system

Abstract

We provide the system. [Solution] A means for users to input their travel preferences, A means for analyzing the user's input using natural language processing technology and identifying the user's intent, A method for generating the most suitable travel plan for a user by learning from past data of similar travel preferences, A means of presenting the generated travel plan to the user, A means of providing real-time event information for the travel destination included in the travel plan, 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, 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 Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In travel planning, users often have difficulty efficiently collecting information that meets various conditions and constraints and realizing a travel experience that suits their individual needs. In particular, there are problems that it is not easy to find an optimal travel plan within the budget, select activities based on interests, and obtain real-time event information. 【Means for Solving the Problems】 【0005】 This invention identifies the user's intentions by inputting their travel preferences and analyzing them using natural language processing technology. It also learns from past data of users with similar travel preferences to generate the most suitable travel plan. Furthermore, it presents the generated travel plan to the user and provides real-time event information for the travel destination, thereby supporting efficient travel planning tailored to the user's individual needs. 【0006】 A "user" refers to an individual who uses the system to plan a trip. 【0007】 "Travel preferences" refer to the requirements that users want to meet when planning a trip, such as budget, destination, accommodation, and activities of interest. 【0008】 "Natural language processing technology" refers to the technology used to enable computers to understand human language and communicate with humans. 【0009】 "Identifying user intent" refers to analyzing the information users enter into the system to clarify their goals and desires for their trip. 【0010】 "Past data with similar travel preferences" refers to data from people who have used the system in the past and whose travel preferences and conditions are similar to those of the current user. 【0011】 A "travel plan" is an overall travel plan proposed to the user, including accommodation, transportation, sightseeing destinations, activities, budget allocation, etc. 【0012】 "Real-time event information" refers to the latest information about events and happenings currently or in the future in a specific region. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【MODE FOR CARRYING OUT THE INVENTION】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0019】 In the following embodiments, a numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like. 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 The system according to the present invention receives the user's travel preferences and generates an optimal travel plan based on them. A specific embodiment of this system is described below. 【0035】 Users use their devices to fill out a form detailing their travel preferences. This includes destination, budget, travel duration, type of accommodation, and activities of interest. 【0036】 The terminal sends the entered conditions to the server. The server uses natural language processing technology to analyze the user's intent based on the received data. Using the results of the analysis, the server retrieves past user data with similar travel preferences from the database in order to generate candidate travel plans that closely match the user's wishes. 【0037】 Based on the acquired data, the server selects destinations, accommodations, and activities that fit the budget and requirements, and creates a plan that best suits the user's wishes. In this process, the server also takes real-time event information into consideration, and therefore refers to the latest event information taking place around the travel destination. 【0038】 The terminal displays the travel plan received from the server to the user. The user reviews this plan, provides feedback, or confirms the plan. If feedback is received, the server re-evaluates the plan based on it and makes necessary adjustments to provide a more satisfying plan. 【0039】 As a concrete example, suppose a user enters the following conditions: "I want to travel to Kyoto with a budget of 150,000 yen. I want to prioritize cultural experiences." The terminal sends this information to the server, which then analyzes it. The server searches past data for plans that include cultural experiences in Kyoto and generates a proposed plan incorporating activities such as "Kyoto tea ceremony experience, temple tours, and kimono rental." By also adding information about festivals held during the travel period to the proposal, the server can provide the user with the most suitable travel experience. 【0040】 In this way, the system of the present invention efficiently generates travel plans based on the user's wishes and conditions, and provides personalized services. 【0041】 The following describes the processing flow. 【0042】 Step 1: 【0043】 Users enter their travel preferences using their own devices. This input includes details such as destination, budget, duration, and areas of interest such as activities and tourist attractions. 【0044】 Step 2: 【0045】 The terminal sends the user's entered conditions to the server as a data packet. This packet contains user information and travel conditions. 【0046】 Step 3: 【0047】 The server analyzes the data received from the terminal. Using natural language processing technology, it analyzes the input content and identifies the user's intentions and desires. 【0048】 Step 4: 【0049】 Based on the analyzed information, the server retrieves past user data from a database showing similar travel experiences and preferences. This gathers reference information to create the most suitable plan for the user. 【0050】 Step 5: 【0051】 The server creates a travel plan based on the acquired data. Based on budget, desired conditions, and past successful plans, it selects the optimal destination, accommodation, and sightseeing route. 【0052】 Step 6: 【0053】 The server collects real-time event information taking place at the travel destination during the trip and adds it to the plan. This provides users with the latest event information. 【0054】 Step 7: 【0055】 The server sends the final travel plan to the device. This plan includes selected travel elements and event information. 【0056】 Step 8: 【0057】 The device displays a travel plan to the user. The user reviews the plan and accepts it if satisfied, or provides feedback if any modifications are needed. 【0058】 Step 9: 【0059】 Based on user feedback, the server re-evaluates the plan, makes corrections as needed, and resubmits the final plan. 【0060】 (Example 1) 【0061】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0062】 Current travel plan generation systems struggle to flexibly respond to diverse user needs, particularly in providing plans that adequately consider budget constraints and real-time event information. As a result, users' travel experiences sometimes end up falling short of expectations. Furthermore, the adaptive adjustment of plans based on feedback is insufficient, limiting the ability to provide plans that truly satisfy users. 【0063】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0064】 In this invention, the server includes means for analyzing user input using natural language processing technology, means for generating a travel plan by learning from past data of users with similar travel preferences, and means for optimizing the travel plan based on budget constraints. This makes it possible to generate a more satisfying travel plan that corresponds to the user's individual conditions and intentions. 【0065】 A "user" refers to an individual or group that intends to use the system to plan a trip. 【0066】 "Desired conditions" refer to the requirements that users specify when planning a trip, such as destination, budget, duration of travel, type of accommodation, and activities of interest. 【0067】 "Natural language processing technology" refers to the technology used by computers to understand and interpret human language. 【0068】 A "travel plan" refers to a detailed plan for a trip desired by the user, including specific destinations, accommodations, and information on activities and events. 【0069】 "Real-time event information" refers to the latest information on specific events and activities taking place at your travel destination during your visit period. 【0070】 A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to generate output for a specific task. 【0071】 A "prompt" refers to the input text used to give instructions or conditions to a generative AI model. 【0072】 "Feedback" refers to opinions and impressions of travel plans provided by users, and may include requests for system improvements. 【0073】 "Budget constraints" refer to the financial limitations or restrictions that users must consider when planning a trip. 【0074】 "Adaptive adjustment" refers to improving or modifying existing travel plans based on user feedback and external information. 【0075】 The system of this invention utilizes natural language processing technology and generative AI models to generate personalized travel plans based on user preferences. This system mainly consists of terminals and servers, each playing a specific role. 【0076】 When planning a trip, users use a device to input their desired conditions, such as destination, budget, travel duration, type of accommodation, and activities of interest. This data is automatically transmitted to the server by the device. The device can be any common information processing device that can connect to the internet, such as a personal computer or smartphone. 【0077】 Upon receiving these preferences, the server analyzes the user's intent using natural language processing techniques. This analysis utilizes generative AI models, including advanced language models such as GPT-4®. The user's input is converted into a prompt, which is then fed into the AI ​​model for analysis. An example of a prompt might be: "Please plan a trip to Kyoto within the user's desired budget. The desired activity is a cultural experience." 【0078】 After analysis, the server accesses the database to retrieve past user data with similar travel preferences. Based on this data, the server generates a travel plan that best matches the user's budget constraints and preferences. It also retrieves real-time event information for the travel destination from an external API and incorporates it into the plan. This ensures that information about events and activities taking place during the trip is also included in the plan. 【0079】 For example, if a user enters conditions such as "I want to travel to Kyoto with a budget of 150,000 yen, and I want to prioritize cultural experiences," the server searches past data for plans related to cultural experiences in Kyoto and generates a travel plan that includes activities such as tea ceremony experiences, temple tours, and kimono rentals. This plan is presented to the user via their terminal and can be adjusted based on their feedback. In this way, the system can provide a customized travel plan that meets the user's expectations. 【0080】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0081】 Step 1: 【0082】 Users enter their travel preferences into a dedicated form on their device. This includes destination, budget, travel duration, type of accommodation, and activities of interest. When the user presses the "Submit" button, this information is sent from the device to the server. The input data is typically organized in text format and transferred to the server over the network. 【0083】 Step 2: 【0084】 The terminal sends the received user conditions to the server. Here, the data is securely transferred using the HTTPS protocol. On the server, the input data is assigned a series of transaction IDs, and a mechanism is in place to track data processing using these IDs. 【0085】 Step 3: 【0086】 The server analyzes the received user conditions using natural language processing techniques. This analysis employs a generative AI model, specifically a model like GPT-4, to tokenize the input sentence and identify key keywords and intents. The input is text data, and the output is a structured list of intents and conditions. 【0087】 Step 4: 【0088】 The server executes database queries based on the analysis results to retrieve similar past travel preference data. Using SQL queries, it searches for records that most closely match the user's budget, destination, and interests. The retrieved data forms the basis for generating travel plans that closely match the user's requests. 【0089】 Step 5: 【0090】 The server uses retrieved historical data and real-time event information to construct a travel plan that matches the user's intentions. In doing so, it utilizes external APIs to obtain the latest event information for the travel destination and integrates it into the plan. The output is a travel plan based on the user's preferences, including itinerary, recommended activities, and accommodation information. 【0091】 Step 6: 【0092】 The terminal receives the travel plan generated from the server and builds an interface to display it to the user. A graphical user interface (GUI) is used to visually display the details of the travel plan. The user can review the plan, provide feedback, or confirm the plan immediately. 【0093】 Step 7: 【0094】 When user feedback is received, the server receives that information and re-evaluates the travel plan and makes necessary modifications. The input is user feedback, and the output is the adjusted or finalized travel plan. Based on the feedback, the server re-utilizes the generating AI model to adaptively adjust the plan. 【0095】 (Application Example 1) 【0096】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0097】 When planning a trip, visitors often face challenges in efficiently enjoying sightseeing due to time constraints and inability to fully utilize information about their destinations. Furthermore, there is a need for a system that can suggest optimal sightseeing routes tailored to individual user interests in real time. 【0098】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0099】 In this invention, the server includes means for inputting the user's travel preferences, means for analyzing the user's input using natural language processing technology to identify the user's intentions, and means for learning past data with similar travel preferences to generate the most suitable travel plan for the user. This makes it possible to provide the optimal sightseeing route within a limited time based on the user's preferences and to create an efficient sightseeing plan that combines this with real-time event information. 【0100】 "User travel preferences" refers to detailed information about the user's desired destination, budget, duration, and activities of interest in their travel plans. 【0101】 "Natural language processing technology" refers to the technology used by computers to understand, generate, and analyze human language. 【0102】 "Learning from past data" refers to the process of analyzing data collected so far from similar travel preferences to generate more effective plans. 【0103】 A "travel plan" refers to a suggestion that combines places to visit, activities to participate in, and accommodations during a specific travel period, based on the user's preferences. 【0104】 "Real-time event information" refers to the latest information on events and activities at a specified travel destination, which can be dynamically incorporated into travel plans. 【0105】 "Tourism resources" refer to facilities, events, and experiences that possess historical, cultural, and natural value within a tourist destination. 【0106】 A "viewing route" refers to a plan that shows the order and route of tourist spots to visit based on conditions set by the user. 【0107】 The system implementing this invention begins with the user inputting their travel preferences via a mobile device. The user's device then transmits these preferences to a server. The server analyzes the user's input using natural language processing technology to identify the user's intent. Libraries such as NLTK can be used for natural language processing. 【0108】 Based on the analysis results, the server retrieves similar travel preference data from past databases and learns from the data. This generates the most suitable travel plan for the user. Furthermore, it incorporates real-time event information from the travel destination and suggests sightseeing routes that utilize local tourist resources. This information is obtained from smart city management systems in tourist areas. 【0109】 The generated travel plan is presented to the user's device, and after reviewing the plan, the user can provide feedback or confirm it. Upon receiving user feedback, the server re-evaluates the plan and makes revisions as needed. This dynamic feedback loop allows users to obtain more satisfying travel plans. 【0110】 For example, if a user enters the condition "I want to visit art galleries in Tokyo on a weekend in June," the server will refer to information on relevant art exhibitions and events and generate an optimal plan, including travel routes. 【0111】 Examples of prompt messages are as follows: 【0112】 "What's the best route for visiting art galleries in Tokyo? My budget is 20,000 yen, it's a weekend, and I'm going with a friend." 【0113】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0114】 Step 1: 【0115】 Users enter their travel preferences on their mobile devices. This information includes destination, budget, travel duration, and activities of interest. This information is then transmitted from the mobile device to the server. 【0116】 Step 2: 【0117】 The server analyzes the user's requested conditions using natural language processing techniques. The input data is in text format, and the server uses a library like NLTK to identify the user's intent. In this process, key keywords and phrases are extracted from the input information and output as structured data. 【0118】 Step 3: 【0119】 The server retrieves historical data from the database based on the analyzed user preferences. By executing database queries and retrieving a filtered dataset, it outputs the most suitable travel plan as a candidate. This candidate is selected from the dataset using an optimization algorithm. 【0120】 Step 4: 【0121】 The server uses an external API to retrieve real-time event information for the travel destination. The retrieved event information is added to the plan candidates and built into a proposed travel plan. In this process, the server processes real-time data and dynamically updates the travel plan. 【0122】 Step 5: 【0123】 The generated travel plan is sent to the device and presented to the user. The user views the plan on the device and provides feedback as needed. This feedback is recorded as data sent to the server via an intuitive interface. 【0124】 Step 6: 【0125】 The server analyzes user feedback and evaluates the travel plan. If necessary, it modifies the plan and generates a new, optimized travel plan. The final plan is then resent to the user's device based on their preferences and the latest information. 【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】 The system according to the present invention receives the user's travel preferences, analyzes their emotions using an emotion engine, and generates an optimal travel plan based on this analysis. A specific embodiment of this system is described below. 【0128】 Users can freely input their travel preferences and expectations / desires using their device. This includes information such as destination, budget, travel duration, activities of interest, and emotions they wish to experience. It is designed to allow users to express their emotions and desires in a more flexible format. 【0129】 The terminal sends user input data to the server. The server uses natural language processing technology to analyze the user's requests and desires based on this data, and identifies the emotions hidden in the user's input using an emotion engine. This analysis helps to understand the user's emotional state and builds a foundation for proposing a plan tailored to that state. 【0130】 Furthermore, the server retrieves data from past users with similar travel experiences based on the user's requests and emotional data. This allows it to learn past plans that are appropriate for the user's emotional state and derive patterns for making the best suggestions for the user. 【0131】 The server constructs a travel plan based on the collected data. This process selects the most suitable destination, accommodation, and sightseeing route based on the user's budget and interests, and enhances the sense of realism by including real-time event information. It also incorporates activities and itineraries that are appropriate to the user's emotional state into the suggestions. 【0132】 The terminal presents the completed travel plan to the user. The user reviews the plan and provides feedback. The server receives this feedback, re-evaluates the plan as needed, and makes adjustments based on the user's emotions. For example, if the user expresses a desire to relax, the server will suggest activities such as spa treatments or nature walks that are enhanced to reflect that desire. 【0133】 Thus, the system of the present invention can create a differentiated travel experience that is tailored to the individual emotions and needs of the user. 【0134】 The following describes the processing flow. 【0135】 Step 1: 【0136】 Users use their own devices to describe their travel preferences and expectations and feelings about the trip. The information entered includes desired destinations, budget, planned dates, activities of interest, and emotions they would like to experience. 【0137】 Step 2: 【0138】 The terminal formats the collected input data and sends it to the server. This data includes text about specific travel wishes and feelings. 【0139】 Step 3: 【0140】 The server analyzes the received data. First, it structures the data using natural language processing techniques to clarify the user's intentions and desires. At this stage, it uses an emotion engine to analyze the emotional state from the user's description. 【0141】 Step 4: 【0142】 Based on the user's analysis results, the server retrieves past travel data from the database for users with similar desires and emotional states. This is to allow users to refer to the successful experiences of other users with similar desires and emotions. 【0143】 Step 5: 【0144】 The server uses this information to generate travel plans. Considering budget and requirements, it selects appropriate destinations, accommodations, and activities, integrating real-time event information with an experience that matches the user's emotions. 【0145】 Step 6: 【0146】 The server sends the completed travel plan to the device. The plan includes a detailed itinerary, along with special recommended activities tailored to the user's mood. 【0147】 Step 7: 【0148】 The device displays the received travel plan to the user. The user can review the plan and provide feedback on its contents. 【0149】 Step 8: 【0150】 The server receives user feedback and modifies the plan as needed. Further adjustments are made based on user sentiment to provide a more ideal plan. 【0151】 This process allows the system to provide a travel experience tailored to the user's emotions and desires, and to present a personalized itinerary. 【0152】 (Example 2) 【0153】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0154】 Traditional travel planning systems have struggled to generate travel plans that fully reflect users' emotions and specific preferences. Furthermore, they lacked the ability to incorporate real-time event information and flexibly adjust plans based on user feedback, resulting in insufficient user satisfaction. 【0155】 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. 【0156】 In this invention, the server includes means for analyzing user input using language analysis technology to identify the user's intentions, means for generating a travel plan by learning past data with similar travel desires, and means for analyzing the user's emotional state and adjusting the travel plan based on those emotions. This makes it possible to generate a travel plan that more accurately reflects the user's emotions and desires. 【0157】 A "user" refers to a person who inputs their desired conditions and feelings into the travel planning system. 【0158】 "Language analysis technology" refers to techniques that use natural language processing to analyze user input and identify intentions and emotions. 【0159】 A "travel plan" refers to a travel suggestion that includes information such as destinations, accommodations, and activities, and is generated based on the user's wishes and feelings. 【0160】 "Real-time event information" refers to the latest event and activity information at a travel destination, and is data that is constantly updated to provide to users. 【0161】 "Emotional state" refers to the emotional situation or tendency analyzed based on user input. 【0162】 "Feedback" refers to the opinions and evaluations that users provide regarding the travel plans suggested by the system. 【0163】 "Budget constraints" refer to the range of money a user can afford when planning a trip. 【0164】 "Cost-effectiveness" refers to the economic efficiency that indicates how much a travel planning option contributes to the user's wishes and satisfaction. 【0165】 This invention is a system in which a user inputs their desired travel conditions and generates an optimal travel plan based on those conditions and emotions. This system mainly consists of a server, a terminal, and a generating AI model. 【0166】 Users input their travel destination, budget, travel duration, activities of interest, and desired emotions using their device. This input is done through a free-form text field, designed to allow users to freely express their feelings and desires. 【0167】 The terminal sends input data to the server via an HTTP POST request. The server analyzes this data using natural language processing (NLTK) techniques. The Python NLTK library is used in this process. An emotion engine is then used to identify the user's intent and emotional state from the analyzed data. A common natural language processing tool is used as the emotion engine. 【0168】 Next, the server accesses a database to retrieve past data from users with similar travel experiences. This database is assumed to be a typical relational database. Based on data from users who have traveled under similar conditions in the past, a generative AI model proposes the optimal travel plan. 【0169】 The generated travel plan includes destinations, accommodations, and sightseeing routes that take into account the user's budget and interests. Real-time event information is also provided, and activities that the user can enjoy at that moment are incorporated into the plan. External event information APIs are used to obtain this information. 【0170】 The terminal ultimately presents the travel plan received from the server to the user, displaying it in a visually easy-to-understand format. The user can provide feedback on the provided plan, and this feedback is sent back to the server. Based on the feedback, the server re-evaluates and adjusts the travel plan. 【0171】 For example, if a user enters the desire to "relax," the server will suggest a travel plan that includes hot springs and massage experiences, based on data from past users with similar desires. An example of a prompt might be, "I want to relax on my next trip. What kind of plan can you suggest?" In this way, a travel experience tailored to the user's individual feelings and desires can be provided. 【0172】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0173】 Step 1: 【0174】 The user enters their travel preferences using a device. The user uses text fields to enter information such as destination, budget, duration, activities of interest, and desired emotional experiences. This input data reflects the user's requests and feelings. 【0175】 Step 2: 【0176】 The terminal sends the data entered by the user to the server. An HTTP POST request is used for this transmission. The input data is packaged in JSON format and securely transferred to the server. 【0177】 Step 3: 【0178】 The server analyzes the received data using natural language processing techniques. The server uses the Python NLTK library to tokenize and semantically analyze the text. This analysis identifies the user's request and emotional state. The input is the user's raw text data, and the output is the analyzed intent and emotional labels. 【0179】 Step 4: 【0180】 The server retrieves past data from the database based on the analysis results, specifically data from users with similar travel experiences. The server sends queries to the relational database to search for past user data. The input is the analysis results, and the output is a set of similar past data. 【0181】 Step 5: 【0182】 The server generates a travel plan based on calculated emotional states and user requests. The generative AI model uses historical training data to select the optimal destination, accommodations, and sightseeing routes. Inputs are similar historical data, current requests, and emotional information, while the output is the completed travel plan. 【0183】 Step 6: 【0184】 The server retrieves real-time event information from an external API and integrates it into the travel plan. This adds information about events and activities taking place locally to the user's plan. The input is the travel plan, and the output is the plan with the event information added. 【0185】 Step 7: 【0186】 The device presents the user with a completed travel plan. The plan is formatted visually on the device, making it easy for the user to understand. 【0187】 Step 8: 【0188】 The user enters feedback on the presented plan from their device. This feedback includes satisfaction with the plan and any additional requests. The feedback is then sent back to the server. 【0189】 Step 9: 【0190】 The server analyzes user feedback and re-evaluates and adjusts the travel plan as needed. The server then uses natural language processing to analyze the feedback again and make sentiment-based corrections. The input is user feedback, and the output is the improved new travel plan. 【0191】 (Application Example 2) 【0192】 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". 【0193】 Traditional travel plan suggestion systems primarily offered suggestions based on user preferences and budgets, making it difficult to provide travel plans that addressed users' emotions and individual expectations for experiences. This resulted in a lack of suggestions that offered unique experiences or surprises, failing to improve overall travel satisfaction. Furthermore, while there was a demand for special dining experiences and emotionally driven suggestions at destinations, providing such services appropriately proved to be a challenging task. 【0194】 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. 【0195】 In this invention, the server includes means for inputting the user's desired travel conditions; means for analyzing the user's input using natural language processing technology to identify the user's emotions; means for learning past data of similar travel experiences to generate the most suitable travel plan for the user; and means for customizing the suggestions based on the emotion analysis. This makes it possible to provide a personalized travel experience that responds to the user's emotions and expectations, and to improve satisfaction with the travel experience, in particular, by introducing special experiences such as meals and events. 【0196】 "Means for inputting user travel preferences" refers to an interface through a terminal for travelers to input their travel requirements and expectations, including destination, mode of transportation, budget, and preferences for special dining experiences. 【0197】 "Means for analyzing user input using natural language processing technology and identifying user emotions" refers to a technology that analyzes text entered by a user using a language processing algorithm and accurately grasps the emotions and intentions contained therein. 【0198】 "A method for generating the most suitable travel plan for a user by learning from past data of users with similar travel experiences" refers to an algorithm that utilizes data from users who have taken similar trips in the past to suggest travel and activities that best match the current user. 【0199】 "Means of presenting the generated travel plan to the user" refers to a user interface that clearly displays the generated travel plan to the user and presents it in a selectable format. 【0200】 "Means of providing real-time activity information for destinations included in travel plans" refers to an information provision system that enriches the travel experience by providing users with the latest event and activity information for their destinations in real time. 【0201】 "Methods for customizing suggestions based on sentiment analysis" refers to technologies that personalize travel plans and activities based on the user's emotional state, providing suggestions that are best suited to the user. 【0202】 This invention is a system that generates an optimal travel plan based on the user's desired travel experience, thereby improving the travel experience. The user inputs their desired travel conditions using a terminal such as a smart device. These conditions include travel destination, mode of transportation, budget, and preferences for special dining experiences. 【0203】 The terminal sends the entered data to the server. The server analyzes the entered preferences using natural language processing techniques to identify the user's emotions. An emotion engine can be used for this emotion analysis. Based on the identified emotions, the server learns from past data of similar travel experiences and generates the most suitable travel plan for the user. This process involves text analysis libraries and custom AI models. 【0204】 The generated travel plan is presented to the user via the device. This plan incorporates real-time activity information at the destination and is a customized suggestion that takes into account the user's emotions and expectations. For example, if the user expresses the emotion of "wanting to experience a surprise," the suggestion, based on emotion analysis, might be to participate in a special local culinary event. 【0205】 An example of a prompt message would be: "Based on the user's input, 'I want to enjoy delicious food and experience new surprises,' please perform sentiment analysis and recommend a dining experience that suits that sentiment." This system allows travelers to have a more engaging and emotionally resonant travel experience. 【0206】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0207】 Step 1: 【0208】 The user enters their desired conditions. This input data includes destination, mode of transportation, budget, and the emotions they wish to experience. The terminal retrieves this information through the user interface and sends it to the server. The input includes text and numerical data, and the output generates a request message that is sent to the server. 【0209】 Step 2: 【0210】 The server analyzes the input data received from the user using natural language processing techniques. This involves using a text analysis library to extract meaning based on the user's requests and preferences. The input is the user's text data, and the output is the analyzed data structure. 【0211】 Step 3: 【0212】 The server uses a generative AI model based on the analyzed data to identify the user's emotions. This process utilizes an emotion engine, which performs data calculations to identify the emotional state from the user's input. The input is the analyzed data, and the output is information indicating the user's emotional state. 【0213】 Step 4: 【0214】 The server learns from past data of similar travel experiences by comparing acquired emotional information with historical databases. Data mining techniques are used to generate a travel plan that best matches the identified emotional state. The input is emotional information and historical data, and the output is a customized travel plan. 【0215】 Step 5: 【0216】 The generated travel plan is supplemented with real-time activity information. This completes the plan, which includes personalized suggestions based on the user's emotions. Activity information is retrieved via an external API and integrated into the plan. The input is the travel plan and activity information, and the output is the final plan including real-time information. 【0217】 Step 6: 【0218】 The server transfers the final travel plan to the user's terminal. The user can review the presented plan and make selections or modifications. The terminal displays the data received from the server in its user interface. The input is the final plan data, and the output is the plan visualized for the user. 【0219】 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. 【0220】 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. 【0221】 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. 【0222】 [Second Embodiment] 【0223】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0224】 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. 【0225】 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). 【0226】 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. 【0227】 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. 【0228】 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). 【0229】 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. 【0230】 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. 【0231】 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. 【0232】 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. 【0233】 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. 【0234】 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". 【0235】 The system according to the present invention receives the user's travel preferences and generates an optimal travel plan based on them. A specific embodiment of this system is described below. 【0236】 Users use their devices to fill out a form detailing their travel preferences. This includes destination, budget, travel duration, type of accommodation, and activities of interest. 【0237】 The terminal sends the entered conditions to the server. The server uses natural language processing technology to analyze the user's intent based on the received data. Using the results of the analysis, the server retrieves past user data with similar travel preferences from the database in order to generate candidate travel plans that closely match the user's wishes. 【0238】 Based on the acquired data, the server selects destinations, accommodations, and activities that fit the budget and requirements, and creates a plan that best suits the user's wishes. In this process, the server also takes real-time event information into consideration, and therefore refers to the latest event information taking place around the travel destination. 【0239】 The terminal displays the travel plan received from the server to the user. The user reviews this plan, provides feedback, or confirms the plan. If feedback is received, the server re-evaluates the plan based on it and makes necessary adjustments to provide a more satisfying plan. 【0240】 As a concrete example, suppose a user enters the following conditions: "I want to travel to Kyoto with a budget of 150,000 yen. I want to prioritize cultural experiences." The terminal sends this information to the server, which then analyzes it. The server searches past data for plans that include cultural experiences in Kyoto and generates a proposed plan incorporating activities such as "Kyoto tea ceremony experience, temple tours, and kimono rental." By also adding information about festivals held during the travel period to the proposal, the server can provide the user with the most suitable travel experience. 【0241】 In this way, the system of the present invention efficiently generates travel plans based on the user's wishes and conditions, and provides personalized services. 【0242】 The following describes the processing flow. 【0243】 Step 1: 【0244】 Users enter their travel preferences using their own devices. This input includes details such as destination, budget, duration, and areas of interest such as activities and tourist attractions. 【0245】 Step 2: 【0246】 The terminal sends the user's entered conditions to the server as a data packet. This packet contains user information and travel conditions. 【0247】 Step 3: 【0248】 The server analyzes the data received from the terminal. Using natural language processing technology, it analyzes the input content and identifies the user's intentions and desires. 【0249】 Step 4: 【0250】 Based on the analyzed information, the server retrieves past user data from a database showing similar travel experiences and preferences. This gathers reference information to create the most suitable plan for the user. 【0251】 Step 5: 【0252】 The server creates a travel plan based on the acquired data. Based on budget, desired conditions, and past successful plans, it selects the optimal destination, accommodation, and sightseeing route. 【0253】 Step 6: 【0254】 The server collects real-time event information taking place at the travel destination during the trip and adds it to the plan. This provides users with the latest event information. 【0255】 Step 7: 【0256】 The server sends the final travel plan to the device. This plan includes selected travel elements and event information. 【0257】 Step 8: 【0258】 The device displays a travel plan to the user. The user reviews the plan and accepts it if satisfied, or provides feedback if any modifications are needed. 【0259】 Step 9: 【0260】 Based on user feedback, the server re-evaluates the plan, makes corrections as needed, and resubmits the final plan. 【0261】 (Example 1) 【0262】 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." 【0263】 Current travel plan generation systems struggle to flexibly respond to diverse user needs, particularly in providing plans that adequately consider budget constraints and real-time event information. As a result, users' travel experiences sometimes end up falling short of expectations. Furthermore, the adaptive adjustment of plans based on feedback is insufficient, limiting the ability to provide plans that truly satisfy users. 【0264】 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. 【0265】 In this invention, the server includes means for analyzing user input using natural language processing technology, means for generating a travel plan by learning from past data of users with similar travel preferences, and means for optimizing the travel plan based on budget constraints. This makes it possible to generate a more satisfying travel plan that corresponds to the user's individual conditions and intentions. 【0266】 A "user" refers to an individual or group that intends to use the system to plan a trip. 【0267】 "Desired conditions" refer to the requirements that users specify when planning a trip, such as destination, budget, duration of travel, type of accommodation, and activities of interest. 【0268】 "Natural language processing technology" refers to the technology used by computers to understand and interpret human language. 【0269】 A "travel plan" refers to a detailed plan for a trip desired by the user, including specific destinations, accommodations, and information on activities and events. 【0270】 "Real-time event information" refers to the latest information on specific events and activities taking place at your travel destination during your visit period. 【0271】 A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to generate output for a specific task. 【0272】 A "prompt" refers to the input text used to give instructions or conditions to a generative AI model. 【0273】 "Feedback" refers to opinions and impressions of travel plans provided by users, and may include requests for system improvements. 【0274】 "Budget constraints" refer to the financial limitations or restrictions that users must consider when planning a trip. 【0275】 "Adaptive adjustment" refers to improving or modifying existing travel plans based on user feedback and external information. 【0276】 The system of this invention utilizes natural language processing technology and generative AI models to generate personalized travel plans based on user preferences. This system mainly consists of terminals and servers, each playing a specific role. 【0277】 When planning a trip, users use a device to input their desired conditions, such as destination, budget, travel duration, type of accommodation, and activities of interest. This data is automatically transmitted to the server by the device. The device can be any common information processing device that can connect to the internet, such as a personal computer or smartphone. 【0278】 Upon receiving these preferences, the server analyzes the user's intent using natural language processing techniques. This analysis employs generative AI models, including advanced language models such as GPT-4. The user's input is converted into a prompt, which is then fed into the AI ​​model for analysis. An example of a prompt might be: "Please plan a trip to Kyoto within the user's desired budget. The desired activity is a cultural experience." 【0279】 After analysis, the server accesses the database to retrieve past user data with similar travel preferences. Based on this data, the server generates a travel plan that best matches the user's budget constraints and preferences. It also retrieves real-time event information for the travel destination from an external API and incorporates it into the plan. This ensures that information about events and activities taking place during the trip is also included in the plan. 【0280】 For example, if a user enters conditions such as "I want to travel to Kyoto with a budget of 150,000 yen, and I want to prioritize cultural experiences," the server searches past data for plans related to cultural experiences in Kyoto and generates a travel plan that includes activities such as tea ceremony experiences, temple tours, and kimono rentals. This plan is presented to the user via their terminal and can be adjusted based on their feedback. In this way, the system can provide a customized travel plan that meets the user's expectations. 【0281】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0282】 Step 1: 【0283】 The user inputs their travel wish conditions into the dedicated form on the terminal. The inputs include the destination, budget, travel period, type of accommodation, interesting activities, etc. When the user presses the "Send" button, these inputs are sent from the terminal to the server. The input data is usually organized in text format and transferred to the server via the network. 【0284】 Step 2: 【0285】 The terminal sends the received user conditions to the server. Here, the HTTPS protocol is used to transfer the data securely. At the server, a mechanism is adopted where a series of transaction IDs are assigned to the input data and used to track data processing. 【0286】 Step 3: 【0287】 The server analyzes the received user conditions using natural language processing technology. In this analysis, a generative AI model is used, specifically a model like GPT-4, to tokenize the input text and identify important keywords and intentions. The input is text data, and the output is a structured list of intentions and conditions. 【0288】 Step 4: 【0289】 The server executes a database query based on the analysis results to obtain past similar travel wish data. An SQL query is used to search for records closest to the budget, destination, and interesting activities. The obtained data serves as a basis for generating a travel plan close to the user's requirements. 【0290】 Step 5: 【0291】 The server uses retrieved historical data and real-time event information to construct a travel plan that matches the user's intentions. In doing so, it utilizes external APIs to obtain the latest event information for the travel destination and integrates it into the plan. The output is a travel plan based on the user's preferences, including itinerary, recommended activities, and accommodation information. 【0292】 Step 6: 【0293】 The terminal receives the travel plan generated from the server and builds an interface to display it to the user. A graphical user interface (GUI) is used to visually display the details of the travel plan. The user can review the plan, provide feedback, or confirm the plan immediately. 【0294】 Step 7: 【0295】 When user feedback is received, the server receives that information and re-evaluates the travel plan and makes necessary modifications. The input is user feedback, and the output is the adjusted or finalized travel plan. Based on the feedback, the server re-utilizes the generating AI model to adaptively adjust the plan. 【0296】 (Application Example 1) 【0297】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0298】 When planning a trip, visitors often face challenges in efficiently enjoying sightseeing due to time constraints and inability to fully utilize information about their destinations. Furthermore, there is a need for a system that can suggest optimal sightseeing routes tailored to individual user interests in real time. 【0299】 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. 【0300】 In this invention, the server includes means for inputting desired conditions related to the user's trip, means for analyzing the user's input using natural language processing technology to identify the user's intention, and means for learning past data with similar travel desires to generate the most suitable travel plan for the user. Thereby, an optimal sightseeing route can be provided within a limited time based on the user's desires, and an efficient sightseeing plan can be formulated by combining real-time event information. 【0301】 The "desired conditions related to the user's trip" refers to detailed information such as the destination, budget, duration, and activities of interest that the user hopes for in the travel plan. 【0302】 The "natural language processing technology" refers to the technology used by a computer to understand, generate, and analyze human language. 【0303】 "Learning past data" refers to the process of performing analysis based on data with similar travel desires collected so far to generate a more effective plan. 【0304】 The "travel plan" refers to a proposal that combines places to visit, activities to participate in, accommodation, etc. during a specific travel period based on the user's desires. 【0305】 The "real-time event information" refers to information on the latest events and activities at the designated travel destination, which can be dynamically incorporated into the travel plan. 【0306】 The "tourist resources" refers to facilities, events, experiences, etc. with historical, cultural, and natural values possessed by the tourist destination. 【0307】 The "appreciation route" refers to a plan indicating the order and route of tourist destinations to be visited based on the conditions set by the user. 【0308】 The system implementing this invention begins with the user inputting their travel preferences via a mobile device. The user's device then transmits these preferences to a server. The server analyzes the user's input using natural language processing technology to identify the user's intent. Libraries such as NLTK can be used for natural language processing. 【0309】 Based on the analysis results, the server retrieves similar travel preference data from past databases and learns from the data. This generates the most suitable travel plan for the user. Furthermore, it incorporates real-time event information from the travel destination and suggests sightseeing routes that utilize local tourist resources. This information is obtained from smart city management systems in tourist areas. 【0310】 The generated travel plan is presented to the user's device, and after reviewing the plan, the user can provide feedback or confirm it. Upon receiving user feedback, the server re-evaluates the plan and makes revisions as needed. This dynamic feedback loop allows users to obtain more satisfying travel plans. 【0311】 For example, if a user enters the condition "I want to visit art galleries in Tokyo on a weekend in June," the server will refer to information on relevant art exhibitions and events and generate an optimal plan, including travel routes. 【0312】 Examples of prompt messages are as follows: 【0313】 "What's the best route for visiting art galleries in Tokyo? My budget is 20,000 yen, it's a weekend, and I'm going with a friend." 【0314】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0315】 Step 1: 【0316】 Users enter their travel preferences on their mobile devices. This information includes destination, budget, travel duration, and activities of interest. This information is then transmitted from the mobile device to the server. 【0317】 Step 2: 【0318】 The server analyzes the user's requested conditions using natural language processing techniques. The input data is in text format, and the server uses a library like NLTK to identify the user's intent. In this process, key keywords and phrases are extracted from the input information and output as structured data. 【0319】 Step 3: 【0320】 The server retrieves historical data from the database based on the analyzed user preferences. By executing database queries and retrieving a filtered dataset, it outputs the most suitable travel plan as a candidate. This candidate is selected from the dataset using an optimization algorithm. 【0321】 Step 4: 【0322】 The server uses an external API to retrieve real-time event information for the travel destination. The retrieved event information is added to the plan candidates and built into a proposed travel plan. In this process, the server processes real-time data and dynamically updates the travel plan. 【0323】 Step 5: 【0324】 The generated travel plan is sent to the device and presented to the user. The user views the plan on the device and provides feedback as needed. This feedback is recorded as data sent to the server via an intuitive interface. 【0325】 Step 6: 【0326】 The server analyzes user feedback and evaluates the travel plan. If necessary, it modifies the plan and generates a new, optimized travel plan. The final plan is then resent to the user's device based on their preferences and the latest information. 【0327】 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. 【0328】 The system according to the present invention receives the user's travel preferences, analyzes their emotions using an emotion engine, and generates an optimal travel plan based on this analysis. A specific embodiment of this system is described below. 【0329】 Users can freely input their travel preferences and expectations / desires using their device. This includes information such as destination, budget, travel duration, activities of interest, and emotions they wish to experience. It is designed to allow users to express their emotions and desires in a more flexible format. 【0330】 The terminal sends user input data to the server. The server uses natural language processing technology to analyze the user's requests and desires based on this data, and identifies the emotions hidden in the user's input using an emotion engine. This analysis helps to understand the user's emotional state and builds a foundation for proposing a plan tailored to that state. 【0331】 Furthermore, the server retrieves data from past users with similar travel experiences based on the user's requests and emotional data. This allows it to learn past plans that are appropriate for the user's emotional state and derive patterns for making the best suggestions for the user. 【0332】 The server constructs a travel plan based on the collected data. This process selects the most suitable destination, accommodation, and sightseeing route based on the user's budget and interests, and enhances the sense of realism by including real-time event information. It also incorporates activities and itineraries that are appropriate to the user's emotional state into the suggestions. 【0333】 The terminal presents the completed travel plan to the user. The user reviews the plan and provides feedback. The server receives this feedback, re-evaluates the plan as needed, and makes adjustments based on the user's emotions. For example, if the user expresses a desire to relax, the server will suggest activities such as spa treatments or nature walks that are enhanced to reflect that desire. 【0334】 Thus, the system of the present invention can create a differentiated travel experience that is tailored to the individual emotions and needs of the user. 【0335】 The following describes the processing flow. 【0336】 Step 1: 【0337】 Users use their own devices to describe their travel preferences and expectations and feelings about the trip. The information entered includes desired destinations, budget, planned dates, activities of interest, and emotions they would like to experience. 【0338】 Step 2: 【0339】 The terminal formats the collected input data and sends it to the server. This data includes text about specific travel wishes and feelings. 【0340】 Step 3: 【0341】 The server analyzes the received data. First, it structures the data using natural language processing techniques to clarify the user's intentions and desires. At this stage, it uses an emotion engine to analyze the emotional state from the user's description. 【0342】 Step 4: 【0343】 Based on the user's analysis results, the server retrieves past travel data from the database for users with similar desires and emotional states. This is to allow users to refer to the successful experiences of other users with similar desires and emotions. 【0344】 Step 5: 【0345】 The server uses this information to generate travel plans. Considering budget and requirements, it selects appropriate destinations, accommodations, and activities, integrating real-time event information with an experience that matches the user's emotions. 【0346】 Step 6: 【0347】 The server sends the completed travel plan to the device. The plan includes a detailed itinerary, along with special recommended activities tailored to the user's mood. 【0348】 Step 7: 【0349】 The device displays the received travel plan to the user. The user can review the plan and provide feedback on its contents. 【0350】 Step 8: 【0351】 The server receives user feedback and modifies the plan as needed. Further adjustments are made based on user sentiment to provide a more ideal plan. 【0352】 This process allows the system to provide a travel experience tailored to the user's emotions and desires, and to present a personalized itinerary. 【0353】 (Example 2) 【0354】 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". 【0355】 Traditional travel planning systems have struggled to generate travel plans that fully reflect users' emotions and specific preferences. Furthermore, they lacked the ability to incorporate real-time event information and flexibly adjust plans based on user feedback, resulting in insufficient user satisfaction. 【0356】 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. 【0357】 In this invention, the server includes means for analyzing user input using language analysis technology to identify the user's intentions, means for generating a travel plan by learning past data with similar travel desires, and means for analyzing the user's emotional state and adjusting the travel plan based on those emotions. This makes it possible to generate a travel plan that more accurately reflects the user's emotions and desires. 【0358】 A "user" refers to a person who inputs their desired conditions and feelings into the travel planning system. 【0359】 "Language analysis technology" refers to techniques that use natural language processing to analyze user input and identify intentions and emotions. 【0360】 A "travel plan" refers to a travel suggestion that includes information such as destinations, accommodations, and activities, and is generated based on the user's wishes and feelings. 【0361】 "Real-time event information" refers to the latest event and activity information at a travel destination, and is data that is constantly updated to provide to users. 【0362】 "Emotional state" refers to the emotional situation or tendency analyzed based on user input. 【0363】 "Feedback" refers to the opinions and evaluations that users provide regarding the travel plans suggested by the system. 【0364】 "Budget constraints" refer to the range of money a user can afford when planning a trip. 【0365】 "Cost-effectiveness" refers to the economic efficiency that indicates how much a travel planning option contributes to the user's wishes and satisfaction. 【0366】 This invention is a system in which a user inputs their desired travel conditions and generates an optimal travel plan based on those conditions and emotions. This system mainly consists of a server, a terminal, and a generating AI model. 【0367】 Users input their travel destination, budget, travel duration, activities of interest, and desired emotions using their device. This input is done through a free-form text field, designed to allow users to freely express their feelings and desires. 【0368】 The terminal sends input data to the server via an HTTP POST request. The server analyzes this data using natural language processing (NLTK) techniques. The Python NLTK library is used in this process. An emotion engine is then used to identify the user's intent and emotional state from the analyzed data. A common natural language processing tool is used as the emotion engine. 【0369】 Next, the server accesses a database to retrieve past data from users with similar travel experiences. This database is assumed to be a typical relational database. Based on data from users who have traveled under similar conditions in the past, a generative AI model proposes the optimal travel plan. 【0370】 The generated travel plan includes destinations, accommodations, and sightseeing routes that take into account the user's budget and interests. Real-time event information is also provided, and activities that the user can enjoy at that moment are incorporated into the plan. External event information APIs are used to obtain this information. 【0371】 The terminal ultimately presents the travel plan received from the server to the user, displaying it in a visually easy-to-understand format. The user can provide feedback on the provided plan, and this feedback is sent back to the server. Based on the feedback, the server re-evaluates and adjusts the travel plan. 【0372】 For example, if a user enters the desire to "relax," the server will suggest a travel plan that includes hot springs and massage experiences, based on data from past users with similar desires. An example of a prompt might be, "I want to relax on my next trip. What kind of plan can you suggest?" In this way, a travel experience tailored to the user's individual feelings and desires can be provided. 【0373】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0374】 Step 1: 【0375】 The user enters their travel preferences using a device. The user uses text fields to enter information such as destination, budget, duration, activities of interest, and desired emotional experiences. This input data reflects the user's requests and feelings. 【0376】 Step 2: 【0377】 The terminal sends the data entered by the user to the server. An HTTP POST request is used for this transmission. The input data is packaged in JSON format and securely transferred to the server. 【0378】 Step 3: 【0379】 The server analyzes the received data using natural language processing techniques. The server uses the Python NLTK library to tokenize and semantically analyze the text. This analysis identifies the user's request and emotional state. The input is the user's raw text data, and the output is the analyzed intent and emotional labels. 【0380】 Step 4: 【0381】 The server retrieves past data from the database based on the analysis results, specifically data from users with similar travel experiences. The server sends queries to the relational database to search for past user data. The input is the analysis results, and the output is a set of similar past data. 【0382】 Step 5: 【0383】 The server generates a travel plan based on calculated emotional states and user requests. The generative AI model uses historical training data to select the optimal destination, accommodations, and sightseeing routes. Inputs are similar historical data, current requests, and emotional information, while the output is the completed travel plan. 【0384】 Step 6: 【0385】 The server retrieves real-time event information from an external API and integrates it into the travel plan. This adds information about events and activities taking place locally to the user's plan. The input is the travel plan, and the output is the plan with the event information added. 【0386】 Step 7: 【0387】 The device presents the user with a completed travel plan. The plan is formatted visually on the device, making it easy for the user to understand. 【0388】 Step 8: 【0389】 The user enters feedback on the presented plan from their device. This feedback includes satisfaction with the plan and any additional requests. The feedback is then sent back to the server. 【0390】 Step 9: 【0391】 The server analyzes user feedback and re-evaluates and adjusts the travel plan as needed. The server then uses natural language processing to analyze the feedback again and make sentiment-based corrections. The input is user feedback, and the output is the improved new travel plan. 【0392】 (Application Example 2) 【0393】 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." 【0394】 Traditional travel plan suggestion systems primarily offered suggestions based on user preferences and budgets, making it difficult to provide travel plans that addressed users' emotions and individual expectations for experiences. This resulted in a lack of suggestions that offered unique experiences or surprises, failing to improve overall travel satisfaction. Furthermore, while there was a demand for special dining experiences and emotionally driven suggestions at destinations, providing such services appropriately proved to be a challenging task. 【0395】 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. 【0396】 In this invention, the server includes means for inputting the user's desired travel conditions; means for analyzing the user's input using natural language processing technology to identify the user's emotions; means for learning past data of similar travel experiences to generate the most suitable travel plan for the user; and means for customizing the suggestions based on the emotion analysis. This makes it possible to provide a personalized travel experience that responds to the user's emotions and expectations, and to improve satisfaction with the travel experience, in particular, by introducing special experiences such as meals and events. 【0397】 "Means for inputting user travel preferences" refers to an interface through a terminal for travelers to input their travel requirements and expectations, including destination, mode of transportation, budget, and preferences for special dining experiences. 【0398】 "Means for analyzing user input using natural language processing technology and identifying user emotions" refers to a technology that analyzes text entered by a user using a language processing algorithm and accurately grasps the emotions and intentions contained therein. 【0399】 "A method for generating the most suitable travel plan for a user by learning from past data of users with similar travel experiences" refers to an algorithm that utilizes data from users who have taken similar trips in the past to suggest travel and activities that best match the current user. 【0400】 "Means of presenting the generated travel plan to the user" refers to a user interface that clearly displays the generated travel plan to the user and presents it in a selectable format. 【0401】 "Means of providing real-time activity information for destinations included in travel plans" refers to an information provision system that enriches the travel experience by providing users with the latest event and activity information for their destinations in real time. 【0402】 "Methods for customizing suggestions based on sentiment analysis" refers to technologies that personalize travel plans and activities based on the user's emotional state, providing suggestions that are best suited to the user. 【0403】 This invention is a system that generates an optimal travel plan based on the user's desired travel experience, thereby improving the travel experience. The user inputs their desired travel conditions using a terminal such as a smart device. These conditions include travel destination, mode of transportation, budget, and preferences for special dining experiences. 【0404】 The terminal sends the entered data to the server. The server analyzes the entered preferences using natural language processing techniques to identify the user's emotions. An emotion engine can be used for this emotion analysis. Based on the identified emotions, the server learns from past data of similar travel experiences and generates the most suitable travel plan for the user. This process involves text analysis libraries and custom AI models. 【0405】 The generated travel plan is presented to the user via the device. This plan incorporates real-time activity information at the destination and is a customized suggestion that takes into account the user's emotions and expectations. For example, if the user expresses the emotion of "wanting to experience a surprise," the suggestion, based on emotion analysis, might be to participate in a special local culinary event. 【0406】 An example of a prompt message would be: "Based on the user's input, 'I want to enjoy delicious food and experience new surprises,' please perform sentiment analysis and recommend a dining experience that suits that sentiment." This system allows travelers to have a more engaging and emotionally resonant travel experience. 【0407】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0408】 Step 1: 【0409】 The user enters their desired conditions. This input data includes destination, mode of transportation, budget, and the emotions they wish to experience. The terminal retrieves this information through the user interface and sends it to the server. The input includes text and numerical data, and the output generates a request message that is sent to the server. 【0410】 Step 2: 【0411】 The server analyzes the input data received from the user using natural language processing techniques. This involves using a text analysis library to extract meaning based on the user's requests and preferences. The input is the user's text data, and the output is the analyzed data structure. 【0412】 Step 3: 【0413】 The server uses a generative AI model based on the analyzed data to identify the user's emotions. This process utilizes an emotion engine, which performs data calculations to identify the emotional state from the user's input. The input is the analyzed data, and the output is information indicating the user's emotional state. 【0414】 Step 4: 【0415】 The server learns from past data of similar travel experiences by comparing acquired emotional information with historical databases. Data mining techniques are used to generate a travel plan that best matches the identified emotional state. The input is emotional information and historical data, and the output is a customized travel plan. 【0416】 Step 5: 【0417】 The generated travel plan is supplemented with real-time activity information. This completes the plan, which includes personalized suggestions based on the user's emotions. Activity information is retrieved via an external API and integrated into the plan. The input is the travel plan and activity information, and the output is the final plan including real-time information. 【0418】 Step 6: 【0419】 The server transfers the final travel plan to the user's terminal. The user can review the presented plan and make selections or modifications. The terminal displays the data received from the server in its user interface. The input is the final plan data, and the output is the plan visualized for the user. 【0420】 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. 【0421】 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. 【0422】 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. 【0423】 [Third Embodiment] 【0424】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0425】 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. 【0426】 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). 【0427】 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. 【0428】 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. 【0429】 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). 【0430】 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. 【0431】 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. 【0432】 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. 【0433】 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. 【0434】 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. 【0435】 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". 【0436】 The system according to the present invention receives the user's travel preferences and generates an optimal travel plan based on them. A specific embodiment of this system is described below. 【0437】 Users use their devices to fill out a form detailing their travel preferences. This includes destination, budget, travel duration, type of accommodation, and activities of interest. 【0438】 The terminal sends the entered conditions to the server. The server uses natural language processing technology to analyze the user's intent based on the received data. Using the results of the analysis, the server retrieves past user data with similar travel preferences from the database in order to generate candidate travel plans that closely match the user's wishes. 【0439】 Based on the acquired data, the server selects destinations, accommodations, and activities that fit the budget and requirements, and creates a plan that best suits the user's wishes. In this process, the server also takes real-time event information into consideration, and therefore refers to the latest event information taking place around the travel destination. 【0440】 The terminal displays the travel plan received from the server to the user. The user reviews this plan, provides feedback, or confirms the plan. If feedback is received, the server re-evaluates the plan based on it and makes necessary adjustments to provide a more satisfying plan. 【0441】 As a concrete example, suppose a user enters the following conditions: "I want to travel to Kyoto with a budget of 150,000 yen. I want to prioritize cultural experiences." The terminal sends this information to the server, which then analyzes it. The server searches past data for plans that include cultural experiences in Kyoto and generates a proposed plan incorporating activities such as "Kyoto tea ceremony experience, temple tours, and kimono rental." By also adding information about festivals held during the travel period to the proposal, the server can provide the user with the most suitable travel experience. 【0442】 In this way, the system of the present invention efficiently generates travel plans based on the user's wishes and conditions, and provides personalized services. 【0443】 The following describes the processing flow. 【0444】 Step 1: 【0445】 Users enter their travel preferences using their own devices. This input includes details such as destination, budget, duration, and areas of interest such as activities and tourist attractions. 【0446】 Step 2: 【0447】 The terminal sends the user's entered conditions to the server as a data packet. This packet contains user information and travel conditions. 【0448】 Step 3: 【0449】 The server analyzes the data received from the terminal. Using natural language processing technology, it analyzes the input content and identifies the user's intentions and desires. 【0450】 Step 4: 【0451】 Based on the analyzed information, the server retrieves past user data from a database showing similar travel experiences and preferences. This gathers reference information to create the most suitable plan for the user. 【0452】 Step 5: 【0453】 The server creates a travel plan based on the acquired data. Based on budget, desired conditions, and past successful plans, it selects the optimal destination, accommodation, and sightseeing route. 【0454】 Step 6: 【0455】 The server collects real-time event information taking place at the travel destination during the trip and adds it to the plan. This provides users with the latest event information. 【0456】 Step 7: 【0457】 The server sends the final travel plan to the device. This plan includes selected travel elements and event information. 【0458】 Step 8: 【0459】 The device displays a travel plan to the user. The user reviews the plan and accepts it if satisfied, or provides feedback if any modifications are needed. 【0460】 Step 9: 【0461】 Based on user feedback, the server re-evaluates the plan, makes corrections as needed, and resubmits the final plan. 【0462】 (Example 1) 【0463】 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." 【0464】 Current travel plan generation systems struggle to flexibly respond to diverse user needs, particularly in providing plans that adequately consider budget constraints and real-time event information. As a result, users' travel experiences sometimes end up falling short of expectations. Furthermore, the adaptive adjustment of plans based on feedback is insufficient, limiting the ability to provide plans that truly satisfy users. 【0465】 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. 【0466】 In this invention, the server includes means for analyzing user input using natural language processing technology, means for generating a travel plan by learning from past data of users with similar travel preferences, and means for optimizing the travel plan based on budget constraints. This makes it possible to generate a more satisfying travel plan that corresponds to the user's individual conditions and intentions. 【0467】 A "user" refers to an individual or group that intends to use the system to plan a trip. 【0468】 "Desired conditions" refer to the requirements that users specify when planning a trip, such as destination, budget, duration of travel, type of accommodation, and activities of interest. 【0469】 "Natural language processing technology" refers to the technology used by computers to understand and interpret human language. 【0470】 A "travel plan" refers to a detailed plan for a trip desired by the user, including specific destinations, accommodations, and information on activities and events. 【0471】 "Real-time event information" refers to the latest information on specific events and activities taking place at your travel destination during your visit period. 【0472】 A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to generate output for a specific task. 【0473】 A "prompt" refers to the input text used to give instructions or conditions to a generative AI model. 【0474】 "Feedback" refers to opinions and impressions of travel plans provided by users, and may include requests for system improvements. 【0475】 "Budget constraints" refer to the financial limitations or restrictions that users must consider when planning a trip. 【0476】 "Adaptive adjustment" refers to improving or modifying existing travel plans based on user feedback and external information. 【0477】 The system of this invention utilizes natural language processing technology and generative AI models to generate personalized travel plans based on user preferences. This system mainly consists of terminals and servers, each playing a specific role. 【0478】 When planning a trip, users use a device to input their desired conditions, such as destination, budget, travel duration, type of accommodation, and activities of interest. This data is automatically transmitted to the server by the device. The device can be any common information processing device that can connect to the internet, such as a personal computer or smartphone. 【0479】 Upon receiving these preferences, the server analyzes the user's intent using natural language processing techniques. This analysis employs generative AI models, including advanced language models such as GPT-4. The user's input is converted into a prompt, which is then fed into the AI ​​model for analysis. An example of a prompt might be: "Please plan a trip to Kyoto within the user's desired budget. The desired activity is a cultural experience." 【0480】 After analysis, the server accesses the database to retrieve past user data with similar travel preferences. Based on this data, the server generates a travel plan that best matches the user's budget constraints and preferences. It also retrieves real-time event information for the travel destination from an external API and incorporates it into the plan. This ensures that information about events and activities taking place during the trip is also included in the plan. 【0481】 For example, if a user enters conditions such as "I want to travel to Kyoto with a budget of 150,000 yen, and I want to prioritize cultural experiences," the server searches past data for plans related to cultural experiences in Kyoto and generates a travel plan that includes activities such as tea ceremony experiences, temple tours, and kimono rentals. This plan is presented to the user via their terminal and can be adjusted based on their feedback. In this way, the system can provide a customized travel plan that meets the user's expectations. 【0482】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0483】 Step 1: 【0484】 Users enter their travel preferences into a dedicated form on their device. This includes destination, budget, travel duration, type of accommodation, and activities of interest. When the user presses the "Submit" button, this information is sent from the device to the server. The input data is typically organized in text format and transferred to the server over the network. 【0485】 Step 2: 【0486】 The terminal sends the received user conditions to the server. Here, the data is securely transferred using the HTTPS protocol. On the server, the input data is assigned a series of transaction IDs, and a mechanism is in place to track data processing using these IDs. 【0487】 Step 3: 【0488】 The server analyzes the received user conditions using natural language processing techniques. This analysis employs a generative AI model, specifically a model like GPT-4, to tokenize the input sentence and identify key keywords and intents. The input is text data, and the output is a structured list of intents and conditions. 【0489】 Step 4: 【0490】 The server executes database queries based on the analysis results to retrieve similar past travel preference data. Using SQL queries, it searches for records that most closely match the user's budget, destination, and interests. The retrieved data forms the basis for generating travel plans that closely match the user's requests. 【0491】 Step 5: 【0492】 The server uses retrieved historical data and real-time event information to construct a travel plan that matches the user's intentions. In doing so, it utilizes external APIs to obtain the latest event information for the travel destination and integrates it into the plan. The output is a travel plan based on the user's preferences, including itinerary, recommended activities, and accommodation information. 【0493】 Step 6: 【0494】 The terminal receives the travel plan generated from the server and builds an interface to display it to the user. A graphical user interface (GUI) is used to visually display the details of the travel plan. The user can review the plan, provide feedback, or confirm the plan immediately. 【0495】 Step 7: 【0496】 When user feedback is received, the server receives that information and re-evaluates the travel plan and makes necessary modifications. The input is user feedback, and the output is the adjusted or finalized travel plan. Based on the feedback, the server re-utilizes the generating AI model to adaptively adjust the plan. 【0497】 (Application Example 1) 【0498】 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." 【0499】 When planning a trip, visitors often face challenges in efficiently enjoying sightseeing due to time constraints and inability to fully utilize information about their destinations. Furthermore, there is a need for a system that can suggest optimal sightseeing routes tailored to individual user interests in real time. 【0500】 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. 【0501】 In this invention, the server includes means for inputting the user's travel preferences, means for analyzing the user's input using natural language processing technology to identify the user's intentions, and means for learning past data with similar travel preferences to generate the most suitable travel plan for the user. This makes it possible to provide the optimal sightseeing route within a limited time based on the user's preferences and to create an efficient sightseeing plan that combines this with real-time event information. 【0502】 "User travel preferences" refers to detailed information about the user's desired destination, budget, duration, and activities of interest in their travel plans. 【0503】 "Natural language processing technology" refers to the technology used by computers to understand, generate, and analyze human language. 【0504】 "Learning from past data" refers to the process of analyzing data collected so far from similar travel preferences to generate more effective plans. 【0505】 A "travel plan" refers to a suggestion that combines places to visit, activities to participate in, and accommodations during a specific travel period, based on the user's preferences. 【0506】 "Real-time event information" refers to the latest information on events and activities at a specified travel destination, which can be dynamically incorporated into travel plans. 【0507】 "Tourism resources" refer to facilities, events, and experiences that possess historical, cultural, and natural value within a tourist destination. 【0508】 A "viewing route" refers to a plan that shows the order and route of tourist spots to visit based on conditions set by the user. 【0509】 The system implementing this invention begins with the user inputting their travel preferences via a mobile device. The user's device then transmits these preferences to a server. The server analyzes the user's input using natural language processing technology to identify the user's intent. Libraries such as NLTK can be used for natural language processing. 【0510】 Based on the analysis results, the server retrieves similar travel preference data from past databases and learns from the data. This generates the most suitable travel plan for the user. Furthermore, it incorporates real-time event information from the travel destination and suggests sightseeing routes that utilize local tourist resources. This information is obtained from smart city management systems in tourist areas. 【0511】 The generated travel plan is presented to the user's device, and after reviewing the plan, the user can provide feedback or confirm it. Upon receiving user feedback, the server re-evaluates the plan and makes revisions as needed. This dynamic feedback loop allows users to obtain more satisfying travel plans. 【0512】 For example, if a user enters the condition "I want to visit art galleries in Tokyo on a weekend in June," the server will refer to information on relevant art exhibitions and events and generate an optimal plan, including travel routes. 【0513】 Examples of prompt messages are as follows: 【0514】 "What's the best route for visiting art galleries in Tokyo? My budget is 20,000 yen, it's a weekend, and I'm going with a friend." 【0515】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0516】 Step 1: 【0517】 Users enter their travel preferences on their mobile devices. This information includes destination, budget, travel duration, and activities of interest. This information is then transmitted from the mobile device to the server. 【0518】 Step 2: 【0519】 The server analyzes the user's requested conditions using natural language processing techniques. The input data is in text format, and the server uses a library like NLTK to identify the user's intent. In this process, key keywords and phrases are extracted from the input information and output as structured data. 【0520】 Step 3: 【0521】 The server retrieves historical data from the database based on the analyzed user preferences. By executing database queries and retrieving a filtered dataset, it outputs the most suitable travel plan as a candidate. This candidate is selected from the dataset using an optimization algorithm. 【0522】 Step 4: 【0523】 The server uses an external API to retrieve real-time event information for the travel destination. The retrieved event information is added to the plan candidates and built into a proposed travel plan. In this process, the server processes real-time data and dynamically updates the travel plan. 【0524】 Step 5: 【0525】 The generated travel plan is sent to the device and presented to the user. The user views the plan on the device and provides feedback as needed. This feedback is recorded as data sent to the server via an intuitive interface. 【0526】 Step 6: 【0527】 The server analyzes user feedback and evaluates the travel plan. If necessary, it modifies the plan and generates a new, optimized travel plan. The final plan is then resent to the user's device based on their preferences and the latest information. 【0528】 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. 【0529】 The system according to the present invention receives the user's travel preferences, analyzes their emotions using an emotion engine, and generates an optimal travel plan based on this analysis. A specific embodiment of this system is described below. 【0530】 Users can freely input their travel preferences and expectations / desires using their device. This includes information such as destination, budget, travel duration, activities of interest, and emotions they wish to experience. It is designed to allow users to express their emotions and desires in a more flexible format. 【0531】 The terminal sends user input data to the server. The server uses natural language processing technology to analyze the user's requests and desires based on this data, and identifies the emotions hidden in the user's input using an emotion engine. This analysis helps to understand the user's emotional state and builds a foundation for proposing a plan tailored to that state. 【0532】 Furthermore, the server retrieves data from past users with similar travel experiences based on the user's requests and emotional data. This allows it to learn past plans that are appropriate for the user's emotional state and derive patterns for making the best suggestions for the user. 【0533】 The server constructs a travel plan based on the collected data. This process selects the most suitable destination, accommodation, and sightseeing route based on the user's budget and interests, and enhances the sense of realism by including real-time event information. It also incorporates activities and itineraries that are appropriate to the user's emotional state into the suggestions. 【0534】 The terminal presents the completed travel plan to the user. The user reviews the plan and provides feedback. The server receives this feedback, re-evaluates the plan as needed, and makes adjustments based on the user's emotions. For example, if the user expresses a desire to relax, the server will suggest activities such as spa treatments or nature walks that are enhanced to reflect that desire. 【0535】 Thus, the system of the present invention can create a differentiated travel experience that is tailored to the individual emotions and needs of the user. 【0536】 The following describes the processing flow. 【0537】 Step 1: 【0538】 Users use their own devices to describe their travel preferences and expectations and feelings about the trip. The information entered includes desired destinations, budget, planned dates, activities of interest, and emotions they would like to experience. 【0539】 Step 2: 【0540】 The terminal formats the collected input data and sends it to the server. This data includes text about specific travel wishes and feelings. 【0541】 Step 3: 【0542】 The server analyzes the received data. First, it structures the data using natural language processing techniques to clarify the user's intentions and desires. At this stage, it uses an emotion engine to analyze the emotional state from the user's description. 【0543】 Step 4: 【0544】 Based on the user's analysis results, the server retrieves past travel data from the database for users with similar desires and emotional states. This is to allow users to refer to the successful experiences of other users with similar desires and emotions. 【0545】 Step 5: 【0546】 The server uses this information to generate travel plans. Considering budget and requirements, it selects appropriate destinations, accommodations, and activities, integrating real-time event information with an experience that matches the user's emotions. 【0547】 Step 6: 【0548】 The server sends the completed travel plan to the device. The plan includes a detailed itinerary, along with special recommended activities tailored to the user's mood. 【0549】 Step 7: 【0550】 The device displays the received travel plan to the user. The user can review the plan and provide feedback on its contents. 【0551】 Step 8: 【0552】 The server receives user feedback and modifies the plan as needed. Further adjustments are made based on user sentiment to provide a more ideal plan. 【0553】 This process allows the system to provide a travel experience tailored to the user's emotions and desires, and to present a personalized itinerary. 【0554】 (Example 2) 【0555】 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." 【0556】 Traditional travel planning systems have struggled to generate travel plans that fully reflect users' emotions and specific preferences. Furthermore, they lacked the ability to incorporate real-time event information and flexibly adjust plans based on user feedback, resulting in insufficient user satisfaction. 【0557】 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. 【0558】 In this invention, the server includes means for analyzing user input using language analysis technology to identify the user's intentions, means for generating a travel plan by learning past data with similar travel desires, and means for analyzing the user's emotional state and adjusting the travel plan based on those emotions. This makes it possible to generate a travel plan that more accurately reflects the user's emotions and desires. 【0559】 A "user" refers to a person who inputs their desired conditions and feelings into the travel planning system. 【0560】 "Language analysis technology" refers to techniques that use natural language processing to analyze user input and identify intentions and emotions. 【0561】 A "travel plan" refers to a travel suggestion that includes information such as destinations, accommodations, and activities, and is generated based on the user's wishes and feelings. 【0562】 "Real-time event information" refers to the latest event and activity information at a travel destination, and is data that is constantly updated to provide to users. 【0563】 "Emotional state" refers to the emotional situation or tendency analyzed based on user input. 【0564】 "Feedback" refers to the opinions and evaluations that users provide regarding the travel plans suggested by the system. 【0565】 "Budget constraints" refer to the range of money a user can afford when planning a trip. 【0566】 "Cost-effectiveness" refers to the economic efficiency that indicates how much a travel planning option contributes to the user's wishes and satisfaction. 【0567】 This invention is a system in which a user inputs their desired travel conditions and generates an optimal travel plan based on those conditions and emotions. This system mainly consists of a server, a terminal, and a generating AI model. 【0568】 Users input their travel destination, budget, travel duration, activities of interest, and desired emotions using their device. This input is done through a free-form text field, designed to allow users to freely express their feelings and desires. 【0569】 The terminal sends input data to the server via an HTTP POST request. The server analyzes this data using natural language processing (NLTK) techniques. The Python NLTK library is used in this process. An emotion engine is then used to identify the user's intent and emotional state from the analyzed data. A common natural language processing tool is used as the emotion engine. 【0570】 Next, the server accesses a database to retrieve past data from users with similar travel experiences. This database is assumed to be a typical relational database. Based on data from users who have traveled under similar conditions in the past, a generative AI model proposes the optimal travel plan. 【0571】 The generated travel plan includes destinations, accommodations, and sightseeing routes that take into account the user's budget and interests. Real-time event information is also provided, and activities that the user can enjoy at that moment are incorporated into the plan. External event information APIs are used to obtain this information. 【0572】 The terminal ultimately presents the travel plan received from the server to the user, displaying it in a visually easy-to-understand format. The user can provide feedback on the provided plan, and this feedback is sent back to the server. Based on the feedback, the server re-evaluates and adjusts the travel plan. 【0573】 For example, if a user enters the desire to "relax," the server will suggest a travel plan that includes hot springs and massage experiences, based on data from past users with similar desires. An example of a prompt might be, "I want to relax on my next trip. What kind of plan can you suggest?" In this way, a travel experience tailored to the user's individual feelings and desires can be provided. 【0574】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0575】 Step 1: 【0576】 The user enters their travel preferences using a device. The user uses text fields to enter information such as destination, budget, duration, activities of interest, and desired emotional experiences. This input data reflects the user's requests and feelings. 【0577】 Step 2: 【0578】 The terminal sends the data entered by the user to the server. An HTTP POST request is used for this transmission. The input data is packaged in JSON format and securely transferred to the server. 【0579】 Step 3: 【0580】 The server analyzes the received data using natural language processing techniques. The server uses the Python NLTK library to tokenize and semantically analyze the text. This analysis identifies the user's request and emotional state. The input is the user's raw text data, and the output is the analyzed intent and emotional labels. 【0581】 Step 4: 【0582】 The server retrieves past data from the database based on the analysis results, specifically data from users with similar travel experiences. The server sends queries to the relational database to search for past user data. The input is the analysis results, and the output is a set of similar past data. 【0583】 Step 5: 【0584】 The server generates a travel plan based on calculated emotional states and user requests. The generative AI model uses historical training data to select the optimal destination, accommodations, and sightseeing routes. Inputs are similar historical data, current requests, and emotional information, while the output is the completed travel plan. 【0585】 Step 6: 【0586】 The server retrieves real-time event information from an external API and integrates it into the travel plan. This adds information about events and activities taking place locally to the user's plan. The input is the travel plan, and the output is the plan with the event information added. 【0587】 Step 7: 【0588】 The device presents the user with a completed travel plan. The plan is formatted visually on the device, making it easy for the user to understand. 【0589】 Step 8: 【0590】 The user enters feedback on the presented plan from their device. This feedback includes satisfaction with the plan and any additional requests. The feedback is then sent back to the server. 【0591】 Step 9: 【0592】 The server analyzes user feedback and re-evaluates and adjusts the travel plan as needed. The server then uses natural language processing to analyze the feedback again and make sentiment-based corrections. The input is user feedback, and the output is the improved new travel plan. 【0593】 (Application Example 2) 【0594】 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." 【0595】 Traditional travel plan suggestion systems primarily offered suggestions based on user preferences and budgets, making it difficult to provide travel plans that addressed users' emotions and individual expectations for experiences. This resulted in a lack of suggestions that offered unique experiences or surprises, failing to improve overall travel satisfaction. Furthermore, while there was a demand for special dining experiences and emotionally driven suggestions at destinations, providing such services appropriately proved to be a challenging task. 【0596】 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. 【0597】 In this invention, the server includes means for inputting the user's desired travel conditions; means for analyzing the user's input using natural language processing technology to identify the user's emotions; means for learning past data of similar travel experiences to generate the most suitable travel plan for the user; and means for customizing the suggestions based on the emotion analysis. This makes it possible to provide a personalized travel experience that responds to the user's emotions and expectations, and to improve satisfaction with the travel experience, in particular, by introducing special experiences such as meals and events. 【0598】 "Means for inputting user travel preferences" refers to an interface through a terminal for travelers to input their travel requirements and expectations, including destination, mode of transportation, budget, and preferences for special dining experiences. 【0599】 "Means for analyzing user input using natural language processing technology and identifying user emotions" refers to a technology that analyzes text entered by a user using a language processing algorithm and accurately grasps the emotions and intentions contained therein. 【0600】 "A method for generating the most suitable travel plan for a user by learning from past data of users with similar travel experiences" refers to an algorithm that utilizes data from users who have taken similar trips in the past to suggest travel and activities that best match the current user. 【0601】 "Means of presenting the generated travel plan to the user" refers to a user interface that clearly displays the generated travel plan to the user and presents it in a selectable format. 【0602】 "Means of providing real-time activity information for destinations included in travel plans" refers to an information provision system that enriches the travel experience by providing users with the latest event and activity information for their destinations in real time. 【0603】 "Methods for customizing suggestions based on sentiment analysis" refers to technologies that personalize travel plans and activities based on the user's emotional state, providing suggestions that are best suited to the user. 【0604】 This invention is a system that generates an optimal travel plan based on the user's desired travel experience, thereby improving the travel experience. The user inputs their desired travel conditions using a terminal such as a smart device. These conditions include travel destination, mode of transportation, budget, and preferences for special dining experiences. 【0605】 The terminal sends the entered data to the server. The server analyzes the entered preferences using natural language processing techniques to identify the user's emotions. An emotion engine can be used for this emotion analysis. Based on the identified emotions, the server learns from past data of similar travel experiences and generates the most suitable travel plan for the user. This process involves text analysis libraries and custom AI models. 【0606】 The generated travel plan is presented to the user via the device. This plan incorporates real-time activity information at the destination and is a customized suggestion that takes into account the user's emotions and expectations. For example, if the user expresses the emotion of "wanting to experience a surprise," the suggestion, based on emotion analysis, might be to participate in a special local culinary event. 【0607】 An example of a prompt message would be: "Based on the user's input, 'I want to enjoy delicious food and experience new surprises,' please perform sentiment analysis and recommend a dining experience that suits that sentiment." This system allows travelers to have a more engaging and emotionally resonant travel experience. 【0608】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0609】 Step 1: 【0610】 The user enters their desired conditions. This input data includes destination, mode of transportation, budget, and the emotions they wish to experience. The terminal retrieves this information through the user interface and sends it to the server. The input includes text and numerical data, and the output generates a request message that is sent to the server. 【0611】 Step 2: 【0612】 The server analyzes the input data received from the user using natural language processing techniques. This involves using a text analysis library to extract meaning based on the user's requests and preferences. The input is the user's text data, and the output is the analyzed data structure. 【0613】 Step 3: 【0614】 The server uses a generative AI model based on the analyzed data to identify the user's emotions. This process utilizes an emotion engine, which performs data calculations to identify the emotional state from the user's input. The input is the analyzed data, and the output is information indicating the user's emotional state. 【0615】 Step 4: 【0616】 The server learns from past data of similar travel experiences by comparing acquired emotional information with historical databases. Data mining techniques are used to generate a travel plan that best matches the identified emotional state. The input is emotional information and historical data, and the output is a customized travel plan. 【0617】 Step 5: 【0618】 The generated travel plan is supplemented with real-time activity information. This completes the plan, which includes personalized suggestions based on the user's emotions. Activity information is retrieved via an external API and integrated into the plan. The input is the travel plan and activity information, and the output is the final plan including real-time information. 【0619】 Step 6: 【0620】 The server transfers the final travel plan to the user's terminal. The user can review the presented plan and make selections or modifications. The terminal displays the data received from the server in its user interface. The input is the final plan data, and the output is the plan visualized for the user. 【0621】 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. 【0622】 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. 【0623】 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. 【0624】 [Fourth Embodiment] 【0625】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0626】 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. 【0627】 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). 【0628】 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. 【0629】 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. 【0630】 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). 【0631】 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. 【0632】 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. 【0633】 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. 【0634】 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. 【0635】 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. 【0636】 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. 【0637】 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". 【0638】 The system according to the present invention receives the user's travel preferences and generates an optimal travel plan based on them. A specific embodiment of this system is described below. 【0639】 Users use their devices to fill out a form detailing their travel preferences. This includes destination, budget, travel duration, type of accommodation, and activities of interest. 【0640】 The terminal sends the entered conditions to the server. The server uses natural language processing technology to analyze the user's intent based on the received data. Using the results of the analysis, the server retrieves past user data with similar travel preferences from the database in order to generate candidate travel plans that closely match the user's wishes. 【0641】 Based on the acquired data, the server selects destinations, accommodations, and activities that fit the budget and requirements, and creates a plan that best suits the user's wishes. In this process, the server also takes real-time event information into consideration, and therefore refers to the latest event information taking place around the travel destination. 【0642】 The terminal displays the travel plan received from the server to the user. The user reviews this plan, provides feedback, or confirms the plan. If feedback is received, the server re-evaluates the plan based on it and makes necessary adjustments to provide a more satisfying plan. 【0643】 As a concrete example, suppose a user enters the following conditions: "I want to travel to Kyoto with a budget of 150,000 yen. I want to prioritize cultural experiences." The terminal sends this information to the server, which then analyzes it. The server searches past data for plans that include cultural experiences in Kyoto and generates a proposed plan incorporating activities such as "Kyoto tea ceremony experience, temple tours, and kimono rental." By also adding information about festivals held during the travel period to the proposal, the server can provide the user with the most suitable travel experience. 【0644】 In this way, the system of the present invention efficiently generates travel plans based on the user's wishes and conditions, and provides personalized services. 【0645】 The following describes the processing flow. 【0646】 Step 1: 【0647】 Users enter their travel preferences using their own devices. This input includes details such as destination, budget, duration, and areas of interest such as activities and tourist attractions. 【0648】 Step 2: 【0649】 The terminal sends the user's entered conditions to the server as a data packet. This packet contains user information and travel conditions. 【0650】 Step 3: 【0651】 The server analyzes the data received from the terminal. Using natural language processing technology, it analyzes the input content and identifies the user's intentions and desires. 【0652】 Step 4: 【0653】 Based on the analyzed information, the server retrieves past user data from a database showing similar travel experiences and preferences. This gathers reference information to create the most suitable plan for the user. 【0654】 Step 5: 【0655】 The server creates a travel plan based on the acquired data. Based on budget, desired conditions, and past successful plans, it selects the optimal destination, accommodation, and sightseeing route. 【0656】 Step 6: 【0657】 The server collects real-time event information taking place at the travel destination during the trip and adds it to the plan. This provides users with the latest event information. 【0658】 Step 7: 【0659】 The server sends the final travel plan to the device. This plan includes selected travel elements and event information. 【0660】 Step 8: 【0661】 The device displays a travel plan to the user. The user reviews the plan and accepts it if satisfied, or provides feedback if any modifications are needed. 【0662】 Step 9: 【0663】 Based on user feedback, the server re-evaluates the plan, makes corrections as needed, and resubmits the final plan. 【0664】 (Example 1) 【0665】 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". 【0666】 Current travel plan generation systems struggle to flexibly respond to diverse user needs, particularly in providing plans that adequately consider budget constraints and real-time event information. As a result, users' travel experiences sometimes end up falling short of expectations. Furthermore, the adaptive adjustment of plans based on feedback is insufficient, limiting the ability to provide plans that truly satisfy users. 【0667】 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. 【0668】 In this invention, the server includes means for analyzing user input using natural language processing technology, means for generating a travel plan by learning from past data of users with similar travel preferences, and means for optimizing the travel plan based on budget constraints. This makes it possible to generate a more satisfying travel plan that corresponds to the user's individual conditions and intentions. 【0669】 A "user" refers to an individual or group that intends to use the system to plan a trip. 【0670】 "Desired conditions" refer to the requirements that users specify when planning a trip, such as destination, budget, duration of travel, type of accommodation, and activities of interest. 【0671】 "Natural language processing technology" refers to the technology used by computers to understand and interpret human language. 【0672】 A "travel plan" refers to a detailed plan for a trip desired by the user, including specific destinations, accommodations, and information on activities and events. 【0673】 "Real-time event information" refers to the latest information on specific events and activities taking place at your travel destination during your visit period. 【0674】 A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to generate output for a specific task. 【0675】 A "prompt" refers to the input text used to give instructions or conditions to a generative AI model. 【0676】 "Feedback" refers to opinions and impressions of travel plans provided by users, and may include requests for system improvements. 【0677】 "Budget constraints" refer to the financial limitations or restrictions that users must consider when planning a trip. 【0678】 "Adaptive adjustment" refers to improving or modifying existing travel plans based on user feedback and external information. 【0679】 The system of this invention utilizes natural language processing technology and generative AI models to generate personalized travel plans based on user preferences. This system mainly consists of terminals and servers, each playing a specific role. 【0680】 When planning a trip, users use a device to input their desired conditions, such as destination, budget, travel duration, type of accommodation, and activities of interest. This data is automatically transmitted to the server by the device. The device can be any common information processing device that can connect to the internet, such as a personal computer or smartphone. 【0681】 Upon receiving these preferences, the server analyzes the user's intent using natural language processing techniques. This analysis employs generative AI models, including advanced language models such as GPT-4. The user's input is converted into a prompt, which is then fed into the AI ​​model for analysis. An example of a prompt might be: "Please plan a trip to Kyoto within the user's desired budget. The desired activity is a cultural experience." 【0682】 After analysis, the server accesses the database to retrieve past user data with similar travel preferences. Based on this data, the server generates a travel plan that best matches the user's budget constraints and preferences. It also retrieves real-time event information for the travel destination from an external API and incorporates it into the plan. This ensures that information about events and activities taking place during the trip is also included in the plan. 【0683】 For example, if a user enters conditions such as "I want to travel to Kyoto with a budget of 150,000 yen, and I want to prioritize cultural experiences," the server searches past data for plans related to cultural experiences in Kyoto and generates a travel plan that includes activities such as tea ceremony experiences, temple tours, and kimono rentals. This plan is presented to the user via their terminal and can be adjusted based on their feedback. In this way, the system can provide a customized travel plan that meets the user's expectations. 【0684】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0685】 Step 1: 【0686】 Users enter their travel preferences into a dedicated form on their device. This includes destination, budget, travel duration, type of accommodation, and activities of interest. When the user presses the "Submit" button, this information is sent from the device to the server. The input data is typically organized in text format and transferred to the server over the network. 【0687】 Step 2: 【0688】 The terminal sends the received user conditions to the server. Here, the data is securely transferred using the HTTPS protocol. On the server, the input data is assigned a series of transaction IDs, and a mechanism is in place to track data processing using these IDs. 【0689】 Step 3: 【0690】 The server analyzes the received user conditions using natural language processing techniques. This analysis employs a generative AI model, specifically a model like GPT-4, to tokenize the input sentence and identify key keywords and intents. The input is text data, and the output is a structured list of intents and conditions. 【0691】 Step 4: 【0692】 The server executes database queries based on the analysis results to retrieve similar past travel preference data. Using SQL queries, it searches for records that most closely match the user's budget, destination, and interests. The retrieved data forms the basis for generating travel plans that closely match the user's requests. 【0693】 Step 5: 【0694】 The server uses retrieved historical data and real-time event information to construct a travel plan that matches the user's intentions. In doing so, it utilizes external APIs to obtain the latest event information for the travel destination and integrates it into the plan. The output is a travel plan based on the user's preferences, including itinerary, recommended activities, and accommodation information. 【0695】 Step 6: 【0696】 The terminal receives the travel plan generated from the server and builds an interface to display it to the user. A graphical user interface (GUI) is used to visually display the details of the travel plan. The user can review the plan, provide feedback, or confirm the plan immediately. 【0697】 Step 7: 【0698】 When user feedback is received, the server receives that information and re-evaluates the travel plan and makes necessary modifications. The input is user feedback, and the output is the adjusted or finalized travel plan. Based on the feedback, the server re-utilizes the generating AI model to adaptively adjust the plan. 【0699】 (Application Example 1) 【0700】 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". 【0701】 When planning a trip, visitors often face challenges in efficiently enjoying sightseeing due to time constraints and inability to fully utilize information about their destinations. Furthermore, there is a need for a system that can suggest optimal sightseeing routes tailored to individual user interests in real time. 【0702】 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. 【0703】 In this invention, the server includes means for inputting the user's travel preferences, means for analyzing the user's input using natural language processing technology to identify the user's intentions, and means for learning past data with similar travel preferences to generate the most suitable travel plan for the user. This makes it possible to provide the optimal sightseeing route within a limited time based on the user's preferences and to create an efficient sightseeing plan that combines this with real-time event information. 【0704】 "User travel preferences" refers to detailed information about the user's desired destination, budget, duration, and activities of interest in their travel plans. 【0705】 "Natural language processing technology" refers to the technology used by computers to understand, generate, and analyze human language. 【0706】 "Learning from past data" refers to the process of analyzing data collected so far from similar travel preferences to generate more effective plans. 【0707】 A "travel plan" refers to a suggestion that combines places to visit, activities to participate in, and accommodations during a specific travel period, based on the user's preferences. 【0708】 "Real-time event information" refers to the latest information on events and activities at a specified travel destination, which can be dynamically incorporated into travel plans. 【0709】 "Tourism resources" refer to facilities, events, and experiences that possess historical, cultural, and natural value within a tourist destination. 【0710】 A "viewing route" refers to a plan that shows the order and route of tourist spots to visit based on conditions set by the user. 【0711】 The system implementing this invention begins with the user inputting their travel preferences via a mobile device. The user's device then transmits these preferences to a server. The server analyzes the user's input using natural language processing technology to identify the user's intent. Libraries such as NLTK can be used for natural language processing. 【0712】 Based on the analysis results, the server retrieves similar travel preference data from past databases and learns from the data. This generates the most suitable travel plan for the user. Furthermore, it incorporates real-time event information from the travel destination and suggests sightseeing routes that utilize local tourist resources. This information is obtained from smart city management systems in tourist areas. 【0713】 The generated travel plan is presented to the user's device, and after reviewing the plan, the user can provide feedback or confirm it. Upon receiving user feedback, the server re-evaluates the plan and makes revisions as needed. This dynamic feedback loop allows users to obtain more satisfying travel plans. 【0714】 For example, if a user enters the condition "I want to visit art galleries in Tokyo on a weekend in June," the server will refer to information on relevant art exhibitions and events and generate an optimal plan, including travel routes. 【0715】 Examples of prompt messages are as follows: 【0716】 "What's the best route for visiting art galleries in Tokyo? My budget is 20,000 yen, it's a weekend, and I'm going with a friend." 【0717】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0718】 Step 1: 【0719】 Users enter their travel preferences on their mobile devices. This information includes destination, budget, travel duration, and activities of interest. This information is then transmitted from the mobile device to the server. 【0720】 Step 2: 【0721】 The server analyzes the user's requested conditions using natural language processing techniques. The input data is in text format, and the server uses a library like NLTK to identify the user's intent. In this process, key keywords and phrases are extracted from the input information and output as structured data. 【0722】 Step 3: 【0723】 The server retrieves historical data from the database based on the analyzed user preferences. By executing database queries and retrieving a filtered dataset, it outputs the most suitable travel plan as a candidate. This candidate is selected from the dataset using an optimization algorithm. 【0724】 Step 4: 【0725】 The server uses an external API to retrieve real-time event information for the travel destination. The retrieved event information is added to the plan candidates and built into a proposed travel plan. In this process, the server processes real-time data and dynamically updates the travel plan. 【0726】 Step 5: 【0727】 The generated travel plan is sent to the device and presented to the user. The user views the plan on the device and provides feedback as needed. This feedback is recorded as data sent to the server via an intuitive interface. 【0728】 Step 6: 【0729】 The server analyzes user feedback and evaluates the travel plan. If necessary, it modifies the plan and generates a new, optimized travel plan. The final plan is then resent to the user's device based on their preferences and the latest information. 【0730】 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. 【0731】 The system according to the present invention receives the user's travel preferences, analyzes their emotions using an emotion engine, and generates an optimal travel plan based on this analysis. A specific embodiment of this system is described below. 【0732】 Users can freely input their travel preferences and expectations / desires using their device. This includes information such as destination, budget, travel duration, activities of interest, and emotions they wish to experience. It is designed to allow users to express their emotions and desires in a more flexible format. 【0733】 The terminal sends user input data to the server. The server uses natural language processing technology to analyze the user's requests and desires based on this data, and identifies the emotions hidden in the user's input using an emotion engine. This analysis helps to understand the user's emotional state and builds a foundation for proposing a plan tailored to that state. 【0734】 Furthermore, the server retrieves data from past users with similar travel experiences based on the user's requests and emotional data. This allows it to learn past plans that are appropriate for the user's emotional state and derive patterns for making the best suggestions for the user. 【0735】 The server constructs a travel plan based on the collected data. This process selects the most suitable destination, accommodation, and sightseeing route based on the user's budget and interests, and enhances the sense of realism by including real-time event information. It also incorporates activities and itineraries that are appropriate to the user's emotional state into the suggestions. 【0736】 The terminal presents the completed travel plan to the user. The user reviews the plan and provides feedback. The server receives this feedback, re-evaluates the plan as needed, and makes adjustments based on the user's emotions. For example, if the user expresses a desire to relax, the server will suggest activities such as spa treatments or nature walks that are enhanced to reflect that desire. 【0737】 Thus, the system of the present invention can create a differentiated travel experience that is tailored to the individual emotions and needs of the user. 【0738】 The following describes the processing flow. 【0739】 Step 1: 【0740】 Users use their own devices to describe their travel preferences and expectations and feelings about the trip. The information entered includes desired destinations, budget, planned dates, activities of interest, and emotions they would like to experience. 【0741】 Step 2: 【0742】 The terminal formats the collected input data and sends it to the server. This data includes text about specific travel wishes and feelings. 【0743】 Step 3: 【0744】 The server analyzes the received data. First, it structures the data using natural language processing techniques to clarify the user's intentions and desires. At this stage, it uses an emotion engine to analyze the emotional state from the user's description. 【0745】 Step 4: 【0746】 Based on the user's analysis results, the server retrieves past travel data from the database for users with similar desires and emotional states. This is to allow users to refer to the successful experiences of other users with similar desires and emotions. 【0747】 Step 5: 【0748】 The server uses this information to generate travel plans. Considering budget and requirements, it selects appropriate destinations, accommodations, and activities, integrating real-time event information with an experience that matches the user's emotions. 【0749】 Step 6: 【0750】 The server sends the completed travel plan to the device. The plan includes a detailed itinerary, along with special recommended activities tailored to the user's mood. 【0751】 Step 7: 【0752】 The device displays the received travel plan to the user. The user can review the plan and provide feedback on its contents. 【0753】 Step 8: 【0754】 The server receives user feedback and modifies the plan as needed. Further adjustments are made based on user sentiment to provide a more ideal plan. 【0755】 This process allows the system to provide a travel experience tailored to the user's emotions and desires, and to present a personalized itinerary. 【0756】 (Example 2) 【0757】 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". 【0758】 Traditional travel planning systems have struggled to generate travel plans that fully reflect users' emotions and specific preferences. Furthermore, they lacked the ability to incorporate real-time event information and flexibly adjust plans based on user feedback, resulting in insufficient user satisfaction. 【0759】 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. 【0760】 In this invention, the server includes means for analyzing user input using language analysis technology to identify the user's intentions, means for generating a travel plan by learning past data with similar travel desires, and means for analyzing the user's emotional state and adjusting the travel plan based on those emotions. This makes it possible to generate a travel plan that more accurately reflects the user's emotions and desires. 【0761】 A "user" refers to a person who inputs their desired conditions and feelings into the travel planning system. 【0762】 "Language analysis technology" refers to techniques that use natural language processing to analyze user input and identify intentions and emotions. 【0763】 A "travel plan" refers to a travel suggestion that includes information such as destinations, accommodations, and activities, and is generated based on the user's wishes and feelings. 【0764】 "Real-time event information" refers to the latest event and activity information at a travel destination, and is data that is constantly updated to provide to users. 【0765】 "Emotional state" refers to the emotional situation or tendency analyzed based on user input. 【0766】 "Feedback" refers to the opinions and evaluations that users provide regarding the travel plans suggested by the system. 【0767】 "Budget constraints" refer to the range of money a user can afford when planning a trip. 【0768】 "Cost-effectiveness" refers to the economic efficiency that indicates how much a travel planning option contributes to the user's wishes and satisfaction. 【0769】 This invention is a system in which a user inputs their desired travel conditions and generates an optimal travel plan based on those conditions and emotions. This system mainly consists of a server, a terminal, and a generating AI model. 【0770】 Users input their travel destination, budget, travel duration, activities of interest, and desired emotions using their device. This input is done through a free-form text field, designed to allow users to freely express their feelings and desires. 【0771】 The terminal sends input data to the server via an HTTP POST request. The server analyzes this data using natural language processing (NLTK) techniques. The Python NLTK library is used in this process. An emotion engine is then used to identify the user's intent and emotional state from the analyzed data. A common natural language processing tool is used as the emotion engine. 【0772】 Next, the server accesses a database to retrieve past data from users with similar travel experiences. This database is assumed to be a typical relational database. Based on data from users who have traveled under similar conditions in the past, a generative AI model proposes the optimal travel plan. 【0773】 The generated travel plan includes destinations, accommodations, and sightseeing routes that take into account the user's budget and interests. Real-time event information is also provided, and activities that the user can enjoy at that moment are incorporated into the plan. External event information APIs are used to obtain this information. 【0774】 The terminal ultimately presents the travel plan received from the server to the user, displaying it in a visually easy-to-understand format. The user can provide feedback on the provided plan, and this feedback is sent back to the server. Based on the feedback, the server re-evaluates and adjusts the travel plan. 【0775】 For example, if a user enters the desire to "relax," the server will suggest a travel plan that includes hot springs and massage experiences, based on data from past users with similar desires. An example of a prompt might be, "I want to relax on my next trip. What kind of plan can you suggest?" In this way, a travel experience tailored to the user's individual feelings and desires can be provided. 【0776】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0777】 Step 1: 【0778】 The user enters their travel preferences using a device. The user uses text fields to enter information such as destination, budget, duration, activities of interest, and desired emotional experiences. This input data reflects the user's requests and feelings. 【0779】 Step 2: 【0780】 The terminal sends the data entered by the user to the server. An HTTP POST request is used for this transmission. The input data is packaged in JSON format and securely transferred to the server. 【0781】 Step 3: 【0782】 The server analyzes the received data using natural language processing techniques. The server uses the Python NLTK library to tokenize and semantically analyze the text. This analysis identifies the user's request and emotional state. The input is the user's raw text data, and the output is the analyzed intent and emotional labels. 【0783】 Step 4: 【0784】 The server retrieves past data from the database based on the analysis results, specifically data from users with similar travel experiences. The server sends queries to the relational database to search for past user data. The input is the analysis results, and the output is a set of similar past data. 【0785】 Step 5: 【0786】 The server generates a travel plan based on calculated emotional states and user requests. The generative AI model uses historical training data to select the optimal destination, accommodations, and sightseeing routes. Inputs are similar historical data, current requests, and emotional information, while the output is the completed travel plan. 【0787】 Step 6: 【0788】 The server retrieves real-time event information from an external API and integrates it into the travel plan. This adds information about events and activities taking place locally to the user's plan. The input is the travel plan, and the output is the plan with the event information added. 【0789】 Step 7: 【0790】 The device presents the user with a completed travel plan. The plan is formatted visually on the device, making it easy for the user to understand. 【0791】 Step 8: 【0792】 The user enters feedback on the presented plan from their device. This feedback includes satisfaction with the plan and any additional requests. The feedback is then sent back to the server. 【0793】 Step 9: 【0794】 The server analyzes user feedback and re-evaluates and adjusts the travel plan as needed. The server then uses natural language processing to analyze the feedback again and make sentiment-based corrections. The input is user feedback, and the output is the improved new travel plan. 【0795】 (Application Example 2) 【0796】 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". 【0797】 Traditional travel plan suggestion systems primarily offered suggestions based on user preferences and budgets, making it difficult to provide travel plans that addressed users' emotions and individual expectations for experiences. This resulted in a lack of suggestions that offered unique experiences or surprises, failing to improve overall travel satisfaction. Furthermore, while there was a demand for special dining experiences and emotionally driven suggestions at destinations, providing such services appropriately proved to be a challenging task. 【0798】 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. 【0799】 In this invention, the server includes means for inputting the user's desired travel conditions; means for analyzing the user's input using natural language processing technology to identify the user's emotions; means for learning past data of similar travel experiences to generate the most suitable travel plan for the user; and means for customizing the suggestions based on the emotion analysis. This makes it possible to provide a personalized travel experience that responds to the user's emotions and expectations, and to improve satisfaction with the travel experience, in particular, by introducing special experiences such as meals and events. 【0800】 "Means for inputting user travel preferences" refers to an interface through a terminal for travelers to input their travel requirements and expectations, including destination, mode of transportation, budget, and preferences for special dining experiences. 【0801】 "Means for analyzing user input using natural language processing technology and identifying user emotions" refers to a technology that analyzes text entered by a user using a language processing algorithm and accurately grasps the emotions and intentions contained therein. 【0802】 "A method for generating the most suitable travel plan for a user by learning from past data of users with similar travel experiences" refers to an algorithm that utilizes data from users who have taken similar trips in the past to suggest travel and activities that best match the current user. 【0803】 "Means of presenting the generated travel plan to the user" refers to a user interface that clearly displays the generated travel plan to the user and presents it in a selectable format. 【0804】 "Means of providing real-time activity information for destinations included in travel plans" refers to an information provision system that enriches the travel experience by providing users with the latest event and activity information for their destinations in real time. 【0805】 "Methods for customizing suggestions based on sentiment analysis" refers to technologies that personalize travel plans and activities based on the user's emotional state, providing suggestions that are best suited to the user. 【0806】 This invention is a system that generates an optimal travel plan based on the user's desired travel experience, thereby improving the travel experience. The user inputs their desired travel conditions using a terminal such as a smart device. These conditions include travel destination, mode of transportation, budget, and preferences for special dining experiences. 【0807】 The terminal sends the entered data to the server. The server analyzes the entered preferences using natural language processing techniques to identify the user's emotions. An emotion engine can be used for this emotion analysis. Based on the identified emotions, the server learns from past data of similar travel experiences and generates the most suitable travel plan for the user. This process involves text analysis libraries and custom AI models. 【0808】 The generated travel plan is presented to the user via the device. This plan incorporates real-time activity information at the destination and is a customized suggestion that takes into account the user's emotions and expectations. For example, if the user expresses the emotion of "wanting to experience a surprise," the suggestion, based on emotion analysis, might be to participate in a special local culinary event. 【0809】 An example of a prompt message would be: "Based on the user's input, 'I want to enjoy delicious food and experience new surprises,' please perform sentiment analysis and recommend a dining experience that suits that sentiment." This system allows travelers to have a more engaging and emotionally resonant travel experience. 【0810】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0811】 Step 1: 【0812】 The user enters their desired conditions. This input data includes destination, mode of transportation, budget, and the emotions they wish to experience. The terminal retrieves this information through the user interface and sends it to the server. The input includes text and numerical data, and the output generates a request message that is sent to the server. 【0813】 Step 2: 【0814】 The server analyzes the input data received from the user using natural language processing techniques. This involves using a text analysis library to extract meaning based on the user's requests and preferences. The input is the user's text data, and the output is the analyzed data structure. 【0815】 Step 3: 【0816】 The server uses a generative AI model based on the analyzed data to identify the user's emotions. This process utilizes an emotion engine, which performs data calculations to identify the emotional state from the user's input. The input is the analyzed data, and the output is information indicating the user's emotional state. 【0817】 Step 4: 【0818】 The server learns from past data of similar travel experiences by comparing acquired emotional information with historical databases. Data mining techniques are used to generate a travel plan that best matches the identified emotional state. The input is emotional information and historical data, and the output is a customized travel plan. 【0819】 Step 5: 【0820】 The generated travel plan is supplemented with real-time activity information. This completes the plan, which includes personalized suggestions based on the user's emotions. Activity information is retrieved via an external API and integrated into the plan. The input is the travel plan and activity information, and the output is the final plan including real-time information. 【0821】 Step 6: 【0822】 The server transfers the final travel plan to the user's terminal. The user can review the presented plan and make selections or modifications. The terminal displays the data received from the server in its user interface. The input is the final plan data, and the output is the plan visualized for the user. 【0823】 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. 【0824】 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. 【0825】 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. 【0826】 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. 【0827】 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. 【0828】 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. 【0829】 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. 【0830】 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. 【0831】 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." 【0832】 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. 【0833】 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. 【0834】 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. 【0835】 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. 【0836】 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. 【0837】 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. 【0838】 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. 【0839】 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. 【0840】 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. 【0841】 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. 【0842】 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. 【0843】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0844】 The following is further disclosed regarding the embodiments described above. 【0845】 (Claim 1) 【0846】 A means for users to input their travel preferences, 【0847】 A means for analyzing the user's input using natural language processing technology and identifying the user's intent, 【0848】 A method for generating the most suitable travel plan for a user by learning from past data of similar travel preferences, 【0849】 A means of presenting the generated travel plan to the user, 【0850】 A means of providing real-time event information for the travel destination included in the travel plan, 【0851】 A system that includes this. 【0852】 (Claim 2) 【0853】 The system according to claim 1, comprising means for obtaining user feedback and re-evaluating or modifying the travel plan. 【0854】 (Claim 3) 【0855】 The system according to claim 1, comprising means for optimizing travel plans and suggesting cost-effective options based on budget constraints. 【0856】 "Example 1" 【0857】 (Claim 1) 【0858】 A means for users to input their travel preferences, 【0859】 A means for analyzing the user's input using natural language processing technology and identifying the user's intent, 【0860】 A method for generating the most suitable travel plan for a user by learning from past data of similar travel preferences, 【0861】 A means of presenting the generated travel plan to the user, 【0862】 A means of providing real-time event information for the travel destination included in the travel plan, 【0863】 A means to optimize travel plans and provide efficient options based on the user's budget constraints, 【0864】 A method for proposing a travel plan using prompt sentences, utilizing a generated AI model based on user input, 【0865】 A system that includes this. 【0866】 (Claim 2) 【0867】 The system according to claim 1, comprising means for obtaining user feedback and re-evaluating or modifying the travel plan. 【0868】 (Claim 3) 【0869】 The system according to claim 1, comprising means for adaptively adjusting travel plans in accordance with user requests. 【0870】 "Application Example 1" 【0871】 (Claim 1) 【0872】 A means for users to input their travel preferences, 【0873】 A means for analyzing the user's input using natural language processing technology and identifying the user's intent, 【0874】 A method for generating the most suitable travel plan for a user by learning from past data of similar travel preferences, 【0875】 A means of presenting the generated travel plan to the user, 【0876】 A means of providing real-time event information for the travel destination included in the travel plan, 【0877】 A method to propose the optimal viewing route in real time within a limited time using the city's tourist resources, 【0878】 A system that includes this. 【0879】 (Claim 2) 【0880】 The system according to claim 1, comprising means for obtaining user feedback and re-evaluating or modifying the travel plan. 【0881】 (Claim 3) 【0882】 The system according to claim 1, comprising means for optimizing travel plans and suggesting cost-effective options based on budget constraints. 【0883】 "Example 2 of combining an emotion engine" 【0884】 (Claim 1) 【0885】 A device for inputting the user's travel preferences, 【0886】 A device that analyzes the user's input using language analysis technology and identifies the user's intent, 【0887】 A device that learns from past data of similar travel preferences to generate the most suitable travel plan for the user, 【0888】 A device that presents the generated travel plan to the user, 【0889】 A device that provides information on current events at the travel destination included in the travel plan, 【0890】 A device that analyzes the user's emotional state and adjusts travel plans based on those emotions, 【0891】 A system that includes this. 【0892】 (Claim 2) 【0893】 The system according to claim 1, further comprising a device for obtaining user feedback and re-evaluating or modifying the travel plan. 【0894】 (Claim 3) 【0895】 The system according to claim 1, comprising a device that optimizes travel planning and proposes cost-effective options based on budget constraints. 【0896】 "Application example 2 when combining with an emotional engine" 【0897】 (Claim 1) 【0898】 A means for users to input their desired conditions regarding travel, 【0899】 A means for analyzing the user's input using natural language processing technology and identifying the user's emotions, 【0900】 A method for generating the most suitable travel plan for a user by learning from past data of similar travel experiences, 【0901】 A means of presenting the generated travel plan to the user, 【0902】 A means of providing real-time activity information for destinations included in the travel plan, 【0903】 A means of customizing suggestions based on sentiment analysis, 【0904】 A system that includes this. 【0905】 (Claim 2) 【0906】 The system according to claim 1, further comprising means for obtaining user feedback and re-evaluating or modifying the travel plan. 【0907】 (Claim 3) 【0908】 The system according to claim 1, comprising means for optimizing travel plans and proposing cost-effective options based on cost constraints. [Explanation of Symbols] 【0909】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means for users to input their travel preferences, A means for analyzing the user's input using natural language processing technology and identifying the user's intent, A method for generating the most suitable travel plan for a user by learning from past data of similar travel preferences, A means of presenting the generated travel plan to the user, A means of providing real-time event information for the travel destination included in the travel plan, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for obtaining user feedback and re-evaluating or modifying the travel plan. [Claim 3] The system according to claim 1, comprising means for optimizing travel plans and proposing cost-effective options based on budget constraints.

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