposed plan and confirms its contents once they are satisfied. They can then share the plan using LINE. 【0604】 Step 8: 【0605】 The device supports PayPay payments based on the travel plan presented to the user. It also provides a function to split expenses with travel companions and simplify the payment process. 【0606】 (Example 1) 【0607】 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". 【0608】 In modern times, planning trips and meals often requires significant time and effort for gathering information and constructing plans, making it particularly difficult to quickly create plans that take into account diverse conditions and requests. Furthermore, providing appropriate suggestions based on the weather at the travel destination and the user's budget is not easy. Therefore, the present invention aims to efficiently automate these planning processes and quickly provide optimal plans tailored to the user's needs. 【0609】 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. 【0610】 In this invention, the server includes means for analyzing user input information and extracting travel planning elements using natural language processing technology; means for generating a travel plan using a generative artificial intelligence model based on the analyzed elements; means for suggesting accommodation, transportation, meals, and activities by referring to an internal database and external information acquisition means; means for suggesting clothing and belongings by integrating weather information; and means for providing the generated travel plan to the user via communication means and supporting payment processing. This enables the user to quickly and flexibly generate an optimal travel plan that meets their individual needs and to proceed with planning efficiently. 【0611】 "User input information" refers to data regarding travel and dining conditions, preferences, and requests provided by users through a dedicated interface. 【0612】 "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to efficiently analyze user input and extract meaning. 【0613】 "Travel planning elements" refer to information necessary to create a travel plan, such as destination, itinerary, budget, and activities. 【0614】 A "generative artificial intelligence model" is an algorithm or program that generates text or data based on input data, and is used to autonomously construct proposed content. 【0615】 An "internal database" is a collection of information stored within the system, including historical data and registered items necessary for generating plans. 【0616】 "Means of acquiring external information" refers to mechanisms and methods for obtaining necessary information from external data sources, and includes the use of APIs and web services. 【0617】 "Accommodation, transportation, meals, and activities" refer to the various options and services offered to the user in a travel plan, and each element is a factor that constitutes the overall plan. 【0618】 "Weather information" refers to local weather data that should be considered when planning a trip, and is used to adjust clothing and activity plans. 【0619】 "Communication methods" refer to the methods and technologies used to transmit generated plans to users, including email, messaging services, and application notifications. 【0620】 "Means to support payment processing" refers to mechanisms that facilitate payments related to travel planned by users, and include payment services and bill-splitting functions. 【0621】 This invention is a system that helps users efficiently plan trips and meals. Users input their travel destination, budget, itinerary, and other requirements in text format using a dedicated application installed on their smartphone or computer. This input information is then transmitted to the server as "user input information." 【0622】 The server uses "natural language processing techniques" to analyze this input information. Common natural language processing libraries (e.g., Python's NLTK or spaCy) can be used here. The server then extracts elements of the travel plan and prepares them for further processing. 【0623】 Based on the extracted data, the server generates travel plans using a "generative artificial intelligence model." Specific models that can be used include, for example, deep learning-based text generation models (e.g., OpenAI's GPT series). The model is pre-trained on a large amount of travel-related information and creates the optimal plan tailored to the user's needs. 【0624】 Furthermore, the server utilizes both an "internal database" and "external information acquisition methods" to gather necessary information. The internal database stores past travel plans and information on popular tourist destinations. External data is obtained using specific APIs (e.g., travel site APIs and weather information APIs). 【0625】 The generated plan includes accommodation, transportation, meal options, and activity suggestions. The server also takes weather information into account and suggests appropriate clothing and items to bring. 【0626】 The completed plan will be provided to the user via "communication methods." Specifically, the plan details will be sent via the messaging service or email used by the user. Furthermore, "payment processing support methods" will be included to facilitate payment processing and assist in cost sharing among companions. 【0627】 As a concrete example, a user can send a request to the system using a prompt statement like the following: 【0628】 "I want to go to the beach for my summer vacation trip. I'm thinking of a budget of under 20,000 yen per person." 【0629】 By using this system, users can quickly generate travel plans tailored to their individual needs and effectively prepare for their trips. 【0630】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0631】 Step 1: 【0632】 Users enter their travel and dining requests using a dedicated application. This input is sent to the application as text prompts. Specifically, a user might enter a request such as, "I want to go to the beach for my summer vacation. My budget is under 20,000 yen per person." This input data serves as the starting point for system processing. 【0633】 Step 2: 【0634】 The server receives prompt messages from the user and parses them using natural language processing techniques. Here, a text analysis library is used to segment the information and extract travel planning elements such as "destination," "budget," and "dates." The input is the prompt message, and the output is a set of parsed elements. This analysis allows the user's requests to be stored on the server as structured data. 【0635】 Step 3: 【0636】 The server generates travel plans using a generative artificial intelligence model based on elements extracted through natural language processing. Specifically, it leverages a dataset pre-trained by a machine learning model to propose plans that match the user's criteria. The input is a set of analyzed elements, and the output is the generated travel plan. The generative artificial intelligence model generates the text necessary for creating the plan and elaborates on the proposed content. 【0637】 Step 4: 【0638】 The server supplements the plan generated for presentation to the user using an internal database and external information retrieval methods. Specifically, it collects information such as accommodation, transportation, dining options, and weather data. The input is a provisional travel plan, and the output is a detailed, completed final plan. Information is retrieved in real time via external APIs and reflected in the plan. 【0639】 Step 5: 【0640】 The server uses communication methods to deliver the final travel plan to the user. Here, content is sent via the user's preferred messaging service or email. The input is the detailed, completed final plan, and the output is the travel plan information provided to the user. The user can review the received plan and send feedback to the server if necessary. 【0641】 Step 6: 【0642】 When a user submits feedback on a provided plan, the server analyzes the feedback and regenerates the plan based on the new conditions. The input is the user's feedback, and the output is the updated travel plan. The server then presents the regenerated plan to the user again and repeats the process to provide the best possible recommendation. 【0643】 (Application Example 1) 【0644】 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". 【0645】 In today's world, planning trips and outings involves researching vast amounts of information individually and combining the best options, a time-consuming and laborious task. Furthermore, a system that can flexibly accommodate changes and adjustments to plans is needed. Additionally, plan development must consider practical factors such as environmental conditions and budget constraints. Therefore, the challenge lies in providing a system that effectively and efficiently creates travel plans according to user needs, while also managing costs and considering environmental factors. 【0646】 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. 【0647】 In this invention, the server includes an automatic generation means for analyzing user requirements and generating a travel plan, a recommendation means for suggesting accommodations, transportation, meal options, and activities based on the analyzed information, a payment means for sharing the suggested travel content and assisting with financial settlement, and an environment adaptation means for integrating weather information into the travel plan and guiding users on appropriate clothing and belongings. As a result, users can easily create a travel plan that can be managed as a whole based on their requests entered once, enabling real-time adjustments and optimal resource allocation. 【0648】 "An automated generation method that analyzes user requirements and generates travel plans" refers to a function that interprets the travel requests and conditions entered by the user and mechanically creates an overall travel plan based on them. 【0649】 "Recommendation methods that suggest accommodations, transportation, dining options, and activities based on analyzed information" refers to a function that can effectively select and present hotels, transportation, dining options, and activities necessary for travel, based on interpreted user request data. 【0650】 "A payment method that shares proposed travel itineraries and supports financial settlement" refers to a function that allows users to share generated travel plans with travel companions and others, and supports payment procedures for easily processing and managing travel-related expenses. 【0651】 "An environmental adaptation tool that integrates weather information into travel plans and guides users on appropriate clothing and belongings" refers to a function that incorporates weather data for the planned travel destination into the travel plan and guides users on what clothes to wear and what items to carry accordingly. 【0652】 The specific system for implementing this invention is designed to allow users to easily create travel plans. Users launch a dedicated application on their smart device and input specific requirements such as travel destination, budget, and desired activities. 【0653】 The server uses the Google Cloud NLP API to process the information received from the user in natural language and extract important attributes. Based on this information, the server uses the OpenAI GPT API to generate a travel plan. The generated plan includes accommodation, transportation, meal options, and activities. 【0654】 Weather data is collected via the Weather API and integrated into travel plans. This allows the server to guide users on appropriate clothing and items to bring. The suggested plan can also be easily shared with travel companions. Payments are made via electronic payment functions available on the device. 【0655】 For example, if a user enters into the application that they "want to plan a family trip to Kyoto during spring break," the server will suggest family-friendly accommodations, tourist attractions, and Japanese restaurants in Kyoto. It will also provide advice on appropriate clothing for the spring weather. 【0656】 An example of a prompt to input into the generating AI model would be: "Create a suitable travel plan based on the following information: destination is Kyoto, family of 4, budget is under 100,000 yen, accommodation is 2 nights and 3 days, meals will be mainly Japanese." 【0657】 In this way, users can efficiently create complex travel plans and enjoy a comfortable and harmonious travel experience based on the suggestions provided. 【0658】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0659】 Step 1: 【0660】 The user uses the terminal's application to enter details about their travel destination, budget, and desired activities. This entered information is then sent to the system. Specifically, the user provides the necessary information through text boxes or voice input, and the terminal's communication module transmits it to the server. 【0661】 Step 2: 【0662】 The server analyzes the user's input information using the Google Cloud NLP API to extract important keywords and phrases. The input data is processed in text format, and travel-related elements (destination, budget, activities) are extracted. This analysis identifies specific travel needs. 【0663】 Step 3: 【0664】 The server invokes the OpenAI GPT API based on the analyzed information and uses a generative AI model to create a travel plan. By generating specific prompts and supplying them to the AI ​​model, it outputs an outline of appropriate accommodations, transportation, dining options, and activities. The server then generates a travel proposal based on these results. 【0665】 Step 4: 【0666】 The server retrieves weather information from an external Weather API and integrates it into the travel plan. After obtaining the weather data, it suggests appropriate clothing and items to the user based on that data. Here, specific clothing choices are made according to the weather conditions. 【0667】 Step 5: 【0668】 The generated travel plan is displayed to the user via their device. The user reviews this plan and sends feedback and modifications to the server. This allows for custom adjustments to suit the user's needs. 【0669】 Step 6: 【0670】 Ultimately, the server regenerates the travel plan as needed based on user feedback and releases an updated version. The feedback is analyzed, and the plan is further improved using the regeneration AI model. 【0671】 Step 7: 【0672】 The confirmed plan is supported by a system that includes financial settlement, enabling electronic payment via the terminal. Users can easily complete the payment process and share their travel plans with their companions. This process is secure and fast. 【0673】 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. 【0674】 This invention is a system that allows users to receive emotionally-informed suggestions while planning trips and meals. Users input their desired travel content and conditions through a chat interface. The server receives the user's input and analyzes the user's emotions using an emotion engine. 【0675】 The emotion engine uses natural language processing and machine learning algorithms to identify emotions from user text and voice data. This identified emotion information is incorporated as a key element in generating travel plans. For example, if a user indicates a desire to relax, the server will suggest quiet accommodations and relaxing activities. 【0676】 The server combines analysis results from the emotion engine with a generative AI model to create an optimal travel plan tailored to the user's preferences and emotions. This plan includes accommodation, transportation, and meal options, as well as activities that align with the user's feelings. It also takes weather information into account and provides advice on appropriate clothing and items to bring. 【0677】 The generated plan is presented to the user via the server, and the user can review and modify its contents. The server collects user feedback, re-analyzes changes in emotional state if necessary, and makes new suggestions. 【0678】 Finally, once the user finalizes their travel plan, the device provides a function to easily share that information via LINE and other apps, and also supports splitting expenses with travel companions through PayPay payment support. 【0679】 As a concrete example, if a user requests a relaxing trip because they are tired from work, the emotion engine will analyze the user's level of fatigue, and the server will suggest spa resorts or activities suitable for relaxation to alleviate stress. In this way, detailed planning that reflects emotions becomes possible. 【0680】 The following describes the processing flow. 【0681】 Step 1: 【0682】 Users input and submit their travel conditions and preferences via the chat interface on their device. This may include expressions of specific emotions. 【0683】 Step 2: 【0684】 The server receives a text message from the user. The received content is parsed using natural language processing to extract basic travel-related information (destination, budget, itinerary, etc.). 【0685】 Step 3: 【0686】 The server uses an emotion engine to analyze the user's message to determine their emotions. Based on keywords and context, it identifies emotional states such as "I want to relax" or "I want to have a fun experience." 【0687】 Step 4: 【0688】 The server generates a travel plan, including accommodation, transportation, dining options, and activities, based on extracted emotions and basic information. This process involves referencing external APIs to obtain the latest information while also taking weather conditions into consideration. 【0689】 Step 5: 【0690】 The server generates a travel plan and presents it to the user. The plan details include activity suggestions tailored to the user's mood and clothing advice. 【0691】 Step 6: 【0692】 The user reviews the presented plan and sends feedback to the server via their device if necessary. This feedback may include further requests or new emotional expressions. 【0693】 Step 7: 【0694】 The server receives user feedback and, if necessary, reuses the emotion engine to regenerate plans based on the changed emotions. 【0695】 Step 8: 【0696】 The user finalizes their travel plan. After confirmation, the device shares the plan via LINE and provides a function to support splitting the cost with travel companions using PayPay. 【0697】 (Example 2) 【0698】 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". 【0699】 Traditional travel planning systems had the problem of not adequately considering the user's emotional state and only being able to offer uniform plans. Furthermore, if the suggested plan did not match the user's feelings or needs, the user had to make many modifications themselves, which negatively impacted the user experience. In addition, there was a lack of convenient features such as cost sharing among travel companions and easy sharing methods. 【0700】 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. 【0701】 In this invention, the server includes an analysis means for analyzing the user's emotional information and generating a travel plan, a suggestion means for proposing accommodation, transportation, meals, and activities using the analyzed information and a generated AI model, and a support means for sharing the proposed plan via communication means and assisting with payment. This enables the proposal of flexible and appropriate travel plans that correspond to the user's emotional state, improving user convenience and experience. 【0702】 "Emotional information" refers to information indicating the emotional state of a user, extracted from their text and voice data. 【0703】 The "analysis means" is a system that analyzes emotional information from user input and processes it to generate a travel plan. 【0704】 A "generative AI model" is an artificial intelligence algorithm that generates plans in natural language based on the user's desired conditions. 【0705】 A "suggestion mechanism" is a system that, based on analyzed information, suggests accommodation, transportation, meals, and activities in a way that is suitable for the user. 【0706】 "Support mechanisms" refer to systems that allow users to share generated plans with others via communication channels and provide support for payment methods. 【0707】 "Communication means" refers to methods and technologies for transmitting information to another terminal or system. 【0708】 This invention is a system that proposes travel plans that take the user's emotions into consideration. First, the user inputs their preferences and conditions regarding travel and meals via a chat interface through their terminal. The terminal then transmits this information to a server. Specifically, the hardware used is a computer or smartphone with communication capabilities. 【0709】 The server activates an emotion engine based on the received information. This emotion engine uses natural language processing and machine learning algorithms to analyze emotional information from the user's text and voice data. The analyzed emotions are passed to a generative AI model, which generates a travel plan based on the user's preferences and emotions. 【0710】 The specific software used includes natural language processing libraries and machine learning frameworks. A standard AI model platform is used for the generative AI model, and it operates based on input in the form of a prompt such as "Please suggest a travel plan that seeks relaxation." 【0711】 The server presents the generated travel plan to the user, allowing them to review its contents. When the user modifies the plan or provides feedback, the server performs necessary processing, such as sentiment analysis, again and makes new suggestions. The finalized plan is shared via messaging apps such as LINE through the device, and payment services such as PayPay are used to share expenses with travel companions. 【0712】 This design allows users to easily obtain a customized travel plan tailored to their emotional state, and enables them to adapt flexibly during the planning process. 【0713】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0714】 Step 1: 【0715】 The user uses the terminal's chat interface to input their travel and dining preferences and requirements via text or voice. The terminal sends this input data to the server. In this step, the input is the user's preferences and requirements, and the output is the input data in the format the server receives. 【0716】 Step 2: 【0717】 The server passes the received user input data to the emotion engine. The emotion engine uses natural language processing and machine learning algorithms to analyze the user's emotions. Specifically, it extracts keywords from text data and analyzes voice data, outputting emotional information such as wanting to relax or wanting to be excited as a result. The input for this step is the user's raw input data, and the output is the analyzed emotional information. 【0718】 Step 3: 【0719】 The server inputs the analyzed emotional information into a generative AI model to generate a travel plan. Here, the AI ​​is given specific instructions as a prompt, such as "Please suggest a travel plan that focuses on relaxation." The generative AI model combines the emotional information with the user's desired conditions to output a travel plan that includes accommodation, activities, transportation, etc. The input for this step is emotional information and a prompt, and the output is a specific travel plan. 【0720】 Step 4: 【0721】 The server presents the generated travel plan to the user. The user reviews this plan via their device and provides feedback on any necessary modifications. This information is sent back to the server, where sentiment analysis may be performed again, and new suggestions are generated. The input for this step is the initial travel plan, and the output is the revised plan incorporating the user's feedback. 【0722】 Step 5: 【0723】 Once the user confirms their travel plan, the device provides a function to share this information via messaging apps such as LINE. The device also allows for cost sharing with travel companions using payment apps such as PayPay. The input for this step is the confirmed travel plan, and the output is the shared information and payment details. 【0724】 (Application Example 2) 【0725】 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". 【0726】 Traditional travel and meal planning systems have a problem in that they do not adequately consider the user's emotional state, resulting in users not being able to obtain the optimal plan they are looking for. Furthermore, the inefficient payment and sharing of created plans leads to user inconvenience. 【0727】 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. 【0728】 This invention includes a generation means for analyzing user input information and generating a travel plan, a presentation means for suggesting accommodations, transportation, meals, and activities based on the analyzed information, a payment support means for sharing the suggested plan content via communication and supporting electronic payment, and an emotion analysis means for analyzing the user's emotions using an emotion analysis engine and generating an optimal travel plan based on the analysis results. This enables the generation of optimal travel and meal plans based on the user's emotions, as well as efficient payment and information sharing. 【0729】 "Generation means" refers to a part of a system that provides the function of generating a travel plan by analyzing user input information. 【0730】 A "presentation means" refers to a part of a system that has the function of suggesting accommodations, transportation, meals, and activities to the user based on the analyzed information. 【0731】 A "payment support mechanism" is part of a system that shares the proposed plan details through communication and also has the function of supporting electronic payments by the user. 【0732】 "Emotional analysis means" refers to a part of a system that uses an emotional analysis engine to analyze the user's emotional state and reflects the results in the generation of a travel plan. 【0733】 The server receives input information from the user, analyzes that information using a generation mechanism, and generates a travel plan. This generation mechanism is implemented using a programming language such as Python and utilizes natural language processing libraries to process user input. For example, if the user enters their wishes as text, the content is analyzed, and the user's emotional state is identified by an emotion analysis mechanism. 【0734】 The sentiment analysis utilizes machine learning algorithms and can leverage Python's sentiment analysis library. This allows the system to identify emotions from user input and generate an optimal travel plan based on the results. The server then uses this sentiment information to propose a plan tailored to the user, including accommodation, transportation, meals, and activities. 【0735】 The proposed plan is transmitted to the user's device via a communication method. This allows the user to review the travel plan on a device such as a smartphone and modify it as needed. Furthermore, it is possible to electronically pay for the proposed travel plan through a payment support system. Payments are processed quickly and securely using the API of an electronic payment service. 【0736】 For example, if a user inputs "I'd like suggestions for a travel plan to relieve stress," the emotion analysis tool will identify the user's emotion as stress and suggest travel destinations and activities suitable for relaxation. Examples of prompts include "I'd like suggestions for a travel plan that will relieve stress" or "Please suggest a relaxing meal." In this way, emotion-based planning using a generative AI model is possible. 【0737】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0738】 Step 1: 【0739】 The user enters their travel preferences. Using the chat interface displayed on the device, the user enters the details and conditions of their trip in text format. This input information is sent to the server. 【0740】 Step 2: 【0741】 The server receives user input and analyzes the input information using sentiment analysis tools. It obtains user text data as input and identifies emotions using a natural language processing library. The resulting sentiment data is then used in the next step. 【0742】 Step 3: 【0743】 The server generates an optimal travel plan based on analyzed emotional data and the user's preferences through a generation mechanism. Utilizing a generation AI model, it proposes a plan that includes accommodation, transportation, meals, and activities. At this stage, emotionally sensitive options are generated. 【0744】 Step 4: 【0745】 The server generates a travel plan and sends it to the user's terminal. Using communication methods, the travel plan is displayed in a visualized format on the user's terminal, providing information so that the user can review the contents and make corrections if necessary. 【0746】 Step 5: 【0747】 The user reviews and makes a final decision on their travel plan. They check the suggested plan on their device and determine if it is optimal. If there are any problems with the plan, they re-enter the information and a correction request is sent to the server. 【0748】 Step 6: 【0749】 Once the user has finalized their travel plan, the server processes the payment electronically through payment support mechanisms. The total cost of the travel plan is calculated and approved by the user; the payment is then securely processed through the payment service using the API. 【0750】 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. 【0751】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0752】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0753】 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. 【0754】 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. 【0755】 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. 【0756】 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. 【0757】 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. 【0758】 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." 【0759】 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. 【0760】 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. 【0761】 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. 【0762】 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. 【0763】 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. 【0764】 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. 【0765】 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. 【0766】 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. 【0767】 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. 【0768】 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. 【0769】 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. 【0770】 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. 【0771】 The following is further disclosed regarding the embodiments described above. 【0772】 (Claim 1) 【0773】 A generation method that analyzes user input information and generates a travel plan, 【0774】 A proposal system that suggests accommodation, transportation, meals, and activities based on analyzed information, 【0775】 The proposed plan details will be shared via communication methods, and support measures will be provided to assist with payment. 【0776】 A system that includes this. 【0777】 (Claim 2) 【0778】 The system according to claim 1, which regenerates the proposed content based on user feedback. 【0779】 (Claim 3) 【0780】 The system according to claim 1, which suggests clothing and belongings that take weather information into consideration. 【0781】 "Example 1" 【0782】 (Claim 1) 【0783】 A means for analyzing user input information and extracting travel planning elements using natural language processing technology, 【0784】 A means for generating a travel plan using a generative artificial intelligence model based on the analyzed elements, 【0785】 A means of suggesting accommodation, transportation, meals, and activities by referring to an internal database and external information acquisition means, 【0786】 A means of integrating weather information to suggest clothing and items to bring, 【0787】 A means of providing the generated travel plan to the user via communication means and supporting payment processing, 【0788】 A system that includes this. 【0789】 (Claim 2) 【0790】 The system according to claim 1, which analyzes user feedback and regenerates a travel plan. 【0791】 (Claim 3) 【0792】 The system according to claim 1, which dynamically incorporates weather information and adjusts suggestions according to the user's travel destination and planned activities. 【0793】 "Application Example 1" 【0794】 (Claim 1) 【0795】 An automated generation method that analyzes user requirements and generates travel plans, 【0796】 Based on the analyzed information, a recommendation system suggests accommodations, transportation options, dining choices, and activities. 【0797】 Share the proposed travel itinerary and use payment methods to facilitate financial settlement. 【0798】 An environmental adaptation tool that integrates weather information into travel planning and provides guidance on appropriate clothing and belongings, 【0799】 A system that includes this. 【0800】 (Claim 2) 【0801】 The system according to claim 1, which regenerates a proposed plan based on user feedback. 【0802】 (Claim 3) 【0803】 The system according to claim 1, further comprising means for gathering information that connects to public information sources and external databases to provide information regarding travel planning. 【0804】 "Example 2 of combining an emotion engine" 【0805】 (Claim 1) 【0806】 An analytical means for analyzing user emotional information and generating travel plans, 【0807】 A proposal method that uses analyzed information and a generative AI model to suggest accommodation, transportation, meals, and activities, 【0808】 The proposed plan will be shared via communication means, and support measures will be provided to assist with payments. 【0809】 A system that includes this. 【0810】 (Claim 2) 【0811】 The system according to claim 1, which reanalyzes emotional information based on user feedback and regenerates suggested content. 【0812】 (Claim 3) 【0813】 The system according to claim 1, which suggests clothing and belongings based on weather information and adapts to the user's emotional state. 【0814】 "Application example 2 when combining with an emotional engine" 【0815】 (Claim 1) 【0816】 A generation means that analyzes user input information and generates a travel plan, 【0817】 A presentation method that suggests accommodation, transportation, meals, and activities based on analyzed information, 【0818】 The proposed plan details are shared via means of communication, and payment support means are provided to support electronic payments. 【0819】 An emotion analysis means that analyzes the user's emotions using an emotion analysis engine and generates an optimal travel plan based on the analysis results, 【0820】 A system that includes this. 【0821】 (Claim 2) 【0822】 The system according to claim 1, which regenerates the proposed content based on user feedback. 【0823】 (Claim 3) 【0824】 The system according to claim 1, which suggests clothing and belongings that take weather information into consideration. [Explanation of symbols] 【0825】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A generation method that analyzes user input information and generates a travel plan, A proposal system that suggests accommodation, transportation, meals, and activities based on analyzed information, The proposed plan details will be shared via communication methods, and support measures will be provided to assist with payment. A system that includes this. [Claim 2] The system according to claim 1, which regenerates the proposed content based on user feedback. [Claim 3] The system according to claim 1, which suggests clothing and belongings that take weather information into consideration.

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