system

Abstract

We provide the system. [Solution] A means for receiving requests from users regarding travel and activity plans in natural language, and for analyzing those requests to extract necessary information, A means for automatically generating travel and activity plans using artificial intelligence technology based on extracted information and externally relevant information, A means of presenting the generated plan to the user and allowing the plan to be modified based on user feedback, A means to make the generated plan shareable with other users via communication means, A system that includes payment methods for sharing the cost of a shared plan among other users.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, traveling and dining out have become precious experiences for many people, and accordingly the importance of planning has been increasing. However, when making a travel plan, it is necessary to individually consider a wide variety of factors such as accommodation, transportation, selection of dining places, calculation of budget, and consideration of the influence of weather. This process requires a lot of information collection and budget management, which is a burden for users. Therefore, there is a need for a system that can efficiently and easily make a travel plan and share it with relevant parties.

Means for Solving the Problems

[0005] This invention provides a system that analyzes travel requests from users in natural language and automatically generates travel plans using generative artificial intelligence. By extracting keywords based on user requests and combining them with external information, including weather information, the system can suggest appropriate accommodations, transportation, meals, and activities. It can also regenerate plans based on user feedback. The generated plans can be shared with other users via a communication network, and costs can be shared and paid for using electronic payment services. This allows users to efficiently and effectively share travel plans and execute them smoothly through flexible payment methods.

[0006] A "user" refers to an individual or group that uses the system to plan things like travel or meals.

[0007] A "travel plan" refers to a detailed schedule or plan that includes destinations, accommodations, transportation, budget, activities, and other aspects of a trip.

[0008] "Natural language" refers to the language that humans use for normal communication, and includes forms such as text and audio.

[0009] "Analysis" refers to the process of breaking down input data and information to derive meaning and relationships.

[0010] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate new information and plans based on given data and conditions.

[0011] A "plan" refers to a series of actions or steps structured to achieve a specific objective.

[0012] "Feedback" refers to the opinions and requests that users give regarding the proposed plan.

[0013] A "communication network" refers to the infrastructure used to send and receive information and data, and includes the internet and mobile communications.

[0014] "Electronic payment services" refer to services that use digital technology to make online payments.

[0015] "Cost sharing" refers to multiple individuals or groups sharing and bearing a specific cost. [Brief explanation of the drawing]

[0016] [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] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] 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.

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The present invention is implemented as a system for streamlining travel and related planning. This system includes various means necessary to process natural language requests from users, generate appropriate plans, and share them with other stakeholders.

[0038] First, the user accesses the chat interface using their device and enters their travel plan request. This request includes information such as the destination, desired dates, number of participants, and budget. This entered information is then sent to the server.

[0039] The server receives the user's request and applies natural language processing (NLP) to extract necessary keywords and important information from the input text. Then, based on the extracted information, it uses generative artificial intelligence (AI) technology to automatically generate a plan that covers key elements such as travel destination, accommodation, transportation, meals, and activities. During the generation process, it also refers to weather information and makes recommendations for clothing and activities to consider during the trip.

[0040] The generated plan is sent to the user's device. The user can review the proposal and request changes or the addition of specific conditions (such as budget constraints) if necessary. Upon receiving the additional request, the server regenerates the plan to reflect the user's new conditions.

[0041] The final approved plan can be shared via a communication network, for example, by sharing a link with other travel participants using a popular messenger service. This process allows all parties involved to easily review and discuss the same plan.

[0042] Furthermore, the server coordinates the payment process through electronic payment services, enabling cost sharing among participants. This allows for smooth payments between users.

[0043] For example, if a user wants to create a holiday plan, the system will present a plan that takes into account popular hotels, local restaurants, tourist attractions, and transportation options. The user can review the plan and make requests, such as "change the hotel to a slightly cheaper option." The system will immediately reflect this request and generate and present a new plan. In this way, the travel planning process is greatly simplified, reducing the effort required from the user.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users input their travel plans and requirements (destination, dates, budget, number of participants, etc.) in natural language through a chat interface on their device.

[0047] Step 2:

[0048] The terminal sends user input information to the server. Upon receiving the data, the server uses a natural language processing (NLP) module to extract important keywords and necessary data from the input text.

[0049] Step 3:

[0050] The server uses the extracted information to call an external API to collect weather data and obtain the weather forecast for the destination on the planned travel date.

[0051] Step 4:

[0052] The server activates a generation AI module to automatically generate a travel plan based on the user's request and acquired weather information. The plan includes suggestions for accommodation, transportation, dining options, and activities, as well as clothing and packing recommendations based on the weather.

[0053] Step 5:

[0054] The server sends the generated travel plan to the user. The user reviews the plan details on their device and requests specific conditions or changes as needed.

[0055] Step 6:

[0056] Upon receiving user feedback, the server regenerates the plan, taking the requested changes into account. The regenerated plan is immediately sent to the user for re-evaluation.

[0057] Step 7:

[0058] Once a user is satisfied with the final plan, they select the sharing option on their device, and the server generates a sharing link. The user then sends this link to the relevant parties via the communication network.

[0059] Step 8:

[0060] The server provides payment methods for cost sharing via an electronic payment service. Users make payments from their terminals, and the server checks each user's payment status and performs a final confirmation.

[0061] This process allows users to quickly and effectively create, share, and execute fully personalized travel plans.

[0062] (Example 1)

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

[0064] Planning a trip is a time-consuming and laborious process, requiring extensive information gathering and coordination. Travelers often find it difficult to quickly create an optimal travel plan while considering multiple factors such as destination, budget, and itinerary. Furthermore, there are numerous issues related to sharing travel plans, cost sharing, and payments, highlighting the need for efficient management systems.

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

[0066] This invention includes a server that receives requests from users regarding travel plans in natural language, analyzes those requests to extract necessary information, automatically generates a travel plan using generative artificial intelligence based on the extracted information and external information, and presents the generated travel plan to the user and can regenerate the plan based on user feedback. This enables users to quickly and efficiently create optimal travel plans and smoothly share them with other travel participants and share costs.

[0067] "Receiving information in natural language" refers to the process of inputting information using the language format that users use in their daily lives and converting it into a format that the computer system can understand.

[0068] "Analyzing requests" refers to the process of interpreting information received from users, extracting necessary information and keywords, and organizing them.

[0069] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate new information and plans based on given data and conditions.

[0070] "Automatic generation" refers to the process in which a system makes its own decisions based on user requests and conditions, and creates the necessary plans and information.

[0071] "Regenerative capabilities" refer to a function that allows you to regenerate a plan or information once it has been created if there are any modifications or changes in conditions, thereby providing a new plan or information.

[0072] A "communication network" is a digital data transmission infrastructure used to share information with other users and systems.

[0073] "Electronic payment" is a method of conducting monetary transactions using digital technology, and is a system that allows payments to be completed without using physical cash.

[0074] This invention is a system for efficiently planning travel. Users input travel requests through natural language prompts using a terminal. For example, a user might input, "I would like to travel to Tokyo next month. My budget is 100,000 yen per person, and I am thinking of a 3-night, 4-day trip." This request is immediately sent to the server.

[0075] The server uses natural language processing techniques to analyze user requests and extract keywords and information. A natural language processing framework (e.g., spaCy) is used for this analysis. The server also accesses external databases and APIs to collect external information such as destination weather, accommodation, and transportation options.

[0076] Next, the server utilizes a generative artificial intelligence model (e.g., OpenAI® GPT) to automatically generate a travel plan by combining the user's requests with external information. This generated plan includes accommodations, activities, meals, transportation, and more. The generated plan is designed to be optimized for the user.

[0077] Users can review the travel plan generated through their device and request changes as needed. For example, if a user requests to change the hotel to a cheaper option, the server will regenerate and present a new plan that meets the user's requirements. This regeneration process allows for flexible planning tailored to the user's preferences.

[0078] The final plan can be shared with other travel participants via a communication network. Furthermore, the server provides electronic payment functionality to facilitate efficient cost sharing and payments among participants. This entire process makes travel planning quick and consistent, significantly reducing the user's workload.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user accesses the chat interface using their device and enters prompts about their travel plans in natural language. For example, they might type, "I'd like to travel to Tokyo next month. My budget is 100,000 yen per person, and I'm thinking of a 3-night, 4-day trip." This input is sent to the server exactly as it was entered.

[0082] Step 2:

[0083] The server analyzes the prompt message received from the user using natural language processing technology. Here, the server uses "spaCy" to analyze the text and extract keywords such as destination, schedule, and budget. The keywords extracted from the input text data are then output as information used in the next processing step.

[0084] Step 3:

[0085] The server initiates access to external information sources based on keywords obtained from the analysis results. Specifically, it sends requests to weather information providers, accommodation databases, and transportation information APIs to obtain the latest information relevant to the user's travel plans. The input here is keyword data, and the output is the collected external information.

[0086] Step 4:

[0087] The server automatically generates travel plans using a generative AI model based on extracted keywords and collected external information. Using tools such as "OpenAI GPT," it creates a comprehensive plan including accommodation, activities, meals, and transportation based on the input data. As a result of the data processing performed by the generative AI, a travel plan optimized for the user is output.

[0088] Step 5:

[0089] The user reviews the travel plan displayed on the device and re-enters the information if changes are needed. For example, they might enter a request to "change the hotel to a slightly cheaper option." This re-entry is sent back to the server and used for further processing.

[0090] Step 6:

[0091] The server regenerates the travel plan based on user feedback. It incorporates the data used in the initial generation and the user's new requests to create a plan that better matches the user's needs. The AI ​​model is used again to output the updated travel plan.

[0092] Step 7:

[0093] The finalized plan is presented to the user via the terminal. The user can then share this final plan with other travel participants using the communication network and manage cost sharing through electronic payment functionality. The input is the finalized plan, and the output is a sharing link and payment information.

[0094] (Application Example 1)

[0095] 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."

[0096] There is a need to streamline people's travel and activity planning, automatically providing optimal plans that take environmental conditions and relevant information into account, thereby reducing user effort and improving the quality of travel and activities. However, traditional methods require the manual collection and integration of individual pieces of information, which is time-consuming and labor-intensive.

[0097] 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.

[0098] This invention includes a server that receives requests from users regarding travel and activity plans in natural language, analyzes those requests to extract necessary information, automatically generates travel and activity plans using artificial intelligence technology based on the extracted information and relevant external information, and makes the generated plans shareable with other users via communication means. This makes it possible to provide users with plans optimized for their needs and reduce the burden of information gathering and planning.

[0099] A "user" is an individual or group that intends to use the system to plan their travel and activities.

[0100] A "travel and activity plan" is a schedule of transportation methods and activities proposed based on the user's needs.

[0101] "Natural language" refers to the language that humans use on a daily basis, and is a means of inputting requests to a system in text format.

[0102] "Means for analyzing requests and extracting necessary information" refers to technologies that process information to identify meaningful keywords and information from input natural language.

[0103] "Means for automatically generating travel and activity plans using artificial intelligence technology" refers to AI technology that creates optimal plans by utilizing relevant patterns and data based on acquired information.

[0104] "External relevant information" refers to external data such as traffic conditions and weather that are referenced when generating a plan.

[0105] "Communication means" refers to the network infrastructure used to send generated plans to other users.

[0106] "Means for sharing plans" refers to features that allow users to share their travel and activity plans with others.

[0107] A "payment method" is a way to share costs and manage the exchange of money between users.

[0108] An "electronic transaction service" is a system designed to facilitate the smooth exchange and payment of money conducted online.

[0109] The system that realizes this invention begins with the user inputting their travel and activity plan in natural language using a communication terminal such as a smartphone or computer. The user's input is sent to a server via the terminal. The server uses Python and natural language processing libraries to analyze this input and extract the necessary information.

[0110] The server then automatically generates travel and activity plans using a generative artificial intelligence model. At this stage, traffic and weather data obtained from external sources are incorporated to improve the accuracy and practicality of the generated plans.

[0111] Specifically, using AI frameworks such as TENSORFLOW® and PyTorch, the system generates optimal travel and activity plans that match the user's conditions based on acquired keywords and external data.

[0112] The generated plan is sent from the server to the user's device for review. The user can provide feedback as needed, and this information is sent back to the server, regenerating a new plan with the specified adjustments.

[0113] Furthermore, the system incorporates communication capabilities, allowing users to share generated plans with other users through a similar process. Additionally, electronic transaction services can be used to share costs and process payments related to shared plans.

[0114] For example, if a user inputs, "I want to plan a trip to a museum and lunch in Tokyo next Saturday," the system analyzes this input and suggests a plan that takes into account available transportation options and museum opening hours. Users can provide feedback such as, "I'd like to stop by a cafe after the museum," and the plan will be adjusted accordingly. Furthermore, this plan can be shared with family and friends, and expenses can be easily shared.

[0115] An example of a prompt sentence would be, "I'd like to plan my activities in the city center next Saturday. I plan to visit an art museum and then have lunch."

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] Users enter requests regarding travel and activity plans in natural language using a smartphone or computer terminal. The requests entered by the user (for example, "Visit a museum in the city center next Saturday, then have lunch") are sent to the server as text data.

[0119] Step 2:

[0120] The server parses the received request using Python and natural language processing libraries (e.g., NLTK and spaCy). It extracts keywords (e.g., "Saturday," "art museum," "lunch") from the input text data and processes the data to identify the user's request. The output of this process is data that represents the user's request as structured information.

[0121] Step 3:

[0122] The server uses extracted keywords and related external information (such as traffic conditions and weather data) as input to automatically generate travel and activity plans using a generative AI model (e.g., using TensorFlow or PyTorch). Specifically, it considers the relationships between each element, evaluates the options, and creates the optimal plan (e.g., a schedule including transportation and order of visits). The output is plan information optimized for the user.

[0123] Step 4:

[0124] The server generates a plan and sends it to the user's device. The device displays the received plan to the user through the application, allowing the user to review the plan's contents. Visual representations and detailed information about the plan are also provided.

[0125] Step 5:

[0126] The user reviews the plan and provides feedback as needed. For example, they might submit a modification request such as, "I'd like to change the lunch time to 2 PM." This feedback is then sent back to the server.

[0127] Step 6:

[0128] Based on the feedback received by the server, the AI ​​model is used again to regenerate the plan. The input is the user's feedback data, and the output is the adjusted new plan.

[0129] Step 7:

[0130] The final plan is shared by the user with other users. The server uses communication methods to distribute the generated plan link or data to other relevant users. The choice of communication tools and platforms is also considered here.

[0131] Step 8:

[0132] Users share the costs associated with the plan and complete the payment process through an electronic transaction service. This process integrates with a third-party payment service for payment confirmation and cost aggregation. The output is confirmation that the costs were processed smoothly.

[0133] 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.

[0134] This invention is configured as a system for efficiently and emotionally supporting users' travel planning. This system includes multiple means for analyzing natural language requests received from users, recognizing the user's emotional state using an emotion engine, and reflecting these in the generation of travel plans.

[0135] First, the user enters their travel plans and preferences in natural language via a chat interface on their device. This information is sent to the server. The server utilizes a natural language processing module to extract important keywords and emotional cues from the entered text.

[0136] Next, the emotion engine kicks in and analyzes the user's emotional state based on these clues. This analysis is then provided to the generative AI module, which automatically generates a travel plan that resonates with the user's emotions. For example, if the user is seeking relaxation, the system will prioritize activities and environments themed around healing, while if they prefer activities that stimulate their sense of adventure, it will suggest an active itinerary.

[0137] The generated travel plan is first presented to the user on their device, and the user can provide feedback based on the plan's content. This feedback also utilizes an emotion engine, which analyzes the user's emotional response to regenerate an even more optimal plan.

[0138] Furthermore, the final plan can be shared with other users via the communication network. Users receive a link to share this plan with other participants, making it easily accessible.

[0139] Furthermore, the server assists with cost sharing through electronic payment services and provides a mechanism for smooth payments between users. In this way, it supports the entire process up to the execution of the travel plan.

[0140] For example, if a user wishes to plan a relaxing weekend trip, the system analyzes their initial preferences and suggests a hot spring resort stay in a nature-rich tourist area. If the system analyzes that the user is experiencing stress, it will then suggest a plan that includes a quieter environment and a meditation experience to enhance the user's mental satisfaction. In this way, travel planning that incorporates the user's emotions enriches individual experiences.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] Users enter their travel plans and specific requirements on the device's chat interface. This includes destination, dates, budget, and purpose of travel (e.g., relaxation, adventure).

[0144] Step 2:

[0145] The terminal sends user input information to the server. The server processes this information using natural language processing technology to extract important keywords and phrases from the text. This reveals the user's specific wishes and requests.

[0146] Step 3:

[0147] The server activates an emotion engine to analyze emotional cues contained in the user's input text. Based on word choices and context, it determines the user's emotional state (e.g., tension, excitement, calmness).

[0148] Step 4:

[0149] The server automatically generates travel plans using a generation AI module based on extracted keywords and emotional states. In this process, it incorporates weather information and destination tourist information to provide suggestions that resonate with the user's emotions.

[0150] Step 5:

[0151] The generated travel plan is sent from the server to the user's device. The user can review the plan and provide feedback on the details. For example, they can make specific requests such as "I want to add more activities" or "I want to reduce the cost."

[0152] Step 6:

[0153] The server receives feedback from the user, performs sentiment analysis again using the sentiment engine, and incorporates the desired plan changes. As a result, it generates an improved plan incorporating the new conditions and provides it to the user again.

[0154] Step 7:

[0155] The plan that the user has finally approved can be shared with other travel participants via the communication network by selecting the sharing option through their device. The server generates a sharing link and sends it to the user.

[0156] Step 8:

[0157] The server manages expenses using electronic payment services and facilitates smooth cost sharing among participants. Users make payments on their terminals, and the server manages and monitors the overall payment status.

[0158] This process allows users to create customized travel plans that take emotions into account, and then share and execute those plans with all participants.

[0159] (Example 2)

[0160] 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."

[0161] In travel planning, conventional systems often fail to adequately consider the emotional needs of users, resulting in difficulty in providing highly satisfying travel plans. In particular, the inability to offer specific suggestions based on travel purpose and mood makes generating travel plans tailored to individual experiences a challenge. Furthermore, features such as travel plan sharing and cost sharing are insufficient, making smooth plan sharing among users difficult.

[0162] 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.

[0163] In this invention, the server includes means for receiving travel plan requests from users in natural language and extracting important clues, means for analyzing the user's emotional state based on the extracted clues, and means for automatically generating a travel plan that is tailored to the user's emotions based on the emotion analysis results and external information. This makes it possible to generate more personalized travel plans that are tailored to the user's emotions and wishes. Furthermore, payment adjustment means for sharing plans and sharing costs enable smooth plan sharing and payment among users.

[0164] "Natural language" refers to the language that users use on a daily basis and is used for requests and information input in a system.

[0165] "Clues" are important pieces of information extracted from user input, and they form the basis for sentiment analysis and plan generation.

[0166] "Emotional analysis" is a process that determines a user's emotional state based on their input and actions, and estimates their psychological needs.

[0167] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates travel plans tailored to the user.

[0168] A "travel plan" is a specific proposal of travel itinerary and activities based on the user's requests and emotional state.

[0169] A "communication line" is a communication network that enables data exchange between users and serves as the foundation for information sharing.

[0170] "Payment adjustment" is a method of managing payment procedures using electronic payments to fairly distribute the costs of a travel plan among users.

[0171] The embodiments for carrying out the present invention are described below.

[0172] As an example of this system, the user first uses their device to input their travel plans and requirements in natural language. The entered information is sent from the user to the server. The server uses existing platforms such as Google® Cloud Natural Language API or IBM Watson® Natural Language Understanding as its natural language processing engine to extract important clues from the user's requests.

[0173] Next, the server performs sentiment analysis based on the clues. This analysis uses sentiment analysis functions such as Microsoft® Azure® Text Analytics to identify the user's psychological state. For example, it can determine whether the user is seeking relaxation or adventure.

[0174] Based on the analysis of the user's emotional state, the server uses a generative AI model to automatically create a travel plan that resonates with the user's feelings. One example of such an AI model is the OpenAI GPT model. The generated travel plan might include suggestions for resort destinations with abundant nature for a user seeking relaxation.

[0175] The generated plan is transferred to the device, where the user can review it and provide feedback. The server, upon receiving the feedback, performs another sentiment analysis and optimizes the plan as needed. Based on the feedback, elements such as "quiet environment" or "meditation experience" can be included.

[0176] Furthermore, the final travel plan can be easily shared with other users via a communication network. Users can use the provided link to share their plan with other devices and collaborate on planning.

[0177] Furthermore, the server coordinates payments for travel plans through its electronic payment functionality. Specifically, it can smoothly share costs among users using electronic payment platforms such as PayPal and Stripe.

[0178] As a concrete example, consider a scenario where a user enters "I want to go somewhere relaxing next weekend" as a prompt. The system then performs natural language analysis and, through sentiment analysis, suggests a relaxing travel plan. The user can then plan a more satisfying travel experience based on the suggested plan.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The user enters their travel plans and preferences in natural language on their device. This input data is sent to the server in text format. For example, the user might enter the prompt, "I'm looking for a relaxing beach resort."

[0182] Step 2:

[0183] The server analyzes the received natural language data using a natural language processing engine to extract important keywords and clues. Keywords such as "relax," "beach," and "resort" are extracted from the input text. The Google Cloud Natural Language API may be used at this stage.

[0184] Step 3:

[0185] Based on the extracted clues, the server uses an emotion analysis engine to analyze the user's emotional state. The data analysis determines that the user's emotional state is "wanting to relax." For example, Microsoft Azure Text Analytics might be used at this stage.

[0186] Step 4:

[0187] The server automatically generates personalized travel plans for users based on sentiment data and keywords through a generative AI model. Here, the generative AI model processes the information obtained in the previous stage to create itinerary suggestions, including a list of suitable beach resorts. OpenAI GPT models, among others, may be used in this process.

[0188] Step 5:

[0189] The generated travel plan is printed on the device and presented to the user. The user can review the plan and provide feedback as needed. For example, the user might comment, "I'd like to add a few more activities."

[0190] Step 6:

[0191] The server receives user feedback, performs sentiment analysis again, and regenerates a more suitable plan. It incorporates the feedback as data and optimizes the initial plan, such as adding new activities.

[0192] Step 7:

[0193] The final travel plan generates a link that can be shared with other users via a communication network. Users can then use this link to share their plans with friends and family. Specifically, the generated link can be sent via email or messaging apps.

[0194] Step 8:

[0195] The server utilizes an electronic payment platform to coordinate payments for travel plans and manage cost sharing among users. Specifically, it uses services like PayPal and Stripe to ensure that accommodation and transportation costs are fairly shared among participants.

[0196] (Application Example 2)

[0197] 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".

[0198] Traditional travel planning often struggled to reflect users' emotions and individual preferences, resulting in generic suggestions. Furthermore, the process of sharing travel plans and costs with others was complex and inconvenient. The lack of personalized travel plan suggestions hindered user satisfaction.

[0199] 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.

[0200] This invention includes a server that receives travel planning requests from users in natural language, analyzes those requests to extract necessary information, automatically generates a travel schedule using generative artificial intelligence based on the extracted information and external information, and presents the generated travel schedule to the user and can regenerate the schedule based on the user's evaluation. This enables the creation of flexible travel plans that are tailored to the user's emotions and individual preferences, as well as the efficient sharing of costs.

[0201] A "user" is an individual or group that uses the system to receive travel plan suggestions.

[0202] "Travel plan requests" refer to information that indicates the user's travel preferences and conditions that they want the system to meet.

[0203] "Natural language" refers to the language that humans use on a daily basis, expressed through text or speech.

[0204] "Means of extracting information" refers to methods for extracting specific keywords and important elements from user requests.

[0205] "External information" refers to data other than what the user requested that is used to suggest travel plans, and includes, for example, information about weather and traffic conditions.

[0206] "Generative artificial intelligence" is an artificial intelligence technology that generates appropriate travel schedules based on user requests and external information.

[0207] "Methods for automatically generating travel schedules" refers to methods that use artificial intelligence to create travel plans tailored to the user's preferences.

[0208] "Means of presenting to the user" refers to methods of providing the generated travel plan in a way that allows the user to visually confirm it.

[0209] "User ratings" refer to users' opinions and feedback on the presented travel plans.

[0210] "Methods for regenerating schedules" refer to methods for redesigning travel plans based on user feedback.

[0211] A "communication data network" is a network system used to share information with other users.

[0212] "Users" refers to other individuals or groups who view or share the generated travel schedule.

[0213] A "payment method for sharing expenses" refers to a method for efficiently sharing and paying for travel-related expenses among users.

[0214] The system for implementing this invention begins with a user inputting a travel plan request in natural language via a smartphone. This information is sent to a cloud-based server, where the request is analyzed using a natural language processing module. During the analysis, the server uses natural language processing software, such as Google Bard or OpenAI's GPT model, to extract keywords and sentiment cues from the information obtained from the user.

[0215] Next, the emotion recognition engine analyzes the user's emotional state and provides the results to the generative artificial intelligence module. This module utilizes a generative AI model to generate a personalized travel schedule based on the user's emotions and expectations. The generated schedule is presented to the user on their device, allowing them to intuitively review its contents.

[0216] When a user provides feedback on the schedule, the server re-analyzes the feedback and regenerates the schedule to optimize it. The regenerated schedule is then presented to the user via their smartphone.

[0217] Furthermore, the terminal has the function to share the generated schedule with other users via the communication data network. Regarding the shared schedule, electronic payment technology is used to facilitate the smooth sharing of costs among users.

[0218] For example, if a user inputs "I want to visit a place where I can refresh myself in a quiet natural setting on the weekend," the system can grasp the user's desire for refreshment and suggest a travel schedule that includes visits to quiet parks and hot spring facilities. An example of a prompt to the generative AI model used in this case would be, "Please tell me how to spend a weekend refreshing myself in a quiet natural setting."

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] The user uses a terminal to input travel plan requests in natural language. The input is sent to the server as text data. During this process, the terminal uses a text editor or voice input function to collect specific details about the user's preferences.

[0222] Step 2:

[0223] The server passes the received text data to a natural language processing module. Here, the server extracts important keywords and sentiment cues from the text, for example, using an OpenAI GPT model. The input is natural language text, and the output is keyword and sentiment information. This information is later provided to the sentiment engine.

[0224] Step 3:

[0225] The server uses an emotion engine to analyze the emotion information obtained in step 2. Here, the user's emotional state is evaluated in detail, and necessary data processing is performed. The input is emotion information, and the output is data about the specific emotional state. This data is provided to the generative artificial intelligence module.

[0226] Step 4:

[0227] The server uses a generative artificial intelligence module to generate a travel schedule based on the user's emotional state and requests. It utilizes a generative AI model to perform data calculations, including prompts. The input is the emotional and request data analyzed in step 3, and the output is a travel schedule plan.

[0228] Step 5:

[0229] The generated travel schedule is sent to the terminal and presented to the user. The terminal uses a GUI (Graphical User Interface) to visually display the schedule. The input is the generated travel schedule data, and the output is a user-friendly schedule display.

[0230] Step 6:

[0231] The user provides feedback on the presented schedule. This information is then sent back to the server via the device. The feedback is analyzed for sentiment and converted into data that represents specific improvement requests.

[0232] Step 7:

[0233] The server repeats the process in step 4 to regenerate the travel schedule based on user feedback. During this process, the feedback is re-evaluated by the generating AI model, and an optimized plan is created. The input is the feedback data, and the output is the regenerated travel schedule.

[0234] Step 8:

[0235] The final travel schedule is provided to the device in a format that can be shared with other users via a communication data network. The device uses a sharing link generation function to easily share this information with other users. The input is the final schedule data, and the output is a shareable link.

[0236] Step 9:

[0237] The server uses electronic payment functionality to streamline the sharing of travel expenses. Expense payments between users are automatically coordinated using electronic payment technology. Inputs are user information and expense data, and output is the transaction result with expenses already shared.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] [Second Embodiment]

[0242] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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).

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] 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".

[0254] This invention is implemented as a system for streamlining travel and related planning. The system includes various means necessary to process natural language requests from users, generate appropriate plans, and share them with other stakeholders.

[0255] First, the user accesses the chat interface using their device and enters their travel plan request. This request includes information such as the destination, desired dates, number of participants, and budget. This entered information is then sent to the server.

[0256] The server receives the user's request and applies natural language processing (NLP) to extract necessary keywords and important information from the input text. Then, based on the extracted information, it uses generative artificial intelligence (AI) technology to automatically generate a plan that covers key elements such as travel destination, accommodation, transportation, meals, and activities. During the generation process, it also refers to weather information and makes recommendations for clothing and activities to consider during the trip.

[0257] The generated plan is sent to the user's device. The user can review the proposal and request changes or the addition of specific conditions (such as budget constraints) if necessary. Upon receiving the additional request, the server regenerates the plan to reflect the user's new conditions.

[0258] The final approved plan can be shared via a communication network, for example, by sharing a link with other travel participants using a popular messenger service. This process allows all parties involved to easily review and discuss the same plan.

[0259] Furthermore, the server coordinates the payment process through electronic payment services, enabling cost sharing among participants. This allows for smooth payments between users.

[0260] For example, if a user wants to create a holiday plan, the system will present a plan that takes into account popular hotels, local restaurants, tourist attractions, and transportation options. The user can review the plan and make requests, such as "change the hotel to a slightly cheaper option." The system will immediately reflect this request and generate and present a new plan. In this way, the travel planning process is greatly simplified, reducing the effort required from the user.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] Users input their travel plans and requirements (destination, dates, budget, number of participants, etc.) in natural language through a chat interface on their device.

[0264] Step 2:

[0265] The terminal sends user input information to the server. Upon receiving the data, the server uses a natural language processing (NLP) module to extract important keywords and necessary data from the input text.

[0266] Step 3:

[0267] The server uses the extracted information to call an external API to collect weather data and obtain the weather forecast for the destination on the planned travel date.

[0268] Step 4:

[0269] The server activates a generation AI module to automatically generate a travel plan based on the user's request and acquired weather information. The plan includes suggestions for accommodation, transportation, dining options, and activities, as well as clothing and packing recommendations based on the weather.

[0270] Step 5:

[0271] The server sends the generated travel plan to the user. The user reviews the plan details on their device and requests specific conditions or changes as needed.

[0272] Step 6:

[0273] Upon receiving user feedback, the server regenerates the plan, taking the requested changes into account. The regenerated plan is immediately sent to the user for re-evaluation.

[0274] Step 7:

[0275] Once a user is satisfied with the final plan, they select the sharing option on their device, and the server generates a sharing link. The user then sends this link to the relevant parties via the communication network.

[0276] Step 8:

[0277] The server provides payment methods for cost sharing via an electronic payment service. Users make payments from their terminals, and the server checks each user's payment status and performs a final confirmation.

[0278] This process allows users to quickly and effectively create, share, and execute fully personalized travel plans.

[0279] (Example 1)

[0280] 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."

[0281] Planning a trip is a time-consuming and laborious process, requiring extensive information gathering and coordination. Travelers often find it difficult to quickly create an optimal travel plan while considering multiple factors such as destination, budget, and itinerary. Furthermore, there are numerous issues related to sharing travel plans, cost sharing, and payments, highlighting the need for efficient management systems.

[0282] 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.

[0283] In this invention, the server includes means for receiving a request regarding a travel plan from a user in natural language, analyzing the request to extract necessary information, automatically generating a travel plan using a generative artificial intelligence based on the extracted information and external information, presenting the generated travel plan to the user, and being able to regenerate the plan based on feedback from the user. As a result, the user can quickly and efficiently create an optimal travel plan and smoothly share it with other travel participants and divide expenses.

[0284] "Receiving in natural language" refers to the process of inputting information in the language form commonly used by users and converting it into a form that can be understood by the computer system.

[0285] "Analyzing the request" refers to the process of interpreting the information received from the user, extracting and organizing necessary information and keywords.

[0286] "Generative artificial intelligence" refers to an artificial intelligence technology with the ability to automatically generate new information and plans based on given data and conditions.

[0287] "Automatically generating" refers to the process by which the system makes its own judgments and creates necessary plans and information based on the user's requests and conditions.

[0288] "Can be regenerated" refers to the function of being able to perform the generation process again and provide new plans and information when there are modifications or condition changes to the plans and information created once.

[0289] "Communication network" refers to the digital data transmission infrastructure used to share information with other users and systems.

[0290] "Electronic payment" refers to a method of conducting financial transactions using digital technology, which is a system that can complete payments without using physical cash.

[0291] This invention is a system for efficiently planning travel. Users input travel requests through natural language prompts using a terminal. For example, a user might input, "I would like to travel to Tokyo next month. My budget is 100,000 yen per person, and I am thinking of a 3-night, 4-day trip." This request is immediately sent to the server.

[0292] The server uses natural language processing techniques to analyze user requests and extract keywords and information. A natural language processing framework (e.g., spaCy) is used for this analysis. The server also accesses external databases and APIs to collect external information such as destination weather, accommodation, and transportation options.

[0293] Next, the server utilizes a generative artificial intelligence model (e.g., OpenAI GPT) to automatically generate a travel plan by combining the user's requests with external information. This generated plan includes accommodations, activities, meals, transportation, and more. The generated plan is designed to be optimized for the user.

[0294] Users can review the travel plan generated through their device and request changes as needed. For example, if a user requests to change the hotel to a cheaper option, the server will regenerate and present a new plan that meets the user's requirements. This regeneration process allows for flexible planning tailored to the user's preferences.

[0295] The final plan can be shared with other travel participants via a communication network. Furthermore, the server provides electronic payment functionality to facilitate efficient cost sharing and payments among participants. This entire process makes travel planning quick and consistent, significantly reducing the user's workload.

[0296] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0297] Step 1:

[0298] The user accesses the chat interface using their device and enters prompts about their travel plans in natural language. For example, they might type, "I'd like to travel to Tokyo next month. My budget is 100,000 yen per person, and I'm thinking of a 3-night, 4-day trip." This input is sent to the server exactly as it was entered.

[0299] Step 2:

[0300] The server analyzes the prompt message received from the user using natural language processing technology. Here, the server uses "spaCy" to analyze the text and extract keywords such as destination, schedule, and budget. The keywords extracted from the input text data are then output as information used in the next processing step.

[0301] Step 3:

[0302] The server initiates access to external information sources based on keywords obtained from the analysis results. Specifically, it sends requests to weather information providers, accommodation databases, and transportation information APIs to obtain the latest information relevant to the user's travel plans. The input here is keyword data, and the output is the collected external information.

[0303] Step 4:

[0304] The server automatically generates travel plans using a generative AI model based on extracted keywords and collected external information. Using tools such as "OpenAI GPT," it creates a comprehensive plan including accommodation, activities, meals, and transportation based on the input data. As a result of the data processing performed by the generative AI, a travel plan optimized for the user is output.

[0305] Step 5:

[0306] The user checks the travel plan presented on the terminal and re-enters it if changes are needed. For example, enter a request such as "Change the hotel to a cheaper option". This re-entry is resent to the server and utilized for new processing.

[0307] Step 6:

[0308] The server regenerates the travel plan based on the user's feedback. Reflecting the data used in the initial generation and the user's new requests, a more suitable plan is generated. At this time, the regeneration AI model is used again to output the updated travel plan.

[0309] Step 7:

[0310] The finally confirmed plan is re-presented to the user through the terminal. The user can share this final plan with other travel participants using the communication network and manage expense sharing through the electronic payment function. The input is the confirmed plan, and the output is the sharing link and payment information.

[0311] (Application Example 1)

[0312] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0313] There is a need to reduce the user's effort and improve the quality of movement and activities by automating the provision of an optimal plan that takes into account environmental conditions and related information to streamline people's movement and activity plans. However, the conventional method has the problem that it is necessary to manually collect and integrate individual information, which takes time and effort.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0315] This invention includes a server that receives requests from users regarding travel and activity plans in natural language, analyzes those requests to extract necessary information, automatically generates travel and activity plans using artificial intelligence technology based on the extracted information and relevant external information, and makes the generated plans shareable with other users via communication means. This makes it possible to provide users with plans optimized for their needs and reduce the burden of information gathering and planning.

[0316] A "user" is an individual or group that intends to use the system to plan their travel and activities.

[0317] A "travel and activity plan" is a schedule of transportation methods and activities proposed based on the user's needs.

[0318] "Natural language" refers to the language that humans use on a daily basis, and is a means of inputting requests to a system in text format.

[0319] "Means for analyzing requests and extracting necessary information" refers to technologies that process information to identify meaningful keywords and information from input natural language.

[0320] "Means for automatically generating travel and activity plans using artificial intelligence technology" refers to AI technology that creates optimal plans by utilizing relevant patterns and data based on acquired information.

[0321] "External relevant information" refers to external data such as traffic conditions and weather that are referenced when generating plans.

[0322] "Communication means" refers to the network infrastructure used to send generated plans to other users.

[0323] "Means for sharing plans" refers to features that allow users to share their travel and activity plans with others.

[0324] A "payment method" is a way to share costs and manage the exchange of money between users.

[0325] An "electronic transaction service" is a system designed to facilitate the smooth exchange and payment of money conducted online.

[0326] The system that realizes this invention begins with the user inputting their travel and activity plan in natural language using a communication terminal such as a smartphone or computer. The user's input is sent to a server via the terminal. The server uses Python and natural language processing libraries to analyze this input and extract the necessary information.

[0327] The server then automatically generates travel and activity plans using a generative artificial intelligence model. At this stage, traffic and weather data obtained from external sources are incorporated to improve the accuracy and practicality of the generated plans.

[0328] Specifically, using AI frameworks such as TensorFlow and PyTorch, the system generates optimal travel and activity plans that match the user's conditions, based on acquired keywords and external data.

[0329] The generated plan is sent from the server to the user's device for review. The user can provide feedback as needed, and this information is sent back to the server, regenerating a new plan with the specified adjustments.

[0330] Furthermore, the system incorporates communication capabilities, allowing users to share generated plans with other users through a similar process. Additionally, electronic transaction services can be used to share costs and process payments related to shared plans.

[0331] For example, if a user inputs, "I want to plan a trip to a museum and lunch in Tokyo next Saturday," the system analyzes this input and suggests a plan that takes into account available transportation options and museum opening hours. Users can provide feedback such as, "I'd like to stop by a cafe after the museum," and the plan will be adjusted accordingly. Furthermore, this plan can be shared with family and friends, and expenses can be easily shared.

[0332] An example of a prompt sentence would be, "I'd like to plan my activities in the city center next Saturday. I plan to visit an art museum and then have lunch."

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] Users enter requests regarding travel and activity plans in natural language using a smartphone or computer terminal. The requests entered by the user (for example, "Visit a museum in the city center next Saturday, then have lunch") are sent to the server as text data.

[0336] Step 2:

[0337] The server parses the received request using Python and natural language processing libraries (e.g., NLTK and spaCy). It extracts keywords (e.g., "Saturday," "art museum," "lunch") from the input text data and processes the data to identify the user's request. The output of this process is data that represents the user's request as structured information.

[0338] Step 3:

[0339] The server uses extracted keywords and related external information (such as traffic conditions and weather data) as input to automatically generate travel and activity plans using a generative AI model (e.g., using TensorFlow or PyTorch). Specifically, it considers the relationships between each element, evaluates the options, and creates the optimal plan (e.g., a schedule including transportation and order of visits). The output is plan information optimized for the user.

[0340] Step 4:

[0341] The server generates a plan and sends it to the user's device. The device displays the received plan to the user through the application, allowing the user to review the plan's contents. Visual representations and detailed information about the plan are also provided.

[0342] Step 5:

[0343] The user reviews the plan and provides feedback as needed. For example, they might submit a modification request such as, "I'd like to change the lunch time to 2 PM." This feedback is then sent back to the server.

[0344] Step 6:

[0345] Based on the feedback received by the server, the AI ​​model is used again to regenerate the plan. The input is the user's feedback data, and the output is the adjusted new plan.

[0346] Step 7:

[0347] The final plan is shared by the user with other users. The server uses communication methods to distribute the generated plan link or data to other relevant users. The choice of communication tools and platforms is also considered here.

[0348] Step 8:

[0349] Users share the costs associated with the plan and complete the payment process through an electronic transaction service. This process integrates with a third-party payment service for payment confirmation and cost aggregation. The output is confirmation that the costs were processed smoothly.

[0350] 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.

[0351] This invention is configured as a system for efficiently and emotionally supporting users' travel planning. This system includes multiple means for analyzing natural language requests received from users, recognizing the user's emotional state using an emotion engine, and reflecting these in the generation of travel plans.

[0352] First, the user enters their travel plans and preferences in natural language via a chat interface on their device. This information is sent to the server. The server utilizes a natural language processing module to extract important keywords and emotional cues from the entered text.

[0353] Next, the emotion engine kicks in and analyzes the user's emotional state based on these clues. This analysis is then provided to the generative AI module, which automatically generates a travel plan that resonates with the user's emotions. For example, if the user is seeking relaxation, the system will prioritize activities and environments themed around healing, while if they prefer activities that stimulate their sense of adventure, it will suggest an active itinerary.

[0354] The generated travel plan is first presented to the user on their device, and the user can provide feedback based on the plan's content. This feedback also utilizes an emotion engine, which analyzes the user's emotional response to regenerate an even more optimal plan.

[0355] Furthermore, the final plan can be shared with other users via the communication network. Users receive a link to share this plan with other participants, making it easily accessible.

[0356] Furthermore, the server assists with cost sharing through electronic payment services and provides a mechanism for smooth payments between users. In this way, it supports the entire process up to the execution of the travel plan.

[0357] For example, if a user wishes to plan a relaxing weekend trip, the system analyzes their initial preferences and suggests a hot spring resort stay in a nature-rich tourist area. If the system analyzes that the user is experiencing stress, it will then suggest a plan that includes a quieter environment and a meditation experience to enhance the user's mental satisfaction. In this way, travel planning that incorporates the user's emotions enriches individual experiences.

[0358] The following describes the processing flow.

[0359] Step 1:

[0360] Users enter their travel plans and specific requirements on the device's chat interface. This includes destination, dates, budget, and purpose of travel (e.g., relaxation, adventure).

[0361] Step 2:

[0362] The terminal sends user input information to the server. The server processes this information using natural language processing technology to extract important keywords and phrases from the text. This reveals the user's specific wishes and requests.

[0363] Step 3:

[0364] The server activates an emotion engine to analyze emotional cues contained in the user's input text. Based on word choices and context, it determines the user's emotional state (e.g., tension, excitement, calmness).

[0365] Step 4:

[0366] The server automatically generates travel plans using a generation AI module based on extracted keywords and emotional states. In this process, it incorporates weather information and destination tourist information to provide suggestions that resonate with the user's emotions.

[0367] Step 5:

[0368] The generated travel plan is sent from the server to the user's device. The user can review the plan and provide feedback on the details. For example, they can make specific requests such as "I want to add more activities" or "I want to reduce the cost."

[0369] Step 6:

[0370] The server receives feedback from the user, performs sentiment analysis again using the sentiment engine, and incorporates the desired plan changes. As a result, it generates an improved plan incorporating the new conditions and provides it to the user again.

[0371] Step 7:

[0372] The plan that the user has finally approved can be shared with other travel participants via the communication network by selecting the sharing option through their device. The server generates a sharing link and sends it to the user.

[0373] Step 8:

[0374] The server manages expenses using electronic payment services and facilitates smooth cost sharing among participants. Users make payments on their terminals, and the server manages and monitors the overall payment status.

[0375] This process allows users to create customized travel plans that take emotions into account, and then share and execute those plans with all participants.

[0376] (Example 2)

[0377] 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".

[0378] In travel planning, conventional systems often fail to adequately consider the emotional needs of users, resulting in difficulty in providing highly satisfying travel plans. In particular, the inability to offer specific suggestions based on travel purpose and mood makes generating travel plans tailored to individual experiences a challenge. Furthermore, features such as travel plan sharing and cost sharing are insufficient, making smooth plan sharing among users difficult.

[0379] 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.

[0380] In this invention, the server includes means for receiving travel plan requests from users in natural language and extracting important clues, means for analyzing the user's emotional state based on the extracted clues, and means for automatically generating a travel plan that is tailored to the user's emotions based on the emotion analysis results and external information. This makes it possible to generate more personalized travel plans that are tailored to the user's emotions and wishes. Furthermore, payment adjustment means for sharing plans and sharing costs enable smooth plan sharing and payment among users.

[0381] "Natural language" refers to the language that users use on a daily basis and is used for requests and information input in a system.

[0382] "Clues" are important pieces of information extracted from user input, and they form the basis for sentiment analysis and plan generation.

[0383] "Emotional analysis" is a process that determines a user's emotional state based on their input and actions, and estimates their psychological needs.

[0384] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates travel plans tailored to the user.

[0385] A "travel plan" is a specific proposal of travel itinerary and activities based on the user's requests and emotional state.

[0386] A "communication line" is a communication network that enables data exchange between users and serves as the foundation for information sharing.

[0387] "Payment adjustment" is a method of managing payment procedures using electronic payments to fairly distribute the costs of a travel plan among users.

[0388] The embodiments for carrying out the present invention are described below.

[0389] As an example of this system, the user first uses their device to input their travel plans, preferences, and requirements in natural language. The entered information is then sent from the user to the server. The server uses existing platforms such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding as its natural language processing engine to extract important clues from the user's requests.

[0390] Next, the server performs sentiment analysis based on the clues. This analysis uses sentiment analysis capabilities such as Microsoft Azure Text Analytics to identify the user's psychological state. For example, it can determine whether the user is seeking relaxation or adventure.

[0391] Based on the analysis of the user's emotional state, the server uses a generative AI model to automatically create a travel plan that resonates with the user's feelings. One example of such an AI model is the OpenAI GPT model. The generated travel plan might include suggestions for resort destinations with abundant nature for a user seeking relaxation.

[0392] The generated plan is transferred to the device, where the user can review it and provide feedback. The server, upon receiving the feedback, performs another sentiment analysis and optimizes the plan as needed. Based on the feedback, elements such as "quiet environment" or "meditation experience" can be included.

[0393] Furthermore, the final travel plan can be easily shared with other users via a communication network. Users can use the provided link to share their plan with other devices and collaborate on planning.

[0394] Furthermore, the server coordinates payments for travel plans through its electronic payment functionality. Specifically, it can smoothly share costs among users using electronic payment platforms such as PayPal and Stripe.

[0395] As a concrete example, consider a scenario where a user enters "I want to go somewhere relaxing next weekend" as a prompt. The system then performs natural language analysis and, through sentiment analysis, suggests a relaxing travel plan. The user can then plan a more satisfying travel experience based on the suggested plan.

[0396] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0397] Step 1:

[0398] The user enters their travel plans and preferences in natural language on their device. This input data is sent to the server in text format. For example, the user might enter the prompt, "I'm looking for a relaxing beach resort."

[0399] Step 2:

[0400] The server analyzes the received natural language data using a natural language processing engine to extract important keywords and clues. Keywords such as "relax," "beach," and "resort" are extracted from the input text. The Google Cloud Natural Language API may be used at this stage.

[0401] Step 3:

[0402] Based on the extracted clues, the server uses an emotion analysis engine to analyze the user's emotional state. The data analysis determines that the user's emotional state is "wanting to relax." For example, Microsoft Azure Text Analytics might be used at this stage.

[0403] Step 4:

[0404] The server automatically generates personalized travel plans for users based on sentiment data and keywords through a generative AI model. Here, the generative AI model processes the information obtained in the previous stage to create itinerary suggestions, including a list of suitable beach resorts. OpenAI GPT models, among others, may be used in this process.

[0405] Step 5:

[0406] The generated travel plan is printed on the device and presented to the user. The user can review the plan and provide feedback as needed. For example, the user might comment, "I'd like to add a few more activities."

[0407] Step 6:

[0408] The server receives user feedback, performs sentiment analysis again, and regenerates a more suitable plan. It incorporates the feedback as data and optimizes the initial plan, such as adding new activities.

[0409] Step 7:

[0410] The final travel plan generates a link that can be shared with other users via a communication network. Users can then use this link to share their plans with friends and family. Specifically, the generated link can be sent via email or messaging apps.

[0411] Step 8:

[0412] The server utilizes an electronic payment platform to coordinate payments for travel plans and manage cost sharing among users. Specifically, it uses services like PayPal and Stripe to ensure that accommodation and transportation costs are fairly shared among participants.

[0413] (Application Example 2)

[0414] 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."

[0415] Traditional travel planning often struggled to reflect users' emotions and individual preferences, resulting in generic suggestions. Furthermore, the process of sharing travel plans and costs with others was complex and inconvenient. The lack of personalized travel plan suggestions hindered user satisfaction.

[0416] 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.

[0417] This invention includes a server that receives travel planning requests from users in natural language, analyzes those requests to extract necessary information, automatically generates a travel schedule using generative artificial intelligence based on the extracted information and external information, and presents the generated travel schedule to the user and can regenerate the schedule based on the user's evaluation. This enables the creation of flexible travel plans that are tailored to the user's emotions and individual preferences, as well as the efficient sharing of costs.

[0418] A "user" is an individual or group that uses the system to receive travel plan suggestions.

[0419] "Travel plan requests" refer to information that indicates the user's travel preferences and conditions that they want the system to meet.

[0420] "Natural language" refers to the language that humans use on a daily basis, expressed through text or speech.

[0421] "Means of extracting information" refers to methods for extracting specific keywords and important elements from user requests.

[0422] "External information" refers to data other than what the user requested that is used to suggest travel plans, and includes, for example, information about weather and traffic conditions.

[0423] "Generative artificial intelligence" is an artificial intelligence technology that generates appropriate travel schedules based on user requests and external information.

[0424] "Methods for automatically generating travel schedules" refers to methods that use artificial intelligence to create travel plans tailored to the user's preferences.

[0425] "Means of presenting to the user" refers to methods of providing the generated travel plan in a way that allows the user to visually confirm it.

[0426] "User ratings" refer to users' opinions and feedback on the presented travel plans.

[0427] "Methods for regenerating schedules" refer to methods for redesigning travel plans based on user feedback.

[0428] A "communication data network" is a network system used to share information with other users.

[0429] "Users" refers to other individuals or groups who view or share the generated travel schedule.

[0430] A "payment method for sharing expenses" refers to a method for efficiently sharing and paying for travel-related expenses among users.

[0431] The system for implementing this invention begins with a user inputting a travel plan request in natural language via a smartphone. This information is sent to a cloud-based server, where the request is analyzed using a natural language processing module. During the analysis, the server uses natural language processing software, such as Google Bard or OpenAI's GPT model, to extract keywords and sentiment cues from the information obtained from the user.

[0432] Next, the emotion recognition engine analyzes the user's emotional state and provides the results to the generative artificial intelligence module. This module utilizes a generative AI model to generate a personalized travel schedule based on the user's emotions and expectations. The generated schedule is presented to the user on their device, allowing them to intuitively review its contents.

[0433] When a user provides feedback on the schedule, the server re-analyzes the feedback and regenerates the schedule to optimize it. The regenerated schedule is then presented to the user via their smartphone.

[0434] Furthermore, the terminal has the function to share the generated schedule with other users via the communication data network. Regarding the shared schedule, electronic payment technology is used to facilitate the smooth sharing of costs among users.

[0435] For example, if a user inputs "I want to visit a place where I can refresh myself in a quiet natural setting on the weekend," the system can grasp the user's desire for refreshment and suggest a travel schedule that includes visits to quiet parks and hot spring facilities. An example of a prompt to the generative AI model used in this case would be, "Please tell me how to spend a weekend refreshing myself in a quiet natural setting."

[0436] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0437] Step 1:

[0438] The user uses a terminal to input travel plan requests in natural language. The input is sent to the server as text data. During this process, the terminal uses a text editor or voice input function to collect specific details about the user's preferences.

[0439] Step 2:

[0440] The server passes the received text data to a natural language processing module. Here, the server extracts important keywords and sentiment cues from the text, for example, using an OpenAI GPT model. The input is natural language text, and the output is keyword and sentiment information. This information is later provided to the sentiment engine.

[0441] Step 3:

[0442] The server uses an emotion engine to analyze the emotion information obtained in step 2. Here, the user's emotional state is evaluated in detail, and necessary data processing is performed. The input is emotion information, and the output is data about the specific emotional state. This data is provided to the generative artificial intelligence module.

[0443] Step 4:

[0444] The server uses a generative artificial intelligence module to generate a travel schedule based on the user's emotional state and requests. It utilizes a generative AI model to perform data calculations, including prompts. The input is the emotional and request data analyzed in step 3, and the output is a travel schedule plan.

[0445] Step 5:

[0446] The generated travel schedule is sent to the terminal and presented to the user. The terminal uses a GUI (Graphical User Interface) to visually display the schedule. The input is the generated travel schedule data, and the output is a user-friendly schedule display.

[0447] Step 6:

[0448] The user provides feedback on the presented schedule. This information is then sent back to the server via the device. The feedback is analyzed for sentiment and converted into data that represents specific improvement requests.

[0449] Step 7:

[0450] The server repeats the process in step 4 to regenerate the travel schedule based on user feedback. During this process, the feedback is re-evaluated by the generating AI model, and an optimized plan is created. The input is the feedback data, and the output is the regenerated travel schedule.

[0451] Step 8:

[0452] The final travel schedule is provided to the device in a format that can be shared with other users via a communication data network. The device uses a sharing link generation function to easily share this information with other users. The input is the final schedule data, and the output is a shareable link.

[0453] Step 9:

[0454] The server uses electronic payment functionality to streamline the sharing of travel expenses. Expense payments between users are automatically coordinated using electronic payment technology. Inputs are user information and expense data, and output is the transaction result with expenses already shared.

[0455] 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.

[0456] 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.

[0457] 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.

[0458] [Third Embodiment]

[0459] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0460] 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.

[0461] 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).

[0462] 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.

[0463] 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.

[0464] 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).

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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.

[0469] 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.

[0470] 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".

[0471] This invention is implemented as a system for streamlining travel and related planning. The system includes various means necessary to process natural language requests from users, generate appropriate plans, and share them with other stakeholders.

[0472] First, the user accesses the chat interface using their device and enters their travel plan request. This request includes information such as the destination, desired dates, number of participants, and budget. This entered information is then sent to the server.

[0473] The server receives the user's request and applies natural language processing (NLP) to extract necessary keywords and important information from the input text. Then, based on the extracted information, it uses generative artificial intelligence (AI) technology to automatically generate a plan that covers key elements such as travel destination, accommodation, transportation, meals, and activities. During the generation process, it also refers to weather information and makes recommendations for clothing and activities to consider during the trip.

[0474] The generated plan is sent to the user's device. The user can review the proposal and request changes or the addition of specific conditions (such as budget constraints) if necessary. Upon receiving the additional request, the server regenerates the plan to reflect the user's new conditions.

[0475] The final approved plan can be shared via a communication network, for example, by sharing a link with other travel participants using a popular messenger service. This process allows all parties involved to easily review and discuss the same plan.

[0476] Furthermore, the server coordinates the payment process through electronic payment services, enabling cost sharing among participants. This allows for smooth payments between users.

[0477] For example, if a user wants to create a holiday plan, the system will present a plan that takes into account popular hotels, local restaurants, tourist attractions, and transportation options. The user can review the plan and make requests, such as "change the hotel to a slightly cheaper option." The system will immediately reflect this request and generate and present a new plan. In this way, the travel planning process is greatly simplified, reducing the effort required from the user.

[0478] The following describes the processing flow.

[0479] Step 1:

[0480] Users input their travel plans and requirements (destination, dates, budget, number of participants, etc.) in natural language through a chat interface on their device.

[0481] Step 2:

[0482] The terminal sends user input information to the server. Upon receiving the data, the server uses a natural language processing (NLP) module to extract important keywords and necessary data from the input text.

[0483] Step 3:

[0484] The server uses the extracted information to call an external API to collect weather data and obtain the weather forecast for the destination on the planned travel date.

[0485] Step 4:

[0486] The server activates a generation AI module to automatically generate a travel plan based on the user's request and acquired weather information. The plan includes suggestions for accommodation, transportation, dining options, and activities, as well as clothing and packing recommendations based on the weather.

[0487] Step 5:

[0488] The server sends the generated travel plan to the user. The user reviews the plan details on their device and requests specific conditions or changes as needed.

[0489] Step 6:

[0490] Upon receiving user feedback, the server regenerates the plan, taking the requested changes into account. The regenerated plan is immediately sent to the user for re-evaluation.

[0491] Step 7:

[0492] Once a user is satisfied with the final plan, they select the sharing option on their device, and the server generates a sharing link. The user then sends this link to the relevant parties via the communication network.

[0493] Step 8:

[0494] The server provides payment methods for cost sharing via an electronic payment service. Users make payments from their terminals, and the server checks each user's payment status and performs a final confirmation.

[0495] This process allows users to quickly and effectively create, share, and execute fully personalized travel plans.

[0496] (Example 1)

[0497] 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."

[0498] Planning a trip is a time-consuming and laborious process, requiring extensive information gathering and coordination. Travelers often find it difficult to quickly create an optimal travel plan while considering multiple factors such as destination, budget, and itinerary. Furthermore, there are numerous issues related to sharing travel plans, cost sharing, and payments, highlighting the need for efficient management systems.

[0499] 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.

[0500] This invention includes a server that receives requests from users regarding travel plans in natural language, analyzes those requests to extract necessary information, automatically generates a travel plan using generative artificial intelligence based on the extracted information and external information, and presents the generated travel plan to the user and can regenerate the plan based on user feedback. This enables users to quickly and efficiently create optimal travel plans and smoothly share them with other travel participants and share costs.

[0501] "Receiving information in natural language" refers to the process of inputting information using the language format that users use on a daily basis and converting it into a format that the computer system can understand.

[0502] "Analyzing requests" refers to the process of interpreting information received from users, extracting necessary information and keywords, and organizing them.

[0503] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate new information and plans based on given data and conditions.

[0504] "Automatic generation" refers to the process in which a system makes its own decisions based on user requests and conditions, and creates the necessary plans and information.

[0505] "Regenerative capabilities" refer to a function that allows you to regenerate a plan or information once it has been created if there are any modifications or changes in conditions, thereby providing a new plan or information.

[0506] A "communication network" is a digital data transmission infrastructure used to share information with other users and systems.

[0507] "Electronic payment" is a method of conducting monetary transactions using digital technology, and it is a system that allows payments to be completed without using physical cash.

[0508] This invention is a system for efficiently planning travel. Users input travel requests through natural language prompts using a terminal. For example, a user might input, "I would like to travel to Tokyo next month. My budget is 100,000 yen per person, and I am thinking of a 3-night, 4-day trip." This request is immediately sent to the server.

[0509] The server uses natural language processing techniques to analyze user requests and extract keywords and information. A natural language processing framework (e.g., spaCy) is used for this analysis. The server also accesses external databases and APIs to collect external information such as destination weather, accommodation, and transportation options.

[0510] Next, the server utilizes a generative artificial intelligence model (e.g., OpenAI GPT) to automatically generate a travel plan by combining the user's requests with external information. This generated plan includes accommodations, activities, meals, transportation, and more. The generated plan is designed to be optimized for the user.

[0511] Users can review the travel plan generated through their device and request changes as needed. For example, if a user requests to change the hotel to a cheaper option, the server will regenerate and present a new plan that meets the user's requirements. This regeneration process allows for flexible planning tailored to the user's preferences.

[0512] The final plan can be shared with other travel participants via a communication network. Furthermore, the server provides electronic payment functionality to facilitate efficient cost sharing and payments among participants. This entire process makes travel planning quick and consistent, significantly reducing the user's workload.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] The user accesses the chat interface using their device and enters prompts about their travel plans in natural language. For example, they might type, "I'd like to travel to Tokyo next month. My budget is 100,000 yen per person, and I'm thinking of a 3-night, 4-day trip." This input is sent to the server exactly as it was entered.

[0516] Step 2:

[0517] The server analyzes the prompt message received from the user using natural language processing technology. Here, the server uses "spaCy" to analyze the text and extract keywords such as destination, schedule, and budget. The keywords extracted from the input text data are then output as information used in the next processing step.

[0518] Step 3:

[0519] The server initiates access to external information sources based on keywords obtained from the analysis results. Specifically, it sends requests to weather information providers, accommodation databases, and transportation information APIs to obtain the latest information relevant to the user's travel plans. The input here is keyword data, and the output is the collected external information.

[0520] Step 4:

[0521] The server automatically generates travel plans using a generative AI model based on extracted keywords and collected external information. Using tools such as "OpenAI GPT," it creates a comprehensive plan including accommodation, activities, meals, and transportation based on the input data. As a result of the data processing performed by the generative AI, a travel plan optimized for the user is output.

[0522] Step 5:

[0523] The user reviews the travel plan displayed on the device and re-enters the information if changes are needed. For example, they might enter a request to "change the hotel to a slightly cheaper option." This re-entry is sent back to the server and used for further processing.

[0524] Step 6:

[0525] The server regenerates the travel plan based on user feedback. It incorporates the data used in the initial generation and the user's new requests to create a plan that better matches the user's needs. The AI ​​model is used again to output the updated travel plan.

[0526] Step 7:

[0527] The finalized plan is presented to the user via the terminal. The user can then share this final plan with other travel participants using the communication network and manage cost sharing through electronic payment functionality. The input is the finalized plan, and the output is a sharing link and payment information.

[0528] (Application Example 1)

[0529] 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."

[0530] There is a need to streamline people's travel and activity planning, automatically providing optimal plans that take environmental conditions and relevant information into account, thereby reducing user effort and improving the quality of travel and activities. However, traditional methods require the manual collection and integration of individual pieces of information, which is time-consuming and labor-intensive.

[0531] 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.

[0532] This invention includes a server that receives requests from users regarding travel and activity plans in natural language, analyzes those requests to extract necessary information, automatically generates travel and activity plans using artificial intelligence technology based on the extracted information and relevant external information, and makes the generated plans shareable with other users via communication means. This makes it possible to provide users with plans optimized for their needs and reduce the burden of information gathering and planning.

[0533] A "user" is an individual or group that intends to use the system to plan their travel and activities.

[0534] A "travel and activity plan" is a schedule of transportation methods and activities proposed based on the user's needs.

[0535] "Natural language" refers to the language that humans use on a daily basis, and is a means of inputting requests to a system in text format.

[0536] "Means for analyzing requests and extracting necessary information" refers to technologies that process information to identify meaningful keywords and information from input natural language.

[0537] "Means for automatically generating travel and activity plans using artificial intelligence technology" refers to AI technology that creates optimal plans by utilizing relevant patterns and data based on acquired information.

[0538] "External relevant information" refers to external data such as traffic conditions and weather that are referenced when generating plans.

[0539] "Communication means" refers to the network infrastructure used to send generated plans to other users.

[0540] "Means for sharing plans" refers to features that allow users to share their travel and activity plans with others.

[0541] A "payment method" is a way to share costs and manage the exchange of money between users.

[0542] An "electronic transaction service" is a system designed to facilitate the smooth exchange and payment of money conducted online.

[0543] The system that realizes this invention begins with the user inputting their travel and activity plan in natural language using a communication terminal such as a smartphone or computer. The user's input is sent to a server via the terminal. The server uses Python and natural language processing libraries to analyze this input and extract the necessary information.

[0544] The server then automatically generates travel and activity plans using a generative artificial intelligence model. At this stage, traffic and weather data obtained from external sources are incorporated to improve the accuracy and practicality of the generated plans.

[0545] Specifically, using AI frameworks such as TensorFlow and PyTorch, the system generates optimal travel and activity plans that match the user's conditions, based on acquired keywords and external data.

[0546] The generated plan is sent from the server to the user's device for review. The user can provide feedback as needed, and this information is sent back to the server, regenerating a new plan with the specified adjustments.

[0547] Furthermore, the system incorporates communication capabilities, allowing users to share generated plans with other users through a similar process. Additionally, electronic transaction services can be used to share costs and process payments related to shared plans.

[0548] For example, if a user inputs, "I want to plan a trip to a museum and lunch in Tokyo next Saturday," the system analyzes this input and suggests a plan that takes into account available transportation options and museum opening hours. Users can provide feedback such as, "I'd like to stop by a cafe after the museum," and the plan will be adjusted accordingly. Furthermore, this plan can be shared with family and friends, and expenses can be easily shared.

[0549] An example of a prompt sentence would be, "I'd like to plan my activities in the city center next Saturday. I plan to visit an art museum and then have lunch."

[0550] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0551] Step 1:

[0552] Users enter requests regarding travel and activity plans in natural language using a smartphone or computer terminal. The requests entered by the user (for example, "Visit a museum in the city center next Saturday, then have lunch") are sent to the server as text data.

[0553] Step 2:

[0554] The server parses the received request using Python and natural language processing libraries (e.g., NLTK and spaCy). It extracts keywords (e.g., "Saturday," "art museum," "lunch") from the input text data and processes the data to identify the user's request. The output of this process is data that represents the user's request as structured information.

[0555] Step 3:

[0556] The server uses extracted keywords and related external information (such as traffic conditions and weather data) as input to automatically generate travel and activity plans using a generative AI model (e.g., using TensorFlow or PyTorch). Specifically, it considers the relationships between each element, evaluates the options, and creates the optimal plan (e.g., a schedule including transportation and order of visits). The output is plan information optimized for the user.

[0557] Step 4:

[0558] The server generates a plan and sends it to the user's device. The device displays the received plan to the user through the application, allowing the user to review the plan's contents. Visual representations and detailed information about the plan are also provided.

[0559] Step 5:

[0560] The user reviews the plan and provides feedback as needed. For example, they might submit a modification request such as, "I'd like to change the lunch time to 2 PM." This feedback is then sent back to the server.

[0561] Step 6:

[0562] Based on the feedback received by the server, the AI ​​model is used again to regenerate the plan. The input is the user's feedback data, and the output is the adjusted new plan.

[0563] Step 7:

[0564] The final plan is shared by the user with other users. The server uses communication methods to distribute the generated plan link or data to other relevant users. The choice of communication tools and platforms is also considered here.

[0565] Step 8:

[0566] Users share the costs associated with the plan and complete the payment process through an electronic transaction service. This process integrates with a third-party payment service for payment confirmation and cost aggregation. The output is confirmation that the costs were processed smoothly.

[0567] 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.

[0568] This invention is configured as a system for efficiently and emotionally supporting users' travel planning. This system includes multiple means for analyzing natural language requests received from users, recognizing the user's emotional state using an emotion engine, and reflecting these in the generation of travel plans.

[0569] First, the user enters their travel plans and preferences in natural language via a chat interface on their device. This information is sent to the server. The server utilizes a natural language processing module to extract important keywords and emotional cues from the entered text.

[0570] Next, the emotion engine kicks in and analyzes the user's emotional state based on these clues. This analysis is then provided to the generative AI module, which automatically generates a travel plan that resonates with the user's emotions. For example, if the user is seeking relaxation, the system will prioritize activities and environments themed around healing, while if they prefer activities that stimulate their sense of adventure, it will suggest an active itinerary.

[0571] The generated travel plan is first presented to the user on their device, and the user can provide feedback based on the plan's content. This feedback also utilizes an emotion engine, which analyzes the user's emotional response to regenerate an even more optimal plan.

[0572] Furthermore, the final plan can be shared with other users via the communication network. Users receive a link to share this plan with other participants, making it easily accessible.

[0573] Furthermore, the server assists with cost sharing through electronic payment services and provides a mechanism for smooth payments between users. In this way, it supports the entire process up to the execution of the travel plan.

[0574] For example, if a user wishes to plan a relaxing weekend trip, the system analyzes their initial preferences and suggests a hot spring resort stay in a nature-rich tourist area. If the system analyzes that the user is experiencing stress, it will then suggest a plan that includes a quieter environment and a meditation experience to enhance the user's mental satisfaction. In this way, travel planning that incorporates the user's emotions enriches individual experiences.

[0575] The following describes the processing flow.

[0576] Step 1:

[0577] Users enter their travel preferences and detailed requirements on the device's chat interface. This includes destination, dates, budget, and purpose of travel (e.g., relaxation, adventure).

[0578] Step 2:

[0579] The terminal sends user input information to the server. The server processes this information using natural language processing technology to extract important keywords and phrases from the text. This reveals the user's specific wishes and requests.

[0580] Step 3:

[0581] The server activates an emotion engine to analyze emotional cues contained in the user's input text. Based on word choices and context, it determines the user's emotional state (e.g., tension, excitement, calmness).

[0582] Step 4:

[0583] The server automatically generates travel plans using a generation AI module based on extracted keywords and emotional states. In this process, it incorporates weather information and destination tourist information to provide suggestions that resonate with the user's emotions.

[0584] Step 5:

[0585] The generated travel plan is sent from the server to the user's device. The user can review the plan and provide feedback on the details. For example, they can make specific requests such as "I want to add more activities" or "I want to reduce the cost."

[0586] Step 6:

[0587] The server receives feedback from the user, performs sentiment analysis again using the sentiment engine, and incorporates the desired plan changes. As a result, it generates an improved plan incorporating the new conditions and provides it to the user again.

[0588] Step 7:

[0589] The plan that the user has finally approved can be shared with other travel participants via the communication network by selecting the sharing option through their device. The server generates a sharing link and sends it to the user.

[0590] Step 8:

[0591] The server manages expenses using electronic payment services and facilitates smooth cost sharing among participants. Users make payments on their terminals, and the server manages and monitors the overall payment status.

[0592] This process allows users to create customized travel plans that take emotions into account, and then share and execute those plans with all participants.

[0593] (Example 2)

[0594] 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."

[0595] In travel planning, conventional systems often fail to adequately consider the emotional needs of users, resulting in difficulty in providing highly satisfying travel plans. In particular, the inability to offer specific suggestions based on travel purpose and mood makes generating travel plans tailored to individual experiences a challenge. Furthermore, features such as travel plan sharing and cost sharing are insufficient, making smooth plan sharing among users difficult.

[0596] 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.

[0597] In this invention, the server includes means for receiving travel plan requests from users in natural language and extracting important clues, means for analyzing the user's emotional state based on the extracted clues, and means for automatically generating a travel plan that is tailored to the user's emotions based on the emotion analysis results and external information. This makes it possible to generate more personalized travel plans that are tailored to the user's emotions and wishes. Furthermore, payment adjustment means for sharing plans and sharing costs enable smooth plan sharing and payment among users.

[0598] "Natural language" refers to the language that users use on a daily basis and is used for requests and information input in systems.

[0599] "Clues" are important pieces of information extracted from user input, and they form the basis for sentiment analysis and plan generation.

[0600] "Emotional analysis" is a process that determines a user's emotional state based on their input and actions, and estimates their psychological needs.

[0601] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates travel plans tailored to the user.

[0602] A "travel plan" is a specific proposal of travel itinerary and activities based on the user's requests and emotional state.

[0603] A "communication line" is a communication network that enables data exchange between users and serves as the foundation for information sharing.

[0604] "Payment adjustment" is a method of managing payment procedures using electronic payments to fairly distribute the costs of a travel plan among users.

[0605] The embodiments for carrying out the present invention are described below.

[0606] As an example of this system, the user first uses their device to input their travel plans, preferences, and requirements in natural language. The entered information is then sent from the user to the server. The server uses existing platforms such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding as its natural language processing engine to extract important clues from the user's requests.

[0607] Next, the server performs sentiment analysis based on the clues. This analysis uses sentiment analysis capabilities such as Microsoft Azure Text Analytics to identify the user's psychological state. For example, it can determine whether the user is seeking relaxation or adventure.

[0608] Based on the analysis of the user's emotional state, the server uses a generative AI model to automatically create a travel plan that resonates with the user's feelings. One example of such an AI model is the OpenAI GPT model. The generated travel plan might include suggestions for resort destinations with abundant nature for a user seeking relaxation.

[0609] The generated plan is transferred to the device, where the user can review it and provide feedback. The server, upon receiving the feedback, performs another sentiment analysis and optimizes the plan as needed. Based on the feedback, elements such as "quiet environment" or "meditation experience" can be included.

[0610] Furthermore, the final travel plan can be easily shared with other users via a communication network. Users can use the provided link to share their plan with other devices and collaborate on planning.

[0611] Furthermore, the server coordinates payments for travel plans through its electronic payment functionality. Specifically, it can smoothly share costs among users using electronic payment platforms such as PayPal and Stripe.

[0612] As a concrete example, consider a scenario where a user enters "I want to go somewhere relaxing next weekend" as a prompt. The system then performs natural language analysis and, through sentiment analysis, suggests a relaxing travel plan. The user can then plan a more satisfying travel experience based on the suggested plan.

[0613] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0614] Step 1:

[0615] The user enters their travel plans and preferences in natural language on their device. This input data is sent to the server in text format. For example, the user might enter the prompt, "I'm looking for a relaxing beach resort."

[0616] Step 2:

[0617] The server analyzes the received natural language data using a natural language processing engine to extract important keywords and clues. Keywords such as "relax," "beach," and "resort" are extracted from the input text. The Google Cloud Natural Language API may be used at this stage.

[0618] Step 3:

[0619] Based on the extracted clues, the server uses an emotion analysis engine to analyze the user's emotional state. The data analysis determines that the user's emotional state is "wanting to relax." For example, Microsoft Azure Text Analytics might be used at this stage.

[0620] Step 4:

[0621] The server automatically generates personalized travel plans for users based on sentiment data and keywords through a generative AI model. Here, the generative AI model processes the information obtained in the previous stage to create itinerary suggestions, including a list of suitable beach resorts. OpenAI GPT models, among others, may be used in this process.

[0622] Step 5:

[0623] The generated travel plan is printed on the device and presented to the user. The user can review the plan and provide feedback as needed. For example, the user might comment, "I'd like to add a few more activities."

[0624] Step 6:

[0625] The server receives user feedback, performs sentiment analysis again, and regenerates a more suitable plan. It incorporates the feedback as data and optimizes the initial plan, such as adding new activities.

[0626] Step 7:

[0627] The final travel plan generates a link that can be shared with other users via a communication network. Users can use this link to share their plans with friends and family. Specifically, the generated link can be sent via email or messaging apps.

[0628] Step 8:

[0629] The server utilizes an electronic payment platform to coordinate payments for travel plans and manage cost sharing among users. Specifically, it uses services like PayPal and Stripe to ensure that accommodation and transportation costs are fairly shared among participants.

[0630] (Application Example 2)

[0631] 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."

[0632] Traditional travel planning often struggled to reflect users' emotions and individual preferences, resulting in generic suggestions. Furthermore, the process of sharing travel plans and costs with others was complex and inconvenient. The lack of personalized travel plan suggestions hindered user satisfaction.

[0633] 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.

[0634] This invention includes a server that receives travel planning requests from users in natural language, analyzes those requests to extract necessary information, automatically generates a travel schedule using generative artificial intelligence based on the extracted information and external information, and presents the generated travel schedule to the user and can regenerate the schedule based on the user's evaluation. This enables the creation of flexible travel plans that are tailored to the user's emotions and individual preferences, as well as the efficient sharing of costs.

[0635] A "user" is an individual or group that uses the system to receive travel plan suggestions.

[0636] "Travel plan requests" refer to information that indicates the user's travel preferences and conditions that they want the system to meet.

[0637] "Natural language" refers to the language that humans use on a daily basis, expressed through text or speech.

[0638] "Means of extracting information" refers to methods for extracting specific keywords and important elements from user requests.

[0639] "External information" refers to data other than what the user requested that is used to suggest travel plans, and includes, for example, information about weather and traffic conditions.

[0640] "Generative artificial intelligence" is an artificial intelligence technology that generates appropriate travel schedules based on user requests and external information.

[0641] "Methods for automatically generating travel schedules" refers to methods that use artificial intelligence to create travel plans tailored to the user's preferences.

[0642] "Means of presenting to the user" refers to methods of providing the generated travel plan in a way that allows the user to visually confirm it.

[0643] "User ratings" refer to users' opinions and feedback on the presented travel plans.

[0644] "Methods for regenerating schedules" refer to methods for redesigning travel plans based on user feedback.

[0645] A "communication data network" is a network system used to share information with other users.

[0646] "Users" refers to other individuals or groups who view or share the generated travel schedule.

[0647] A "payment method for sharing expenses" refers to a method for efficiently sharing and paying for travel-related expenses among users.

[0648] The system for implementing this invention begins with a user inputting a travel plan request in natural language via a smartphone. This information is sent to a cloud-based server, where the request is analyzed using a natural language processing module. During the analysis, the server uses natural language processing software, such as Google Bard or OpenAI's GPT model, to extract keywords and sentiment cues from the information obtained from the user.

[0649] Next, the emotion recognition engine analyzes the user's emotional state and provides the results to the generative artificial intelligence module. This module utilizes a generative AI model to generate a personalized travel schedule based on the user's emotions and expectations. The generated schedule is presented to the user on their device, allowing them to intuitively review its contents.

[0650] When a user provides feedback on the schedule, the server re-analyzes the feedback and regenerates the schedule to optimize it. The regenerated schedule is then presented to the user via their smartphone.

[0651] Furthermore, the terminal has the function to share the generated schedule with other users via the communication data network. Regarding the shared schedule, electronic payment technology is used to facilitate the smooth sharing of costs among users.

[0652] For example, if a user inputs "I want to visit a place where I can refresh myself in a quiet natural setting on the weekend," the system can grasp the user's desire for refreshment and suggest a travel schedule that includes visits to quiet parks and hot spring facilities. An example of a prompt to the generative AI model used in this case would be, "Please tell me how to spend a weekend refreshing myself in a quiet natural setting."

[0653] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0654] Step 1:

[0655] The user uses a terminal to input travel plan requests in natural language. The input is sent to the server as text data. During this process, the terminal uses a text editor or voice input function to collect specific details about the user's preferences.

[0656] Step 2:

[0657] The server passes the received text data to a natural language processing module. Here, the server extracts important keywords and sentiment cues from the text, for example, using an OpenAI GPT model. The input is natural language text, and the output is keyword and sentiment information. This information is later provided to the sentiment engine.

[0658] Step 3:

[0659] The server uses an emotion engine to analyze the emotion information obtained in step 2. Here, the user's emotional state is evaluated in detail, and necessary data processing is performed. The input is emotion information, and the output is data about the specific emotional state. This data is provided to the generative artificial intelligence module.

[0660] Step 4:

[0661] The server uses a generative artificial intelligence module to generate a travel schedule based on the user's emotional state and requests. It utilizes a generative AI model to perform data calculations, including prompts. The input is the emotional and request data analyzed in step 3, and the output is a travel schedule plan.

[0662] Step 5:

[0663] The generated travel schedule is sent to the terminal and presented to the user. The terminal uses a GUI (Graphical User Interface) to visually display the schedule. The input is the generated travel schedule data, and the output is a user-friendly schedule display.

[0664] Step 6:

[0665] The user provides feedback on the presented schedule. This information is then sent back to the server via the device. The feedback is analyzed for sentiment and converted into data that represents specific improvement requests.

[0666] Step 7:

[0667] The server repeats the process in step 4 to regenerate the travel schedule based on user feedback. During this process, the feedback is re-evaluated by the generating AI model, and an optimized plan is created. The input is the feedback data, and the output is the regenerated travel schedule.

[0668] Step 8:

[0669] The final travel schedule is provided to the device in a format that can be shared with other users via a communication data network. The device uses a sharing link generation function to easily share the schedule with other users. The input is the final schedule data, and the output is a shareable link.

[0670] Step 9:

[0671] The server uses electronic payment functionality to streamline the sharing of travel expenses. Expense payments between users are automatically coordinated using electronic payment technology. Inputs are user information and expense data, and output is the transaction result with expenses already shared.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] [Fourth Embodiment]

[0676] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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).

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] 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.

[0687] 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.

[0688] 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".

[0689] This invention is implemented as a system for streamlining travel and related planning. The system includes various means necessary to process natural language requests from users, generate appropriate plans, and share them with other stakeholders.

[0690] First, the user accesses the chat interface using their device and enters their travel plan request. This request includes information such as the destination, desired dates, number of participants, and budget. This entered information is then sent to the server.

[0691] The server receives the user's request and applies natural language processing (NLP) to extract necessary keywords and important information from the input text. Then, based on the extracted information, it uses generative artificial intelligence (AI) technology to automatically generate a plan that covers key elements such as travel destination, accommodation, transportation, meals, and activities. During the generation process, it also refers to weather information and makes recommendations for clothing and activities to consider during the trip.

[0692] The generated plan is sent to the user's device. The user can review the proposal and request changes or the addition of specific conditions (such as budget constraints) if necessary. Upon receiving the additional request, the server regenerates the plan to reflect the user's new conditions.

[0693] The final approved plan can be shared via a communication network, for example, by sharing a link with other travel participants using a popular messenger service. This process allows all parties involved to easily review and discuss the same plan.

[0694] Furthermore, the server coordinates the payment process through electronic payment services, enabling cost sharing among participants. This allows for smooth payments between users.

[0695] For example, if a user wants to create a holiday plan, the system will present a plan that takes into account popular hotels, local restaurants, tourist attractions, and transportation options. The user can review the plan and make requests, such as "change the hotel to a slightly cheaper option." The system will immediately reflect this request and generate and present a new plan. In this way, the travel planning process is greatly simplified, reducing the effort required from the user.

[0696] The following describes the processing flow.

[0697] Step 1:

[0698] Users input their travel plans and requirements (destination, dates, budget, number of participants, etc.) in natural language through a chat interface on their device.

[0699] Step 2:

[0700] The terminal sends user input information to the server. Upon receiving the data, the server uses a natural language processing (NLP) module to extract important keywords and necessary data from the input text.

[0701] Step 3:

[0702] The server uses the extracted information to call an external API to collect weather data and obtain the weather forecast for the destination on the planned travel date.

[0703] Step 4:

[0704] The server activates a generation AI module to automatically generate a travel plan based on the user's request and acquired weather information. The plan includes suggestions for accommodation, transportation, dining options, and activities, as well as clothing and packing recommendations based on the weather.

[0705] Step 5:

[0706] The server sends the generated travel plan to the user. The user reviews the plan details on their device and requests specific conditions or changes as needed.

[0707] Step 6:

[0708] Upon receiving user feedback, the server regenerates the plan, taking the requested changes into account. The regenerated plan is immediately sent to the user for re-evaluation.

[0709] Step 7:

[0710] Once a user is satisfied with the final plan, they select the sharing option on their device, and the server generates a sharing link. The user then sends this link to the relevant parties via the communication network.

[0711] Step 8:

[0712] The server provides payment methods for cost sharing via an electronic payment service. Users make payments from their terminals, and the server checks each user's payment status and performs a final confirmation.

[0713] This process allows users to quickly and effectively create, share, and execute fully personalized travel plans.

[0714] (Example 1)

[0715] 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".

[0716] Planning a trip is a time-consuming and laborious process, requiring extensive information gathering and coordination. Travelers often find it difficult to quickly create an optimal travel plan while considering multiple factors such as destination, budget, and itinerary. Furthermore, there are numerous issues related to sharing travel plans, cost sharing, and payments, highlighting the need for efficient management systems.

[0717] 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.

[0718] This invention includes a server that receives requests from users regarding travel plans in natural language, analyzes those requests to extract necessary information, automatically generates a travel plan using generative artificial intelligence based on the extracted information and external information, and presents the generated travel plan to the user and can regenerate the plan based on user feedback. This enables users to quickly and efficiently create optimal travel plans and smoothly share them with other travel participants and share costs.

[0719] "Receiving information in natural language" refers to the process of inputting information using the language format that users use on a daily basis and converting it into a format that the computer system can understand.

[0720] "Analyzing requests" refers to the process of interpreting information received from users, extracting necessary information and keywords, and organizing them.

[0721] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to automatically generate new information and plans based on given data and conditions.

[0722] "Automatic generation" refers to the process in which a system makes its own decisions based on user requests and conditions, and creates the necessary plans and information.

[0723] "Regenerative capabilities" refer to a function that allows you to regenerate a plan or information once it has been created if there are any modifications or changes in conditions, thereby providing a new plan or information.

[0724] A "communication network" is a digital data transmission infrastructure used to share information with other users and systems.

[0725] "Electronic payment" is a method of conducting monetary transactions using digital technology, and it is a system that allows payments to be completed without using physical cash.

[0726] This invention is a system for efficiently planning travel. Users input travel requests through natural language prompts using a terminal. For example, a user might input, "I would like to travel to Tokyo next month. My budget is 100,000 yen per person, and I am thinking of a 3-night, 4-day trip." This request is immediately sent to the server.

[0727] The server uses natural language processing techniques to analyze user requests and extract keywords and information. A natural language processing framework (e.g., spaCy) is used for this analysis. The server also accesses external databases and APIs to collect external information such as destination weather, accommodation, and transportation options.

[0728] Next, the server utilizes a generative artificial intelligence model (e.g., OpenAI GPT) to automatically generate a travel plan by combining the user's requests with external information. This generated plan includes accommodations, activities, meals, transportation, and more. The generated plan is designed to be optimized for the user.

[0729] Users can review the travel plan generated through their device and request changes as needed. For example, if a user requests to change the hotel to a cheaper option, the server will regenerate and present a new plan that meets the user's requirements. This regeneration process allows for flexible planning tailored to the user's preferences.

[0730] The final plan can be shared with other travel participants via a communication network. Furthermore, the server provides electronic payment functionality to facilitate efficient cost sharing and payments among participants. This entire process makes travel planning quick and consistent, significantly reducing the user's workload.

[0731] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0732] Step 1:

[0733] The user accesses the chat interface using their device and enters prompts about their travel plans in natural language. For example, they might type, "I'd like to travel to Tokyo next month. My budget is 100,000 yen per person, and I'm thinking of a 3-night, 4-day trip." This input is sent to the server exactly as it was entered.

[0734] Step 2:

[0735] The server analyzes the prompt message received from the user using natural language processing technology. Here, the server uses "spaCy" to analyze the text and extract keywords such as destination, schedule, and budget. The keywords extracted from the input text data are then output as information used in the next processing step.

[0736] Step 3:

[0737] The server initiates access to external information sources based on keywords obtained from the analysis results. Specifically, it sends requests to weather information providers, accommodation databases, and transportation information APIs to obtain the latest information relevant to the user's travel plans. The input here is keyword data, and the output is the collected external information.

[0738] Step 4:

[0739] The server automatically generates travel plans using a generative AI model based on extracted keywords and collected external information. Using tools such as "OpenAI GPT," it creates a comprehensive plan including accommodation, activities, meals, and transportation based on the input data. As a result of the data processing performed by the generative AI, a travel plan optimized for the user is output.

[0740] Step 5:

[0741] The user reviews the travel plan displayed on the device and re-enters the information if changes are needed. For example, they might enter a request to "change the hotel to a slightly cheaper option." This re-entry is sent back to the server and used for further processing.

[0742] Step 6:

[0743] The server regenerates the travel plan based on user feedback. It incorporates the data used in the initial generation and the user's new requests to create a plan that better matches the user's needs. The AI ​​model is used again to output the updated travel plan.

[0744] Step 7:

[0745] The finalized plan is presented to the user via the terminal. The user can then share this final plan with other travel participants using the communication network and manage cost sharing through electronic payment functionality. The input is the finalized plan, and the output is a sharing link and payment information.

[0746] (Application Example 1)

[0747] 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".

[0748] There is a need to streamline people's travel and activity planning, automatically providing optimal plans that take environmental conditions and relevant information into account, thereby reducing user effort and improving the quality of travel and activities. However, traditional methods require the manual collection and integration of individual pieces of information, which is time-consuming and labor-intensive.

[0749] 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.

[0750] This invention includes a server that receives requests from users regarding travel and activity plans in natural language, analyzes those requests to extract necessary information, automatically generates travel and activity plans using artificial intelligence technology based on the extracted information and relevant external information, and makes the generated plans shareable with other users via communication means. This makes it possible to provide users with plans optimized for their needs and reduce the burden of information gathering and planning.

[0751] A "user" is an individual or group that intends to use the system to plan their travel and activities.

[0752] A "travel and activity plan" is a schedule of transportation methods and activities proposed based on the user's needs.

[0753] "Natural language" refers to the language that humans use on a daily basis, and is a means of inputting requests to a system in text format.

[0754] "Means for analyzing requests and extracting necessary information" refers to technologies that process information to identify meaningful keywords and information from input natural language.

[0755] "Means for automatically generating travel and activity plans using artificial intelligence technology" refers to AI technology that creates optimal plans by utilizing relevant patterns and data based on acquired information.

[0756] "External relevant information" refers to external data such as traffic conditions and weather that are referenced when generating plans.

[0757] "Communication means" refers to the network infrastructure used to send generated plans to other users.

[0758] "Means for sharing plans" refers to features that allow users to share their travel and activity plans with others.

[0759] A "payment method" is a way to share costs and manage the exchange of money between users.

[0760] An "electronic transaction service" is a system designed to facilitate the smooth exchange and payment of money conducted online.

[0761] The system that realizes this invention begins with the user inputting their travel and activity plan in natural language using a communication terminal such as a smartphone or computer. The user's input is sent to a server via the terminal. The server uses Python and natural language processing libraries to analyze this input and extract the necessary information.

[0762] The server then automatically generates travel and activity plans using a generative artificial intelligence model. At this stage, traffic and weather data obtained from external sources are incorporated to improve the accuracy and practicality of the generated plans.

[0763] Specifically, using AI frameworks such as TensorFlow and PyTorch, the system generates optimal travel and activity plans that match the user's conditions, based on acquired keywords and external data.

[0764] The generated plan is sent from the server to the user's device for review. The user can provide feedback as needed, and this information is sent back to the server, regenerating a new plan with the specified adjustments.

[0765] Furthermore, the system incorporates communication capabilities, allowing users to share generated plans with other users through a similar process. Additionally, electronic transaction services can be used to share costs and process payments related to shared plans.

[0766] For example, if a user inputs, "I want to plan a trip to a museum and lunch in Tokyo next Saturday," the system analyzes this input and suggests a plan that takes into account available transportation options and museum opening hours. Users can provide feedback such as, "I'd like to stop by a cafe after the museum," and the plan will be adjusted accordingly. Furthermore, this plan can be shared with family and friends, and expenses can be easily shared.

[0767] An example of a prompt sentence would be, "I'd like to plan my activities in the city center next Saturday. I plan to visit an art museum and then have lunch."

[0768] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0769] Step 1:

[0770] Users enter requests regarding travel and activity plans in natural language using a smartphone or computer terminal. The requests entered by the user (for example, "Visit a museum in the city center next Saturday, then have lunch") are sent to the server as text data.

[0771] Step 2:

[0772] The server parses the received request using Python and natural language processing libraries (e.g., NLTK and spaCy). It extracts keywords (e.g., "Saturday," "art museum," "lunch") from the input text data and processes the data to identify the user's request. The output of this process is data that represents the user's request as structured information.

[0773] Step 3:

[0774] The server uses extracted keywords and related external information (such as traffic conditions and weather data) as input to automatically generate travel and activity plans using a generative AI model (e.g., using TensorFlow or PyTorch). Specifically, it considers the relationships between each element, evaluates the options, and creates the optimal plan (e.g., a schedule including transportation and order of visits). The output is plan information optimized for the user.

[0775] Step 4:

[0776] The server generates a plan and sends it to the user's device. The device displays the received plan to the user through the application, allowing the user to review the plan's contents. Visual representations and detailed information about the plan are also provided.

[0777] Step 5:

[0778] The user reviews the plan and provides feedback as needed. For example, they might submit a modification request such as, "I'd like to change the lunch time to 2 PM." This feedback is then sent back to the server.

[0779] Step 6:

[0780] Based on the feedback received by the server, the AI ​​model is used again to regenerate the plan. The input is the user's feedback data, and the output is the adjusted new plan.

[0781] Step 7:

[0782] The final plan is shared by the user with other users. The server uses communication methods to distribute the generated plan link or data to other relevant users. The choice of communication tools and platforms is also considered here.

[0783] Step 8:

[0784] Users share the costs associated with the plan and complete the payment process through an electronic transaction service. This process integrates with a third-party payment service for payment confirmation and cost aggregation. The output is confirmation that the costs were processed smoothly.

[0785] 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.

[0786] This invention is configured as a system for efficiently and emotionally supporting users' travel planning. This system includes multiple means for analyzing natural language requests received from users, recognizing the user's emotional state using an emotion engine, and reflecting these in the generation of travel plans.

[0787] First, the user enters their travel plans and preferences in natural language via a chat interface on their device. This information is sent to the server. The server utilizes a natural language processing module to extract important keywords and emotional cues from the entered text.

[0788] Next, the emotion engine kicks in and analyzes the user's emotional state based on these clues. This analysis is then provided to the generative AI module, which automatically generates a travel plan that resonates with the user's emotions. For example, if the user is seeking relaxation, the system will prioritize activities and environments themed around healing, while if they prefer activities that stimulate their sense of adventure, it will suggest an active itinerary.

[0789] The generated travel plan is first presented to the user on their device, and the user can provide feedback based on the plan's content. This feedback also utilizes an emotion engine, which analyzes the user's emotional response to regenerate an even more optimal plan.

[0790] Furthermore, the final plan can be shared with other users via the communication network. Users receive a link to share this plan with other participants, making it easily accessible.

[0791] Furthermore, the server assists with cost sharing through electronic payment services and provides a mechanism for smooth payments between users. In this way, it supports the entire process up to the execution of the travel plan.

[0792] For example, if a user wishes to plan a relaxing weekend trip, the system analyzes their initial preferences and suggests a hot spring resort stay in a nature-rich tourist area. If the system analyzes that the user is experiencing stress, it will then suggest a plan that includes a quieter environment and a meditation experience to enhance the user's mental satisfaction. In this way, travel planning that incorporates the user's emotions enriches individual experiences.

[0793] The following describes the processing flow.

[0794] Step 1:

[0795] Users enter their travel preferences and detailed requirements on the device's chat interface. This includes destination, dates, budget, and purpose of travel (e.g., relaxation, adventure).

[0796] Step 2:

[0797] The terminal sends user input information to the server. The server processes this information using natural language processing technology to extract important keywords and phrases from the text. This reveals the user's specific wishes and requests.

[0798] Step 3:

[0799] The server activates an emotion engine to analyze emotional cues contained in the user's input text. Based on word choices and context, it determines the user's emotional state (e.g., tension, excitement, calmness).

[0800] Step 4:

[0801] The server automatically generates travel plans using a generation AI module based on extracted keywords and emotional states. In this process, it incorporates weather information and destination tourist information to provide suggestions that resonate with the user's emotions.

[0802] Step 5:

[0803] The generated travel plan is sent from the server to the user's device. The user can review the plan and provide feedback on the details. For example, they can make specific requests such as "I want to add more activities" or "I want to reduce the cost."

[0804] Step 6:

[0805] The server receives feedback from the user, performs sentiment analysis again using the sentiment engine, and incorporates the desired plan changes. As a result, it generates an improved plan incorporating the new conditions and provides it to the user again.

[0806] Step 7:

[0807] The plan that the user has finally approved can be shared with other travel participants via the communication network by selecting the sharing option through their device. The server generates a sharing link and sends it to the user.

[0808] Step 8:

[0809] The server manages expenses using electronic payment services and facilitates smooth cost sharing among participants. Users make payments on their terminals, and the server manages and monitors the overall payment status.

[0810] This process allows users to create customized travel plans that take emotions into account, and then share and execute those plans with all participants.

[0811] (Example 2)

[0812] 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".

[0813] In travel planning, conventional systems often fail to adequately consider the emotional needs of users, resulting in difficulty in providing highly satisfying travel plans. In particular, the inability to offer specific suggestions based on travel purpose and mood makes generating travel plans tailored to individual experiences a challenge. Furthermore, features such as travel plan sharing and cost sharing are insufficient, making smooth plan sharing among users difficult.

[0814] 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.

[0815] In this invention, the server includes means for receiving travel plan requests from users in natural language and extracting important clues, means for analyzing the user's emotional state based on the extracted clues, and means for automatically generating a travel plan that is tailored to the user's emotions based on the emotion analysis results and external information. This makes it possible to generate more personalized travel plans that are tailored to the user's emotions and wishes. Furthermore, payment adjustment means for sharing plans and sharing costs enable smooth plan sharing and payment among users.

[0816] "Natural language" refers to the language that users use on a daily basis and is used for requests and information input in systems.

[0817] "Clues" are important pieces of information extracted from user input, and they form the basis for sentiment analysis and plan generation.

[0818] "Emotional analysis" is a process that determines a user's emotional state based on their input and actions, and estimates their psychological needs.

[0819] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates travel plans tailored to the user.

[0820] A "travel plan" is a specific proposal of travel itinerary and activities based on the user's requests and emotional state.

[0821] A "communication line" is a communication network that enables data exchange between users and serves as the foundation for information sharing.

[0822] "Payment adjustment" is a method of managing payment procedures using electronic payments to fairly distribute the costs of a travel plan among users.

[0823] The embodiments for carrying out the present invention are described below.

[0824] As an example of this system, the user first uses their device to input their travel plans, preferences, and requirements in natural language. The entered information is then sent from the user to the server. The server uses existing platforms such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding as its natural language processing engine to extract important clues from the user's requests.

[0825] Next, the server performs sentiment analysis based on the clues. This analysis uses sentiment analysis capabilities such as Microsoft Azure Text Analytics to identify the user's psychological state. For example, it can determine whether the user is seeking relaxation or adventure.

[0826] Based on the analysis of the user's emotional state, the server uses a generative AI model to automatically create a travel plan that resonates with the user's feelings. One example of such an AI model is the OpenAI GPT model. The generated travel plan might include suggestions for resort destinations with abundant nature for a user seeking relaxation.

[0827] The generated plan is transferred to the device, where the user can review it and provide feedback. The server, upon receiving the feedback, performs another sentiment analysis and optimizes the plan as needed. Based on the feedback, elements such as "quiet environment" or "meditation experience" can be included.

[0828] Furthermore, the final travel plan can be easily shared with other users via a communication network. Users can use the provided link to share their plan with other devices and collaborate on planning.

[0829] Furthermore, the server coordinates payments for travel plans through its electronic payment functionality. Specifically, it can smoothly share costs among users using electronic payment platforms such as PayPal and Stripe.

[0830] As a concrete example, consider a scenario where a user enters "I want to go somewhere relaxing next weekend" as a prompt. The system then performs natural language analysis and, through sentiment analysis, suggests a relaxing travel plan. The user can then plan a more satisfying travel experience based on the suggested plan.

[0831] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0832] Step 1:

[0833] The user enters their travel plans and preferences in natural language on their device. This input data is sent to the server in text format. For example, the user might enter the prompt, "I'm looking for a relaxing beach resort."

[0834] Step 2:

[0835] The server analyzes the received natural language data using a natural language processing engine to extract important keywords and clues. Keywords such as "relax," "beach," and "resort" are extracted from the input text. The Google Cloud Natural Language API may be used at this stage.

[0836] Step 3:

[0837] Based on the extracted clues, the server uses an emotion analysis engine to analyze the user's emotional state. The data analysis determines that the user's emotional state is "wanting to relax." For example, Microsoft Azure Text Analytics might be used at this stage.

[0838] Step 4:

[0839] The server automatically generates personalized travel plans for users based on sentiment data and keywords through a generative AI model. Here, the generative AI model processes the information obtained in the previous stage to create itinerary suggestions, including a list of suitable beach resorts. OpenAI GPT models, among others, may be used in this process.

[0840] Step 5:

[0841] The generated travel plan is printed on the device and presented to the user. The user can review the plan and provide feedback as needed. For example, the user might comment, "I'd like to add a few more activities."

[0842] Step 6:

[0843] The server receives user feedback, performs sentiment analysis again, and regenerates a more suitable plan. It incorporates the feedback as data and optimizes the initial plan, such as adding new activities.

[0844] Step 7:

[0845] The final travel plan generates a link that can be shared with other users via a communication network. Users can use this link to share their plans with friends and family. Specifically, the generated link can be sent via email or messaging apps.

[0846] Step 8:

[0847] The server utilizes an electronic payment platform to coordinate payments for travel plans and manage cost sharing among users. Specifically, it uses services like PayPal and Stripe to ensure that accommodation and transportation costs are fairly shared among participants.

[0848] (Application Example 2)

[0849] 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".

[0850] Traditional travel planning often struggled to reflect users' emotions and individual preferences, resulting in generic suggestions. Furthermore, the process of sharing travel plans and costs with others was complex and inconvenient. The lack of personalized travel plan suggestions hindered user satisfaction.

[0851] 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.

[0852] This invention includes a server that receives travel planning requests from users in natural language, analyzes those requests to extract necessary information, automatically generates a travel schedule using generative artificial intelligence based on the extracted information and external information, and presents the generated travel schedule to the user and can regenerate the schedule based on the user's evaluation. This enables the creation of flexible travel plans that are tailored to the user's emotions and individual preferences, as well as the efficient sharing of costs.

[0853] A "user" is an individual or group that uses the system to receive travel plan suggestions.

[0854] "Travel plan requests" refer to information that indicates the user's travel preferences and conditions that they want the system to meet.

[0855] "Natural language" refers to the language that humans use on a daily basis, expressed through text or speech.

[0856] "Means of extracting information" refers to methods for extracting specific keywords and important elements from user requests.

[0857] "External information" refers to data other than what the user requested that is used to suggest travel plans, and includes, for example, information about weather and traffic conditions.

[0858] "Generative artificial intelligence" is an artificial intelligence technology that generates appropriate travel schedules based on user requests and external information.

[0859] "Methods for automatically generating travel schedules" refers to methods that use artificial intelligence to create travel plans tailored to the user's preferences.

[0860] "Means of presenting to the user" refers to methods of providing the generated travel plan in a way that allows the user to visually confirm it.

[0861] "User ratings" refer to users' opinions and feedback on the presented travel plans.

[0862] "Methods for regenerating schedules" refer to methods for redesigning travel plans based on user feedback.

[0863] A "communication data network" is a network system used to share information with other users.

[0864] "Users" refers to other individuals or groups who view or share the generated travel schedule.

[0865] A "payment method for sharing expenses" refers to a method for efficiently sharing and paying for travel-related expenses among users.

[0866] The system for implementing this invention begins with a user inputting a travel plan request in natural language via a smartphone. This information is sent to a cloud-based server, where the request is analyzed using a natural language processing module. During the analysis, the server uses natural language processing software, such as Google Bard or OpenAI's GPT model, to extract keywords and sentiment cues from the information obtained from the user.

[0867] Next, the emotion recognition engine analyzes the user's emotional state and provides the results to the generative artificial intelligence module. This module utilizes a generative AI model to generate a personalized travel schedule based on the user's emotions and expectations. The generated schedule is presented to the user on their device, allowing them to intuitively review its contents.

[0868] When a user provides feedback on the schedule, the server re-analyzes the feedback and regenerates the schedule to optimize it. The regenerated schedule is then presented to the user via their smartphone.

[0869] Furthermore, the terminal has the function to share the generated schedule with other users via the communication data network. Regarding the shared schedule, electronic payment technology is used to facilitate the smooth sharing of costs among users.

[0870] For example, if a user inputs "I want to visit a place where I can refresh myself in a quiet natural setting on the weekend," the system can grasp the user's desire for refreshment and suggest a travel schedule that includes visits to quiet parks and hot spring facilities. An example of a prompt to the generative AI model used in this case would be, "Please tell me how to spend a weekend refreshing myself in a quiet natural setting."

[0871] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0872] Step 1:

[0873] The user uses a terminal to input travel plan requests in natural language. The input is sent to the server as text data. During this process, the terminal uses a text editor or voice input function to collect specific details about the user's preferences.

[0874] Step 2:

[0875] The server passes the received text data to a natural language processing module. Here, the server extracts important keywords and sentiment cues from the text, for example, using an OpenAI GPT model. The input is natural language text, and the output is keyword and sentiment information. This information is later provided to the sentiment engine.

[0876] Step 3:

[0877] The server uses an emotion engine to analyze the emotion information obtained in step 2. Here, the user's emotional state is evaluated in detail, and necessary data processing is performed. The input is emotion information, and the output is data about the specific emotional state. This data is provided to the generative artificial intelligence module.

[0878] Step 4:

[0879] The server uses a generative artificial intelligence module to generate a travel schedule based on the user's emotional state and requests. It utilizes a generative AI model to perform data calculations, including prompts. The input is the emotional and request data analyzed in step 3, and the output is a travel schedule plan.

[0880] Step 5:

[0881] The generated travel schedule is sent to the terminal and presented to the user. The terminal uses a GUI (Graphical User Interface) to visually display the schedule. The input is the generated travel schedule data, and the output is a user-friendly schedule display.

[0882] Step 6:

[0883] The user provides feedback on the presented schedule. This information is then sent back to the server via the device. The feedback is analyzed for sentiment and converted into data that represents specific improvement requests.

[0884] Step 7:

[0885] The server repeats the process in step 4 to regenerate the travel schedule based on user feedback. During this process, the feedback is re-evaluated by the generating AI model, and an optimized plan is created. The input is the feedback data, and the output is the regenerated travel schedule.

[0886] Step 8:

[0887] The final travel schedule is provided to the device in a format that can be shared with other users via a communication data network. The device uses a sharing link generation function to easily share the schedule with other users. The input is the final schedule data, and the output is a shareable link.

[0888] Step 9:

[0889] The server uses electronic payment functionality to streamline the sharing of travel expenses. Expense payments between users are automatically coordinated using electronic payment technology. Inputs are user information and expense data, and output is the transaction result with expenses already shared.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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."

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0911] The following is further disclosed regarding the embodiments described above.

[0912] (Claim 1)

[0913] A means of receiving travel planning requests from users in natural language, analyzing those requests, and extracting necessary keywords,

[0914] A means of automatically generating travel plans using artificial intelligence based on extracted keywords and external information,

[0915] A means to present a generated travel plan to the user and to regenerate the plan based on user feedback,

[0916] A means to make the generated plan shareable with other users via a communication network,

[0917] A system that includes payment methods for sharing the cost of a shared plan with other users.

[0918] (Claim 2)

[0919] The system according to claim 1, comprising means for incorporating weather information into the analysis of user requests and providing activity and clothing suggestions suitable for travel plans.

[0920] (Claim 3)

[0921] The system according to claim 1, wherein the payment means includes means for sharing costs and facilitating payments between users using an electronic payment service.

[0922] "Example 1"

[0923] (Claim 1)

[0924] A means of receiving travel planning requests from users in natural language, analyzing those requests, and extracting the necessary information,

[0925] A means of automatically generating a travel plan using artificial intelligence based on extracted information and external information,

[0926] A means to present a generated travel plan to the user and to regenerate the plan based on user feedback,

[0927] A means to make the regenerated plan shareable with other users via a communication network,

[0928] A system that includes electronic payment methods for sharing and paying for the costs of a shared plan with other users.

[0929] (Claim 2)

[0930] The system according to claim 1, comprising means for incorporating environmental information into the analysis of user requests and providing activity and clothing suggestions suitable for travel planning.

[0931] (Claim 3)

[0932] The system according to claim 1, wherein the electronic payment means includes means for sharing costs using a digital transaction service and for streamlining payments between users.

[0933] "Application Example 1"

[0934] (Claim 1)

[0935] A means for receiving requests from users regarding travel and activity plans in natural language, and for analyzing those requests to extract necessary information,

[0936] A means for automatically generating travel and activity plans using artificial intelligence technology based on extracted information and externally relevant information,

[0937] A means of presenting the generated plan to the user and allowing the plan to be modified based on user feedback,

[0938] A means to make the generated plan shareable with other users via communication means,

[0939] A system that includes payment methods for sharing the cost of a shared plan among other users.

[0940] (Claim 2)

[0941] The system according to claim 1, comprising means for incorporating environmental information into user request analysis and making suggestions suitable for travel and activity plans.

[0942] (Claim 3)

[0943] The system according to claim 1, wherein the payment means includes means for sharing costs and facilitating payments between users using an electronic transaction service.

[0944] "Example 2 of combining an emotion engine"

[0945] (Claim 1)

[0946] A means of receiving travel planning requests from users in natural language, analyzing those requests, and extracting important clues.

[0947] An emotion analysis method for analyzing the user's emotional state based on extracted clues,

[0948] A means of automatically generating a travel plan that is tailored to the user's emotions using generative artificial intelligence based on emotion analysis results and external information,

[0949] A means of presenting the generated travel plan to the user on the device and regenerating the plan based on user feedback,

[0950] A means to make the generated plan shareable with other users via a communication line,

[0951] A system that includes payment adjustment mechanisms for sharing the cost of a shared plan among users.

[0952] (Claim 2)

[0953] The system according to claim 1, comprising means for incorporating weather information into the analysis of user requests and providing activity and clothing suggestions suitable for a travel plan.

[0954] (Claim 3)

[0955] The system according to claim 1, wherein the payment adjustment means includes means for sharing costs using electronic payment means and facilitating payments among users.

[0956] "Application example 2 when combining with an emotional engine"

[0957] (Claim 1)

[0958] A means of receiving travel planning requests from users in natural language, analyzing those requests, and extracting the necessary information,

[0959] A means of automatically generating a travel schedule using artificial intelligence based on extracted and external information,

[0960] A means to present a generated travel schedule to the user and to regenerate the schedule based on the user's evaluation,

[0961] A means to make the generated schedule shareable with other users via a communication data network,

[0962] A system that includes a payment method for sharing and paying for the costs of a shared schedule with other users.

[0963] (Claim 2)

[0964] The system according to claim 1, comprising means for incorporating environmental information into user request analysis and providing activity and clothing suggestions suitable for the travel schedule.

[0965] (Claim 3)

[0966] The system according to claim 1, wherein the payment means includes means for sharing costs and facilitating payments between users using electronic payment technology. [Explanation of Symbols]

[0967] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving requests from users regarding travel and activity plans in natural language, and for analyzing those requests to extract necessary information, A means for automatically generating travel and activity plans using artificial intelligence technology based on extracted information and externally relevant information, A means of presenting the generated plan to the user and allowing the plan to be modified based on user feedback, A means to make the generated plan shareable with other users via communication means, A system that includes payment methods for sharing the cost of a shared plan among other users.

2. The system according to claim 1, comprising means for incorporating environmental information into the analysis of user requests and making suggestions suitable for travel and activity plans.

3. The system according to claim 1, wherein the payment means includes means for sharing costs and facilitating payments between users using an electronic transaction service.

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