system

Abstract

We provide the system. [Solution] An input means for receiving travel requirements from the user, Information gathering means that obtain data from external sources based on received travel requirements, A plan generation means that analyzes acquired data and generates multiple travel plans to provide to the user, A selection method in which the user makes a choice from the generated travel plan, A booking method that allows you to make various reservations in one go based on the selected travel plan, A notification method to inform the user that the reservation has been completed, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When making a travel plan, a traveler has to individually collect information such as transportation, accommodation, and activities from multiple websites and platforms, which is very time-consuming and inefficient. In addition, since the information displayed on each site is different, it is difficult to make an optimal choice. Furthermore, even after a travel plan is determined, its reservation has to be made manually, which may result in mistakes and time loss.

Means for Solving the Problems

[0005] To solve the above problems, the present invention includes an information gathering means that receives travel requirements from a user and acquires data from external sources based on those requirements. It also includes a plan generation means that generates multiple travel plans based on the acquired data and proposes plans in a format that is easy for the user to use. Furthermore, it provides a reservation means that allows the user to make reservations for transportation, accommodation, and activities all at once based on the travel plan selected by the user, and notifies the user of the reservation completion information, thereby providing a system that streamlines the process from planning to reservation completion.

[0006] A "user" refers to a traveler who plans a trip and makes reservations.

[0007] "Travel requirements" refer to the desired conditions that users specify when planning a trip, such as the departure point, destination, number of travel days, budget, and activities.

[0008] "Input method" refers to the interface or device that allows users to input their travel requirements into the system.

[0009] "Information gathering means" refers to a component of a system that has the function of acquiring travel-related data from external information sources.

[0010] "External information sources" refer to websites and APIs that provide information on transportation, accommodations, activities, and other related topics.

[0011] The "plan generation means" refers to the part of the system that generates travel plans to propose to users using the collected data.

[0012] A "selection method" refers to an interface that provides a function allowing users to choose any travel plan from those presented.

[0013] A "booking method" is a system component that allows for the simultaneous booking of all necessary reservations based on the selected travel plan.

[0014] A "notification method" refers to a function that communicates completed reservation information and confirmations to the user. [Brief explanation of the drawing]

[0015] [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention provides a system for users to efficiently plan their trips. Users input their travel requirements on a terminal, and the entered information is sent to a server. The server collects necessary data from external sources and generates an optimal travel plan. This plan generation process creates multiple options based on information about transportation, accommodation, and activities, taking into account price, convenience, and user preferences.

[0037] The generated plans are presented to the user via the device, and the user selects the plan that best matches their preferences. This selected plan information is then sent back to the server, which uses this information to make various reservations in bulk. This includes booking transportation, hotels, and activities.

[0038] Once a reservation is complete, the server confirms the reservation details and sends a notification to the user's device. The user can then review this reservation information through the device and make changes or cancellations as needed. In this way, this embodiment significantly reduces the complexity of travel planning for users and enables efficient travel arrangements.

[0039] For example, if a user enters a request such as, "I want to plan a 3-day trip from Osaka to Sapporo, where I can enjoy sightseeing and local cuisine," the server will generate a plan by optimally combining flights, hotels, sightseeing tours, and restaurant reservations. Once the user completes their selections, all arrangements are made automatically, and a notification is sent to their device, allowing the user to enjoy their trip with peace of mind.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user enters their travel requirements. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and desired activities. Once the user enters this information, the terminal collects the data and sends it to the server.

[0043] Step 2:

[0044] The server collects data from external sources based on the received travel requirements. It sends API requests to transportation databases, accommodation booking sites, activity information sites, and other similar resources. The collected information is then organized to be used as material for generating travel plans.

[0045] Step 3:

[0046] The server uses collected data and a generative AI model to generate multiple travel plans to suggest to the user. These plans are scored and optimized based on price, convenience, and user preferences.

[0047] Step 4:

[0048] The terminal displays a list of travel plan options sent from the server to the user. The user reviews the displayed plans and selects the one that best suits their preferences, considering the travel dates, details, and price.

[0049] Step 5:

[0050] The user sends the selected plan information from their device to the server. Based on the selected plan, the server automatically makes reservations for various modes of transportation, accommodations, and activities in a single batch.

[0051] Step 6:

[0052] After all reservations are complete, the server generates a reservation confirmation and detailed information and sends it to the user's device. The user can then check the reservation details on the device to ensure there are no problems.

[0053] (Example 1)

[0054] 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."

[0055] Conventional travel planning systems require users to research multiple sources and make reservations individually, which is extremely time-consuming and cumbersome. Furthermore, it is difficult to present optimal options quickly during travel planning, making it challenging to improve user satisfaction. This invention aims to solve the problem of efficiently generating optimal travel plans tailored to diverse travel requirements and automatically executing all necessary arrangements in a user-friendly manner.

[0056] 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.

[0057] In this invention, the server includes means for acquiring information from an external data source based on received travel requirements, means for generating multiple travel plans using a generative AI model, and means for executing various arrangements in a batch based on the travel plan selected by the user. This allows the user to centrally and efficiently acquire all the information necessary for their itinerary and easily utilize an optimized travel plan.

[0058] A "terminal device" is a device used by a user to input travel requirements and send that information to a server.

[0059] A "server system" is a computer system that retrieves relevant information from an external data source based on travel requirements received from a user.

[0060] The "plan generation method" is a function that analyzes acquired information and generates multiple travel plans to provide to the user using a generation AI model.

[0061] "Interface means" refers to a user interface that allows users to make selections from generated travel plans.

[0062] A "booking system" is a system that allows for the simultaneous execution of all necessary arrangements based on the selected travel plan.

[0063] "Communication means" refers to a communication function used to notify the user that arrangements have been completed.

[0064] "External data sources" refer to external systems and services used to obtain information such as transportation, accommodation, and activities.

[0065] "Generative AI models" refer to artificial intelligence technology used to generate optimal travel plans based on diverse travel requirements.

[0066] This invention is an information processing system aimed at improving the efficiency of travel planning, and consists of the following elements.

[0067] First, the user uses a device to enter their travel requirements. This device can be any device capable of inputting information, such as a computer, smartphone, or tablet. The device provides an interface for the user to input information such as their departure point, destination, travel duration, activities, and budget.

[0068] The terminal sends this entered information to the server. The server accesses external data sources via the information and communication network to collect data on transportation, accommodation, and activities. This includes utilizing external APIs and web services. For example, it may obtain flight information from airline APIs or accommodation information from hotel booking website APIs.

[0069] Subsequently, the server analyzes the collected data using a generative AI model and generates multiple travel plans for the user. The generative AI model has the ability to create multiple optimized plans that take into account the user's preferences and constraints. The generated plans offer a variety of options based on price, time efficiency, and the user's intended use, providing the best choice.

[0070] As a concrete example, suppose a user enters the prompt message, "I want to visit a resort with my family on the weekend two weeks from now and enjoy local activities." Based on this request, the server generates a travel plan combining family-friendly transportation, suitable accommodations, and popular activities. This information is presented to the user via the terminal, allowing the user to select the most suitable plan.

[0071] When a user selects a travel plan, the device sends that information to the server, which then executes all necessary arrangements based on the selected plan. This includes booking flights, accommodations, and activities. After the bookings are complete, the server verifies the details and sends a notification to the device, providing the user with the necessary information. This entire process allows users to plan and execute their trips efficiently and without hassle.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user enters their travel requirements using a terminal. The terminal receives input such as departure point, destination, travel duration, budget, and activities. This data is formatted as overall foundational information for travel planning and sent to the server.

[0075] Step 2:

[0076] The terminal sends the entered travel requirements to the server. The server receives this data and prepares requests to retrieve data from the necessary external sources. This process involves constructing and sending API requests.

[0077] Step 3:

[0078] The server collects necessary information from external data sources. The server accesses each external data source to retrieve information on transportation, accommodation, and activities. Specifically, it obtains flight information from airline APIs and hotel information from accommodation booking site APIs, and stores this information in a database.

[0079] Step 4:

[0080] The server generates travel plans using a generative AI model. The server inputs collected data into the generative AI model and creates multiple travel plans to suggest to the user based on this data. The data calculations performed include price comparison, duration calculation, and matching with the user's preferences. The generated plans are then adjusted to each have distinct characteristics.

[0081] Step 5:

[0082] The server generates travel plans and sends them to the device. The device then displays these plans for the user to view. The user can review each plan and select the one that best suits their needs.

[0083] Step 6:

[0084] The user selects the optimal travel plan and sends that information to the server using their device. The server receives this selection information and prepares the data for the next step.

[0085] Step 7:

[0086] The server handles all arrangements based on the selected travel plan. The server sends the details of the selected plan to each service provider via API, completing bookings for flights, hotels, and activities. This includes booking confirmation and payment processing.

[0087] Step 8:

[0088] The server notifies the terminal of the booking completion information. The terminal displays this information to the user, providing options for confirming the booking details and making changes or cancellations as needed. The user can then proceed with their travel preparations with peace of mind.

[0089] (Application Example 1)

[0090] 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."

[0091] Traditional travel planning systems required users to make individual bookings separately, making it difficult to efficiently integrate the entire plan. Furthermore, creating optimal travel plans tailored to user needs was challenging, making travel planning a very time-consuming and laborious task. Additionally, they lacked sufficient intuitive voice-activated operation and the provision of virtual travel experiences utilizing modern technology.

[0092] 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.

[0093] In this invention, the server includes a data input device that receives travel requirements from a user, an information gathering device that acquires information from external sources based on the received travel requirements, and a plan generation device that analyzes the acquired information and generates multiple travel plans to present to the user. This enables the creation of intuitive travel plans using voice input and allows for the provision of more convenient travel plans utilizing natural language processing.

[0094] A "data input device" is a device that has the function of receiving travel conditions and requests from users and processing them within the system.

[0095] An "information gathering device" is a device that acquires necessary data from external sources based on the received travel requirements.

[0096] A "plan generation device" is a device that analyzes collected data and creates and presents the optimal travel plan to the user.

[0097] A "selection device" is a device that allows a user to choose their preferred travel plan from among the travel plans presented.

[0098] A "reservation device" is a device that allows users to make various reservations, such as for transportation and accommodation, all at once, based on the travel plan they have selected.

[0099] A "communication device" is a device used to notify the user that their reservation has been completed.

[0100] An "input support device" is a device that receives the user's travel requirements through voice input and then performs natural language processing on them.

[0101] An "optimization algorithm" is a computational method used to evaluate and rank travel plans and select the most suitable one.

[0102] A "generative AI model" is a model that uses artificial intelligence technology to generate the optimal travel plan for a user.

[0103] The system for carrying out the present invention comprises a user, a terminal, and a server. The user uses a terminal such as a smartphone or smart glasses to input travel preferences and requirements in voice or text. On the terminal, voice recognition technology, such as Google® Cloud Speech-to-Text API, is used to convert the voice data into text data. This text data is analyzed using natural language processing technology and sent to the server as travel requirements.

[0104] The server retrieves necessary information from external sources (such as the internet or databases provided by partner companies) based on the received travel requirements. Cloud services, such as Google Cloud Platform, are utilized for this information retrieval. The collected information is analyzed by optimization algorithms and generative AI models to generate an optimal travel plan tailored to the user's needs. This AI model proposes plans that match the user's preferences, budget, and schedule.

[0105] The travel plan, returned to the device, is presented to the user. The user selects their preferred plan from the multiple options presented. The details of the selected plan are sent back to the server, which then makes reservations for transportation, accommodation, and activities all at once. After the reservations are complete, the server notifies the device of the details.

[0106] For example, if a user enters a request such as, "I want to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," the system will generate a plan combining the best Shinkansen (bullet train) times, highly-rated Japanese restaurants, and hotel information. Based on the plan approved by the user, the reservation is automatically completed, and a notification is sent to the device. An example of a prompt message would be, "Please suggest a relaxing hot spring trip plan. My budget is under 100,000 yen, I want a three-night, four-day stay, and preferably a Japanese-style inn."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] Users input their travel preferences and requirements using their smartphones or smart glasses via voice or text. The system utilizes speech recognition technology to convert voice data into text. For example, if a user says, "I'd like to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," that text will appear on the device.

[0110] Step 2:

[0111] The terminal sends the converted text data to the server. The server analyzes the received text data using NLP (Natural Language Processing), a natural language processing technique, and understands it as travel requirements. Specifically, it extracts keywords such as "Tokyo," "Kyoto," "2 days," and "Japanese food" from the text.

[0112] Step 3:

[0113] The server collects relevant information from external sources based on the user's travel requirements. This information gathering utilizes the internet and partner databases via APIs. Specifically, this step retrieves information such as Shinkansen (bullet train) schedules, highly-rated Japanese restaurants, and accommodation availability.

[0114] Step 4:

[0115] The server generates multiple travel plans using optimization algorithms and generative AI models based on the collected information. As part of the data processing, it evaluates and ranks the plans based on the user's budget and schedule. Specifically, it lists the best plans that fit within the budget.

[0116] Step 5:

[0117] The device presents the user with proposed plans sent from the server. The user selects their preferred plan from the multiple options displayed on the device. Specifically, the user taps to indicate "This plan is good."

[0118] Step 6:

[0119] The selected travel plan information is sent to the server, which then makes bulk reservations for transportation and accommodation based on that information. Specifically, it accesses partner reservation services via API and automatically confirms the necessary reservations.

[0120] Step 7:

[0121] The server confirms that all reservations are complete and notifies the terminal of this completion. Users can then check the reservation details on their terminal to ensure there are no issues. Specifically, a reservation success message and detailed information will be displayed on a particular screen.

[0122] Step 8:

[0123] Users can change or cancel their reservations as needed. Actions taken on the device send a request to the server, which then processes the reservation change. For example, canceling a plan is done through a similar process.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention is a system that not only efficiently plans trips but also takes user emotions into account to provide a more personalized travel experience. The system includes a terminal interface for inputting travel requirements, a server-based information gathering and plan generation function, and an emotion engine to assist with plan selection and booking arrangements.

[0126] First, the user enters their travel requirements via a device. This information includes departure point, destination, travel duration, budget, and desired activities. The device then organizes this information and sends it to the server.

[0127] Based on the received requirements, the server collects the necessary data from external sources. After data collection, the plan generation function on the server generates multiple travel plans using an optimization algorithm and ranks them. A distinctive feature here is the use of an emotion engine; the server recognizes the user's emotions and reflects the results in plan generation, providing plans that match the traveler's mood and preferences.

[0128] For example, if a user expresses a desire to "relieve stress," the emotion engine can generate a plan that prioritizes activities with high relaxation and refreshing effects, as well as accommodations in lush, green spaces. The user's emotional information is derived from user input and, if necessary, other data obtained from the device.

[0129] Users select the plan that best suits them from the available options via their device. After selection, the server automatically arranges all necessary reservations based on the chosen plan. Once the reservations are complete, the server notifies the user, displaying the reservation details on their device. This emotionally conscious process not only reduces the hassle of travel arrangements but also enriches the user experience, making it more satisfying.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] The user enters their travel requirements using a terminal. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and activities. After the user enters this information, the terminal organizes the data and sends it to the server.

[0133] Step 2:

[0134] The server collects relevant data from external sources based on the received travel requirements. Specifically, it obtains information using APIs from databases and booking sites related to flights, hotels, and tourist activities.

[0135] Step 3:

[0136] The device generates emotional data using input and, if necessary, sensor data to understand the user's emotional state. This data is sent to a server.

[0137] Step 4:

[0138] The server combines collected data with user sentiment data and generates multiple travel plans using a generative AI model. The plans are evaluated and ranked using an optimization algorithm that takes user sentiment into account. At this stage, the sentiment engine prioritizes plans that match the user's mood.

[0139] Step 5:

[0140] A travel plan generated on the device is sent from the server, and the user reviews it and selects the most preferred plan. The plan includes detailed information such as price, schedule, and accommodation information.

[0141] Step 6:

[0142] The user sends their selected travel plan to the server. Based on this selection, the server makes various reservations in a single batch (e.g., transportation tickets, hotel rooms, activity bookings).

[0143] Step 7:

[0144] Once all reservations are confirmed, the server generates a reservation confirmation and sends it to the user's device. The user then reviews the reservation details on their device, completing their travel plan.

[0145] (Example 2)

[0146] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0147] Conventional travel planning systems have struggled to provide travel plans that adequately consider users' emotions and individual needs, resulting in insufficient user satisfaction. Furthermore, the booking process after selecting a travel plan is often cumbersome, requiring considerable time and effort from the user. To address these issues, there is a need for a system that generates travel plans that take emotions into account and enables efficient booking procedures.

[0148] 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.

[0149] In this invention, the server includes an interface means for receiving travel-related information from the user, an emotion analysis means for analyzing the user's emotional state and reflecting it in the travel plan, and a travel plan generation means for generating a travel plan using optimization technology. This makes it possible to provide personalized travel plans that take into account the user's individual emotions and needs, and to efficiently arrange reservations based on the selected travel plan.

[0150] "Interface means" refers to a device or software through which a user inputs travel-related information, and through which that information is transmitted to a server.

[0151] "Data acquisition means" refers to a device or method for collecting necessary data from external sources based on information received from the user.

[0152] A "travel plan generation means" is a device or software that analyzes acquired data and creates multiple optimized travel plans according to the user's requirements.

[0153] "Selection method" refers to a method or apparatus for a user to select their preferred travel plan from the generated travel plans.

[0154] A "booking arrangement device" is a device or system that automatically performs the necessary booking procedures based on the travel plan selected by the user.

[0155] "Communication means" refers to a method or system for transmitting information to the user, such as the completion of a reservation procedure.

[0156] "Emotional analysis means" refers to a technology or device that analyzes data related to a user's emotions and reflects the results in travel plans.

[0157] The system of this invention aims to provide personalized travel plans by taking into account the user's emotions and individual needs in travel planning. An embodiment thereof is shown below.

[0158] First, the user enters travel information using a device. This device can be a smartphone or a computer, and is accessible via a dedicated application or web interface. The user enters their departure point, destination, travel duration, budget, and desired activities. This information is compiled through the interface and sent to the server.

[0159] The server uses data acquisition methods based on information received from the terminal to collect necessary information through the internet and travel-related databases. External information includes accommodation, transportation, and tourist destination information, and data is acquired in real time using APIs.

[0160] Based on the acquired information, the server activates an emotion analysis system. This involves a process that uses natural language processing technology to analyze the user's input information to determine their emotions. For example, if the user inputs "I want to relax," the emotion analysis will recommend activities to reduce stress.

[0161] Subsequently, the server uses a travel plan generation mechanism and optimization techniques (e.g., genetic algorithms) to create multiple travel plans that match the user's requests. The generated travel plans are sent to the terminal in a visually easy-to-understand format, allowing the user to select one.

[0162] For example, if the prompt is "I want to get away from the hustle and bustle of the city," sentiment analysis will generate a plan that prioritizes quiet travel destinations surrounded by nature. A more specific example of a prompt would be, "Please create a travel plan that meets the following conditions: departure point is Tokyo, destination is a place surrounded by nature, travel duration is 3 days, budget is under 100,000 yen, and relaxing activities are prioritized."

[0163] Ultimately, the user selects the most suitable travel plan from the provided options. The server then automatically makes the necessary booking arrangements based on the selected travel plan using booking tools. This allows the user to prepare for their trip with minimal stress.

[0164] The above describes a specific embodiment for implementing this invention. By providing travel plans that take into account the user's emotions, a more personalized experience is realized, thereby improving user satisfaction.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] Users enter travel information using their device. This information includes departure point, destination, travel duration, budget, and desired activities. This information is entered intuitively using forms and selection menus on the device screen. This input data is then prepared to be sent to the server in a structured format (e.g., JSON).

[0168] Step 2:

[0169] The terminal receives user input data, organizes it, and sends it to the server. Here, the data is encrypted using the HTTPS protocol to ensure security. The data sent to the server includes all travel requirements entered by the user.

[0170] Step 3:

[0171] The server receives user travel information sent from the terminal. Based on this information, it uses data acquisition methods to collect necessary external data from the internet and travel-related databases. Specifically, the server issues API requests, retrieves response data in real time, and stores it. The collected data includes information on accommodations and tourist attractions at the travel destination.

[0172] Step 4:

[0173] The server uses the collected data and user input to activate the sentiment analysis system. Here, natural language processing techniques are used to analyze the user's emotions. Based on the input (e.g., "I want to relax"), the system identifies the user's emotional state and prepares the results for use in the next step.

[0174] Step 5:

[0175] The server drives the travel plan generation mechanism using the results of sentiment analysis and collected data. It utilizes a generative AI model to process input data using an optimization algorithm (e.g., a genetic algorithm) and generate multiple travel plans. Each generated travel plan is adjusted to match the user's identified emotional state and then ranked.

[0176] Step 6:

[0177] The server sends the generated travel plan to the device. The device displays the travel plan to the user in a visually easy-to-understand format (e.g., map or schedule). At this time, the device presents the travel plan with a user interface designed to allow the user to easily compare and select options.

[0178] Step 7:

[0179] The user selects their preferred travel plan from those presented on the device. The information of the selected travel plan is then sent back to the server. If a selection is made at this stage, preparations for the next steps proceed based on that travel plan.

[0180] Step 8:

[0181] The server activates the booking system based on the selected travel plan and automatically makes the necessary bookings. At this stage, the server collaborates with external systems to make reservations for accommodations and activities. Booking information is recorded for later notifications.

[0182] Step 9:

[0183] After the server confirms the completion of the reservation, it sends the details to the device. The device then displays the details of the completed reservation to the user. At this time, detailed information is provided via confirmation email or in-app notification to give the user peace of mind.

[0184] (Application Example 2)

[0185] 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".

[0186] Traditional recommendation systems have struggled to provide personalized services that cater to users' emotions and individual needs. As a result, users often feel that the products and services offered do not suit their mood or circumstances, leading to decreased satisfaction.

[0187] 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.

[0188] In this invention, the server includes input means for receiving requirements from the user, information gathering means for acquiring data from external information sources, and sentiment analysis means for reflecting the user's emotions in plan generation. This makes it possible to provide personalized plans based on the user's emotions.

[0189] An "input means" is a device or interface for receiving requirements or instructions from the user.

[0190] "Information gathering means" refers to the processes and functions for obtaining necessary data from external databases and information sources.

[0191] The "plan generation method" is a function that creates multiple recommended plans to provide to the user based on the acquired data.

[0192] "Selection method" refers to an interface or function that allows a user to choose the plan they want from the options provided.

[0193] "Arrangement method" refers to the process or function of making arrangements such as reservations and orders based on the selected plan, all in one go.

[0194] "Notification means" refers to methods or functions for informing the user of the information once the arrangements have been completed.

[0195] "Emotional analysis tools" refer to technologies and functions that recognize a user's emotions and reflect them in plan generation.

[0196] This invention is a system that provides personalized recommendation plans that take user emotions into consideration. The system mainly consists of a server and user terminals.

[0197] The server will be implemented using Python or other programming languages. Sentiment analysis will utilize sentiment analysis libraries (e.g., TextBlob, Natural Language Toolkit). The system will include data collection mechanisms to gather data from external sources and generate plans based on user input.

[0198] The user terminal functions as a smartphone or tablet, where the user enters their requirements. When the user enters a specific situation or mood, that data is sent to the server. The server analyzes this information using sentiment analysis tools and generates an appropriate plan based on the user's emotions.

[0199] The generated plan is notified to the user's terminal, and the user can select it. After selection, the server makes all relevant arrangements via the arrangement mechanism and notifies the user of the completed information via the notification mechanism.

[0200] For example, if a user enters "I want to relax today," the server will collect relevant data and generate prompts suggesting items and activities with relaxation effects. For instance, the generating AI model can be run using a prompt such as, "Suggest the best products based on the emotion entered by the user. The user said, 'I want to relax.'"

[0201] This allows users to receive plans and items that better suit their emotions and needs, leading to increased satisfaction.

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The user uses a device to input their current emotions and requirements. This input data includes the user's emotions and desired activities. The entered data is organized on the device and ready to be sent to the server.

[0205] Step 2:

[0206] The server receives user data sent from the terminal. The server uses information gathering tools to retrieve relevant data from external sources. Specifically, the server queries a database via a particular API to collect the necessary information. In data processing, information related to the user's emotions is extracted.

[0207] Step 3:

[0208] The server uses emotion analysis tools to analyze the received user input data. Here, an emotion analysis library is used to classify the user's input into emotion categories. For example, if the input is "I want to relax," it will be classified into the relaxation category.

[0209] Step 4:

[0210] The server uses a plan generation mechanism to generate multiple recommended plans based on acquired data and sentiment analysis results. A generation AI model is used to create recommended plans that match specific emotions. During this process, each plan is ranked, and the optimal recommended plan is selected.

[0211] Step 5:

[0212] The generated recommended plan is sent from the server to the device. The user can review the provided plan on the device and select their preferred plan using the selection tool.

[0213] Step 6:

[0214] Once a user selects a plan, the server uses its booking system to handle all related arrangements in a single operation. Specifically, it accesses hotel and activity reservation systems and completes the necessary procedures.

[0215] Step 7:

[0216] Finally, the server uses a notification system to inform the user that the arrangements are complete. The notification is sent to the terminal, and the user can check the reservation details from their terminal.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] [Second Embodiment]

[0221] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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).

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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".

[0233] This invention provides a system for users to efficiently plan their trips. Users input their travel requirements on a terminal, and the entered information is sent to a server. The server collects necessary data from external sources and generates an optimal travel plan. This plan generation process creates multiple options based on information about transportation, accommodation, and activities, taking into account price, convenience, and user preferences.

[0234] The generated plans are presented to the user via the device, and the user selects the plan that best matches their preferences. This selected plan information is then sent back to the server, which uses this information to make various reservations in bulk. This includes booking transportation, hotels, and activities.

[0235] Once a reservation is complete, the server confirms the reservation details and sends a notification to the user's device. The user can then review this reservation information through the device and make changes or cancellations as needed. In this way, this embodiment significantly reduces the complexity of travel planning for users and enables efficient travel arrangements.

[0236] For example, if a user enters a request such as, "I want to plan a 3-day trip from Osaka to Sapporo, where I can enjoy sightseeing and local cuisine," the server will generate a plan by optimally combining flights, hotels, sightseeing tours, and restaurant reservations. Once the user completes their selections, all arrangements are made automatically, and a notification is sent to their device, allowing the user to enjoy their trip with peace of mind.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The user enters their travel requirements. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and desired activities. Once the user enters this information, the terminal collects the data and sends it to the server.

[0240] Step 2:

[0241] The server collects data from external sources based on the received travel requirements. It sends API requests to transportation databases, accommodation booking sites, activity information sites, and other similar resources. The collected information is then organized to be used as material for generating travel plans.

[0242] Step 3:

[0243] The server uses collected data and a generative AI model to generate multiple travel plans to suggest to the user. These plans are scored and optimized based on price, convenience, and user preferences.

[0244] Step 4:

[0245] The terminal displays a list of travel plan options sent from the server to the user. The user reviews the displayed plans and selects the one that best suits their preferences, considering the travel dates, details, and price.

[0246] Step 5:

[0247] The user sends the selected plan information from their device to the server. Based on the selected plan, the server automatically makes reservations for various modes of transportation, accommodations, and activities in a single batch.

[0248] Step 6:

[0249] After all reservations are complete, the server generates a reservation confirmation and detailed information and sends it to the user's device. The user can then check the reservation details on the device to ensure there are no problems.

[0250] (Example 1)

[0251] 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."

[0252] Conventional travel planning systems require users to research multiple sources and make reservations individually, which is extremely time-consuming and cumbersome. Furthermore, it is difficult to present optimal options quickly during travel planning, making it challenging to improve user satisfaction. This invention aims to solve the problem of efficiently generating optimal travel plans tailored to diverse travel requirements and automatically executing all necessary arrangements in a user-friendly manner.

[0253] 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.

[0254] In this invention, the server includes means for acquiring information from an external data source based on received travel requirements, means for generating multiple travel plans using a generative AI model, and means for executing various arrangements in a batch based on the travel plan selected by the user. This allows the user to centrally and efficiently acquire all the information necessary for their itinerary and easily utilize an optimized travel plan.

[0255] A "terminal device" is a device used by a user to input travel requirements and send that information to a server.

[0256] A "server system" is a computer system that retrieves relevant information from an external data source based on travel requirements received from a user.

[0257] The "plan generation method" is a function that analyzes acquired information and generates multiple travel plans to provide to the user using a generation AI model.

[0258] "Interface means" refers to a user interface that allows users to make selections from generated travel plans.

[0259] A "booking system" is a system that allows for the simultaneous execution of all necessary arrangements based on the selected travel plan.

[0260] "Communication means" refers to a communication function used to notify the user that arrangements have been completed.

[0261] "External data sources" refer to external systems and services used to obtain information such as transportation, accommodation, and activities.

[0262] "Generative AI models" refer to artificial intelligence technology used to generate optimal travel plans based on diverse travel requirements.

[0263] This invention is an information processing system aimed at improving the efficiency of travel planning, and consists of the following elements.

[0264] First, the user uses a device to enter their travel requirements. This device can be any device capable of inputting information, such as a computer, smartphone, or tablet. The device provides an interface for the user to input information such as their departure point, destination, travel duration, activities, and budget.

[0265] The terminal sends this entered information to the server. The server accesses external data sources via the information and communication network to collect data on transportation, accommodation, and activities. This includes utilizing external APIs and web services. For example, it may obtain flight information from airline APIs or accommodation information from hotel booking website APIs.

[0266] Subsequently, the server analyzes the collected data using a generative AI model and generates multiple travel plans for the user. The generative AI model has the ability to create multiple optimized plans that take into account the user's preferences and constraints. The generated plans offer a variety of options based on price, time efficiency, and the user's intended use, providing the best choice.

[0267] As a concrete example, suppose a user enters the prompt message, "I want to visit a resort with my family on the weekend two weeks from now and enjoy local activities." Based on this request, the server generates a travel plan combining family-friendly transportation, suitable accommodations, and popular activities. This information is presented to the user via the terminal, allowing the user to select the most suitable plan.

[0268] When a user selects a travel plan, the device sends that information to the server, which then executes all necessary arrangements based on the selected plan. This includes booking flights, accommodations, and activities. After the bookings are complete, the server verifies the details and sends a notification to the device, providing the user with the necessary information. This entire process allows users to plan and execute their trips efficiently and without hassle.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The user enters their travel requirements using a terminal. The terminal receives input such as departure point, destination, travel duration, budget, and activities. This data is formatted as overall foundational information for travel planning and sent to the server.

[0272] Step 2:

[0273] The terminal sends the entered travel requirements to the server. The server receives this data and prepares requests to retrieve data from the necessary external sources. This process involves constructing and sending API requests.

[0274] Step 3:

[0275] The server collects the necessary information from external data sources. The server accesses each external data source to obtain information on transportation means, accommodation facilities, and activities. Specifically, it retrieves flight information from the airline's API and hotel information from the accommodation reservation site's API, and stores the content in the database.

[0276] Step 4:

[0277] The server uses the generated AI model to generate a travel plan. The server inputs the collected data into the generated AI model and creates multiple travel plans to propose to the user based on this. The data operations performed here include price comparison, travel time calculation, and matching with the user's preferences. The generated plans are adjusted to have different characteristics.

[0278] Step 5:

[0279] The server sends the travel plans generated to the terminal. The terminal displays those plans for the user to view. The user can check each plan and select the travel plan that best suits their needs.

[0280] Step 6:

[0281] The user selects the optimal travel plan and uses the terminal to send that information to the server. The server arranges the data for the next step upon receiving this selection information.

[0282] Step 7:

[0283] Based on the selected travel plan, the server executes various arrangements in a batch. The server sends the content of the selected plan to each service provider through the API to complete the reservation of flights, hotels, and activities. This includes reservation confirmation and payment procedures.

[0284] Step 8:

[0285] The server notifies the terminal of the reservation completion information. The terminal displays the information to the user and provides options for confirming the reservation details and making changes or cancellations if necessary. The user can then proceed with confidence in preparing for the trip.

[0286] (Application Example 1)

[0287] 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".

[0288] In a conventional travel planning system, users had to perform individual reservation procedures separately, making it difficult to efficiently integrate the overall plan. Additionally, it was challenging to easily create an optimal travel plan according to the user's requirements, so travel planning was a very time-consuming and laborious task. Furthermore, the provision of intuitive operations using voice and virtual travel experiences leveraging modern technologies was insufficient.

[0289] 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.

[0290] In this invention, the server includes a data input device that receives travel requirements from the user, an information collection device that acquires information from an external information source based on the received travel requirements, and a plan generation device that analyzes the acquired information and generates a plurality of travel plans to be presented to the user. This enables the creation of an intuitive travel plan through voice input and provides a more convenient travel plan utilizing natural language processing.

[0291] The "data input device" is a device that receives travel conditions and requirements from the user and has the function of processing them within the system.

[0292] The "information collection device" is a device that acquires necessary data from an external information source based on the received travel requirements.

[0293] A "plan generation device" is a device that analyzes collected data and creates and presents the optimal travel plan to the user.

[0294] A "selection device" is a device that allows a user to choose their preferred travel plan from among the travel plans presented.

[0295] A "reservation device" is a device that allows users to make various reservations, such as for transportation and accommodation, all at once, based on the travel plan they have selected.

[0296] A "communication device" is a device used to notify the user that their reservation has been completed.

[0297] An "input support device" is a device that receives the user's travel requirements through voice input and then performs natural language processing on them.

[0298] An "optimization algorithm" is a computational method used to evaluate and rank travel plans and select the most suitable one.

[0299] A "generative AI model" is a model that uses artificial intelligence technology to generate the optimal travel plan for a user.

[0300] The system for carrying out the present invention comprises a user, a terminal, and a server. The user uses a terminal such as a smartphone or smart glasses to input travel preferences and requirements in voice or text. On the terminal, voice recognition technology, such as Google Cloud Speech-to-Text API, is used to convert the voice data into text data. This text data is analyzed using natural language processing technology and sent to the server as travel requirements.

[0301] The server retrieves necessary information from external sources (such as the internet or databases provided by partner companies) based on the received travel requirements. Cloud services, such as Google Cloud Platform, are utilized for this information retrieval. The collected information is analyzed by optimization algorithms and generative AI models to generate an optimal travel plan tailored to the user's needs. This AI model proposes plans that match the user's preferences, budget, and schedule.

[0302] The travel plan, returned to the device, is presented to the user. The user selects their preferred plan from the multiple options presented. The details of the selected plan are sent back to the server, which then makes reservations for transportation, accommodation, and activities all at once. After the reservations are complete, the server notifies the device of the details.

[0303] For example, if a user enters a request such as, "I want to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," the system will generate a plan combining the best Shinkansen (bullet train) times, highly-rated Japanese restaurants, and hotel information. Based on the plan approved by the user, the reservation is automatically completed, and a notification is sent to the device. An example of a prompt message would be, "Please suggest a relaxing hot spring trip plan. My budget is under 100,000 yen, I want a three-night, four-day stay, and preferably a Japanese-style inn."

[0304] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0305] Step 1:

[0306] Users input their travel preferences and requirements using their smartphones or smart glasses via voice or text. The system utilizes speech recognition technology to convert voice data into text. For example, if a user says, "I'd like to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," that text will appear on the device.

[0307] Step 2:

[0308] The terminal sends the converted text data to the server. The server analyzes the received text data using NLP (Natural Language Processing), a natural language processing technology, and understands it as travel requirements. As specific operations, keywords such as "Tokyo", "Kyoto", "two days", and "Japanese cuisine" are extracted from the text.

[0309] Step 3:

[0310] The server collects relevant information from external information sources based on the user's travel requirements. For information collection, the Internet and partner databases are utilized through APIs. In this step, specifically, information such as Shinkansen schedules, highly rated Japanese cuisine restaurants, and availability of accommodation facilities is obtained.

[0311] Step 4:

[0312] The server generates multiple travel plans using an optimization algorithm and a generation AI model based on the collected information. As data processing, the plans are evaluated and ranked based on the user's budget and schedule. Specifically, the optimal plans that can be made within the budget are listed up.

[0313] Step 5:

[0314] The terminal presents the proposed plans sent from the server to the user. The user selects the desired plan from the multiple options displayed on the terminal. As a specific operation, there is an operation where the user taps "This plan is good".

[0315] Step 6:

[0316] The information of the selected travel plan is sent to the server, and the server makes reservations for transportation and accommodation in a batch based on the content. The specific operation is to access the partner reservation service via the API and automatically confirm the necessary reservations.

[0317] Step 7:

[0318] The server confirms that all reservations are complete and notifies the terminal of this completion. Users can then check the reservation details on their terminal to ensure there are no issues. Specifically, a reservation success message and detailed information will be displayed on a particular screen.

[0319] Step 8:

[0320] Users can change or cancel their reservations as needed. Actions taken on the device send a request to the server, which then processes the reservation change. For example, canceling a plan is done through a similar process.

[0321] 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.

[0322] This invention is a system that not only efficiently plans trips but also takes user emotions into account to provide a more personalized travel experience. The system includes a terminal interface for inputting travel requirements, a server-based information gathering and plan generation function, and an emotion engine to assist with plan selection and booking arrangements.

[0323] First, the user enters their travel requirements via a device. This information includes departure point, destination, travel duration, budget, and desired activities. The device then organizes this information and sends it to the server.

[0324] Based on the received requirements, the server collects the necessary data from external sources. After data collection, the plan generation function on the server generates multiple travel plans using an optimization algorithm and ranks them. A distinctive feature here is the use of an emotion engine; the server recognizes the user's emotions and reflects the results in plan generation, providing plans that match the traveler's mood and preferences.

[0325] For example, if a user expresses a desire to "relieve stress," the emotion engine can generate a plan that prioritizes activities with high relaxation and refreshing effects, as well as accommodations in lush, green spaces. The user's emotional information is derived from user input and, if necessary, other data obtained from the device.

[0326] Users select the plan that best suits them from the available options via their device. After selection, the server automatically arranges all necessary reservations based on the chosen plan. Once the reservations are complete, the server notifies the user, displaying the reservation details on their device. This emotionally conscious process not only reduces the hassle of travel arrangements but also enriches the user experience, making it more satisfying.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The user enters their travel requirements using a terminal. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and activities. After the user enters this information, the terminal organizes the data and sends it to the server.

[0330] Step 2:

[0331] The server collects relevant data from external sources based on the received travel requirements. Specifically, it obtains information using APIs from databases and booking sites related to flights, hotels, and tourist activities.

[0332] Step 3:

[0333] The device generates emotional data using input and, if necessary, sensor data to understand the user's emotional state. This data is sent to a server.

[0334] Step 4:

[0335] The server combines collected data with user sentiment data and generates multiple travel plans using a generative AI model. The plans are evaluated and ranked using an optimization algorithm that takes user sentiment into account. At this stage, the sentiment engine prioritizes plans that match the user's mood.

[0336] Step 5:

[0337] A travel plan generated on the device is sent from the server, and the user reviews it and selects the most preferred plan. The plan includes detailed information such as price, schedule, and accommodation information.

[0338] Step 6:

[0339] The user sends their selected travel plan to the server. Based on this selection, the server makes various reservations in a single batch (e.g., transportation tickets, hotel rooms, activity bookings).

[0340] Step 7:

[0341] Once all reservations are confirmed, the server generates a reservation confirmation and sends it to the user's device. The user then reviews the reservation details on their device, completing their travel plan.

[0342] (Example 2)

[0343] 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".

[0344] Conventional travel planning systems have struggled to provide travel plans that adequately consider users' emotions and individual needs, resulting in insufficient user satisfaction. Furthermore, the booking process after selecting a travel plan is often cumbersome, requiring considerable time and effort from the user. To address these issues, there is a need for a system that generates travel plans that take emotions into account and enables efficient booking procedures.

[0345] 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.

[0346] In this invention, the server includes an interface means for receiving travel-related information from the user, an emotion analysis means for analyzing the user's emotional state and reflecting it in the travel plan, and a travel plan generation means for generating a travel plan using optimization technology. This makes it possible to provide personalized travel plans that take into account the user's individual emotions and needs, and to efficiently arrange reservations based on the selected travel plan.

[0347] "Interface means" refers to a device or software through which a user inputs travel-related information, and through which that information is transmitted to a server.

[0348] "Data acquisition means" refers to a device or method for collecting necessary data from external sources based on information received from the user.

[0349] A "travel plan generation means" is a device or software that analyzes acquired data and creates multiple optimized travel plans according to the user's requirements.

[0350] "Selection method" refers to a method or apparatus for a user to select their preferred travel plan from the generated travel plans.

[0351] A "booking arrangement device" is a device or system that automatically performs the necessary booking procedures based on the travel plan selected by the user.

[0352] "Communication means" refers to a method or system for transmitting information to the user, such as the completion of a reservation procedure.

[0353] "Emotional analysis means" refers to a technology or device that analyzes data related to a user's emotions and reflects the results in travel plans.

[0354] The system of this invention aims to provide personalized travel plans by taking into account the user's emotions and individual needs in travel planning. An embodiment thereof is shown below.

[0355] First, the user enters travel information using a device. This device can be a smartphone or a computer, and is accessible via a dedicated application or web interface. The user enters their departure point, destination, travel duration, budget, and desired activities. This information is compiled through the interface and sent to the server.

[0356] The server uses data acquisition methods based on information received from the terminal to collect necessary information through the internet and travel-related databases. External information includes accommodation, transportation, and tourist destination information, and data is acquired in real time using APIs.

[0357] Based on the acquired information, the server activates an emotion analysis system. This involves a process that uses natural language processing technology to analyze the user's input information to determine their emotions. For example, if the user inputs "I want to relax," the emotion analysis will recommend activities to reduce stress.

[0358] Subsequently, the server uses a travel plan generation mechanism and optimization techniques (e.g., genetic algorithms) to create multiple travel plans that match the user's requests. The generated travel plans are sent to the terminal in a visually easy-to-understand format, allowing the user to select one.

[0359] For example, if the prompt is "I want to get away from the hustle and bustle of the city," sentiment analysis will generate a plan that prioritizes quiet travel destinations surrounded by nature. A more specific example of a prompt would be, "Please create a travel plan that meets the following conditions: departure point is Tokyo, destination is a place surrounded by nature, travel duration is 3 days, budget is under 100,000 yen, and relaxing activities are prioritized."

[0360] Ultimately, the user selects the most suitable travel plan from the provided options. The server then automatically makes the necessary booking arrangements based on the selected travel plan using booking tools. This allows the user to prepare for their trip with minimal stress.

[0361] The above describes a specific embodiment for implementing this invention. By providing travel plans that take into account the user's emotions, a more personalized experience is realized, thereby improving user satisfaction.

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] Users enter travel information using their device. This information includes departure point, destination, travel duration, budget, and desired activities. This information is entered intuitively using forms and selection menus on the device screen. This input data is then prepared to be sent to the server in a structured format (e.g., JSON).

[0365] Step 2:

[0366] The terminal receives user input data, organizes it, and sends it to the server. Here, the data is encrypted using the HTTPS protocol to ensure security. The data sent to the server includes all travel requirements entered by the user.

[0367] Step 3:

[0368] The server receives user travel information sent from the terminal. Based on this information, it uses data acquisition methods to collect necessary external data from the internet and travel-related databases. Specifically, the server issues API requests, retrieves response data in real time, and stores it. The collected data includes information on accommodations and tourist attractions at the travel destination.

[0369] Step 4:

[0370] The server uses the collected data and user input to activate the sentiment analysis system. Here, natural language processing techniques are used to analyze the user's emotions. Based on the input (e.g., "I want to relax"), the system identifies the user's emotional state and prepares the results for use in the next step.

[0371] Step 5:

[0372] The server drives the travel plan generation mechanism using the results of sentiment analysis and collected data. It utilizes a generative AI model to process input data using an optimization algorithm (e.g., a genetic algorithm) and generate multiple travel plans. Each generated travel plan is adjusted to match the user's identified emotional state and then ranked.

[0373] Step 6:

[0374] The server sends the generated travel plan to the device. The device displays the travel plan to the user in a visually easy-to-understand format (e.g., map or schedule). At this time, the device presents the travel plan with a user interface designed to allow the user to easily compare and select options.

[0375] Step 7:

[0376] The user selects their preferred travel plan from those presented on the device. The information of the selected travel plan is then sent back to the server. If a selection is made at this stage, preparations for the next steps proceed based on that travel plan.

[0377] Step 8:

[0378] The server activates the booking system based on the selected travel plan and automatically makes the necessary bookings. At this stage, the server collaborates with external systems to make reservations for accommodations and activities. Booking information is recorded for later notifications.

[0379] Step 9:

[0380] After the server confirms the completion of the reservation, it sends the details to the device. The device then displays the details of the completed reservation to the user. At this time, detailed information is provided via confirmation email or in-app notification to give the user peace of mind.

[0381] (Application Example 2)

[0382] 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."

[0383] Traditional recommendation systems have struggled to provide personalized services that cater to users' emotions and individual needs. As a result, users often feel that the products and services offered do not suit their mood or circumstances, leading to decreased satisfaction.

[0384] 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.

[0385] In this invention, the server includes input means for receiving requirements from the user, information gathering means for acquiring data from external information sources, and sentiment analysis means for reflecting the user's emotions in plan generation. This makes it possible to provide personalized plans based on the user's emotions.

[0386] An "input means" is a device or interface for receiving requirements or instructions from the user.

[0387] "Information gathering means" refers to the processes and functions for obtaining necessary data from external databases and information sources.

[0388] The "plan generation method" is a function that creates multiple recommended plans to provide to the user based on the acquired data.

[0389] "Selection method" refers to an interface or function that allows a user to choose the plan they want from the options provided.

[0390] "Arrangement method" refers to the process or function of making arrangements such as reservations and orders based on the selected plan, all in one go.

[0391] "Notification means" refers to methods or functions for informing the user of the information once the arrangements have been completed.

[0392] "Emotional analysis tools" refer to technologies and functions that recognize a user's emotions and reflect them in plan generation.

[0393] This invention is a system that provides personalized recommendation plans that take user emotions into consideration. The system mainly consists of a server and user terminals.

[0394] The server will be implemented using Python or other programming languages. Sentiment analysis will utilize sentiment analysis libraries (e.g., TextBlob, Natural Language Toolkit). The system will include data collection mechanisms to gather data from external sources and generate plans based on user input.

[0395] The user terminal functions as a smartphone or tablet, where the user enters their requirements. When the user enters a specific situation or mood, that data is sent to the server. The server analyzes this information using sentiment analysis tools and generates an appropriate plan based on the user's emotions.

[0396] The generated plan is notified to the user's terminal, and the user can select it. After selection, the server makes all relevant arrangements via the arrangement mechanism and notifies the user of the completed information via the notification mechanism.

[0397] For example, if a user enters "I want to relax today," the server will collect relevant data and generate prompts suggesting items and activities with relaxation effects. For instance, the generating AI model can be run using a prompt such as, "Suggest the best products based on the emotion entered by the user. The user said, 'I want to relax.'"

[0398] This allows users to receive plans and items that better suit their emotions and needs, leading to increased satisfaction.

[0399] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0400] Step 1:

[0401] The user uses a device to input their current emotions and requirements. This input data includes the user's emotions and desired activities. The entered data is organized on the device and ready to be sent to the server.

[0402] Step 2:

[0403] The server receives user data sent from the terminal. The server uses information gathering tools to retrieve relevant data from external sources. Specifically, the server queries a database via a particular API to collect the necessary information. In data processing, information related to the user's emotions is extracted.

[0404] Step 3:

[0405] The server uses emotion analysis tools to analyze the received user input data. Here, an emotion analysis library is used to classify the user's input into emotion categories. For example, if the input is "I want to relax," it will be classified into the relaxation category.

[0406] Step 4:

[0407] The server uses a plan generation mechanism to generate multiple recommended plans based on acquired data and sentiment analysis results. A generation AI model is used to create recommended plans that match specific emotions. During this process, each plan is ranked, and the optimal recommended plan is selected.

[0408] Step 5:

[0409] The generated recommended plan is sent from the server to the device. The user can review the provided plan on the device and select their preferred plan using the selection tool.

[0410] Step 6:

[0411] Once a user selects a plan, the server uses its booking system to handle all related arrangements in a single operation. Specifically, it accesses hotel and activity reservation systems and completes the necessary procedures.

[0412] Step 7:

[0413] Finally, the server uses a notification system to inform the user that the arrangements are complete. The notification is sent to the terminal, and the user can check the reservation details from their terminal.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] [Third Embodiment]

[0418] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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).

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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".

[0430] This invention provides a system for users to efficiently plan their trips. Users input their travel requirements on a terminal, and the entered information is sent to a server. The server collects necessary data from external sources and generates an optimal travel plan. This plan generation process creates multiple options based on information about transportation, accommodation, and activities, taking into account price, convenience, and user preferences.

[0431] The generated plans are presented to the user via the device, and the user selects the plan that best matches their preferences. This selected plan information is then sent back to the server, which uses this information to make various reservations in bulk. This includes booking transportation, hotels, and activities.

[0432] Once a reservation is complete, the server confirms the reservation details and sends a notification to the user's device. The user can then review this reservation information through the device and make changes or cancellations as needed. In this way, this embodiment significantly reduces the complexity of travel planning for users and enables efficient travel arrangements.

[0433] For example, if a user enters a request such as, "I want to plan a 3-day trip from Osaka to Sapporo, where I can enjoy sightseeing and local cuisine," the server will generate a plan by optimally combining flights, hotels, sightseeing tours, and restaurant reservations. Once the user completes their selections, all arrangements are made automatically, and a notification is sent to their device, allowing the user to enjoy their trip with peace of mind.

[0434] The following describes the processing flow.

[0435] Step 1:

[0436] The user enters their travel requirements. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and desired activities. Once the user enters this information, the terminal collects the data and sends it to the server.

[0437] Step 2:

[0438] The server collects data from external sources based on the received travel requirements. It sends API requests to transportation databases, accommodation booking sites, activity information sites, and other similar resources. The collected information is then organized to be used as material for generating travel plans.

[0439] Step 3:

[0440] The server uses collected data and a generative AI model to generate multiple travel plans to suggest to the user. These plans are scored and optimized based on price, convenience, and user preferences.

[0441] Step 4:

[0442] The terminal displays a list of travel plan options sent from the server to the user. The user reviews the displayed plans and selects the one that best suits their preferences, considering the travel dates, details, and price.

[0443] Step 5:

[0444] The user sends the selected plan information from their device to the server. Based on the selected plan, the server automatically makes reservations for various modes of transportation, accommodations, and activities in a single batch.

[0445] Step 6:

[0446] After all reservations are complete, the server generates a reservation confirmation and detailed information and sends it to the user's device. The user can then check the reservation details on the device to ensure there are no problems.

[0447] (Example 1)

[0448] 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."

[0449] Conventional travel planning systems require users to research multiple sources and make reservations individually, which is extremely time-consuming and cumbersome. Furthermore, it is difficult to present optimal options quickly during travel planning, making it challenging to improve user satisfaction. This invention aims to solve the problem of efficiently generating optimal travel plans tailored to diverse travel requirements and automatically executing all necessary arrangements in a user-friendly manner.

[0450] 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.

[0451] In this invention, the server includes means for acquiring information from an external data source based on received travel requirements, means for generating multiple travel plans using a generative AI model, and means for executing various arrangements in a batch based on the travel plan selected by the user. This allows the user to centrally and efficiently acquire all the information necessary for their itinerary and easily utilize an optimized travel plan.

[0452] A "terminal device" is a device used by a user to input travel requirements and send that information to a server.

[0453] A "server system" is a computer system that retrieves relevant information from an external data source based on travel requirements received from a user.

[0454] The "plan generation method" is a function that analyzes acquired information and generates multiple travel plans to provide to the user using a generation AI model.

[0455] "Interface means" refers to a user interface that allows users to make selections from generated travel plans.

[0456] A "booking system" is a system that allows for the simultaneous execution of all necessary arrangements based on the selected travel plan.

[0457] "Communication means" refers to a communication function used to notify the user that arrangements have been completed.

[0458] "External data sources" refer to external systems and services used to obtain information such as transportation, accommodation, and activities.

[0459] "Generative AI models" refer to artificial intelligence technology used to generate optimal travel plans based on diverse travel requirements.

[0460] This invention is an information processing system aimed at improving the efficiency of travel planning, and consists of the following elements.

[0461] First, the user uses a device to enter their travel requirements. This device can be any device capable of inputting information, such as a computer, smartphone, or tablet. The device provides an interface for the user to input information such as their departure point, destination, travel duration, activities, and budget.

[0462] The terminal sends this entered information to the server. The server accesses external data sources via the information and communication network to collect data on transportation, accommodation, and activities. This includes utilizing external APIs and web services. For example, it may obtain flight information from airline APIs or accommodation information from hotel booking website APIs.

[0463] Subsequently, the server analyzes the collected data using a generative AI model and generates multiple travel plans for the user. The generative AI model has the ability to create multiple optimized plans that take into account the user's preferences and constraints. The generated plans offer a variety of options based on price, time efficiency, and the user's intended use, providing the best choice.

[0464] As a concrete example, suppose a user enters the prompt message, "I want to visit a resort with my family on the weekend two weeks from now and enjoy local activities." Based on this request, the server generates a travel plan combining family-friendly transportation, suitable accommodations, and popular activities. This information is presented to the user via the terminal, allowing the user to select the most suitable plan.

[0465] When a user selects a travel plan, the device sends that information to the server, which then executes all necessary arrangements based on the selected plan. This includes booking flights, accommodations, and activities. After the bookings are complete, the server verifies the details and sends a notification to the device, providing the user with the necessary information. This entire process allows users to plan and execute their trips efficiently and without hassle.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] The user enters their travel requirements using a terminal. The terminal receives input such as departure point, destination, travel duration, budget, and activities. This data is formatted as overall foundational information for travel planning and sent to the server.

[0469] Step 2:

[0470] The terminal sends the entered travel requirements to the server. The server receives this data and prepares requests to retrieve data from the necessary external sources. This process involves constructing and sending API requests.

[0471] Step 3:

[0472] The server collects necessary information from external data sources. The server accesses each external data source to retrieve information on transportation, accommodation, and activities. Specifically, it obtains flight information from airline APIs and hotel information from accommodation booking site APIs, and stores this information in a database.

[0473] Step 4:

[0474] The server generates travel plans using a generative AI model. The server inputs collected data into the generative AI model and creates multiple travel plans to suggest to the user based on this data. The data calculations performed include price comparison, duration calculation, and matching with the user's preferences. The generated plans are then adjusted to each have distinct characteristics.

[0475] Step 5:

[0476] The server generates travel plans and sends them to the device. The device then displays these plans for the user to view. The user can review each plan and select the one that best suits their needs.

[0477] Step 6:

[0478] The user selects the optimal travel plan and sends that information to the server using their device. The server receives this selection information and prepares the data for the next step.

[0479] Step 7:

[0480] The server handles all arrangements based on the selected travel plan. The server sends the details of the selected plan to each service provider via API, completing bookings for flights, hotels, and activities. This includes booking confirmation and payment processing.

[0481] Step 8:

[0482] The server notifies the terminal of the booking completion information. The terminal displays this information to the user, providing options for confirming the booking details and making changes or cancellations as needed. The user can then proceed with their travel preparations with peace of mind.

[0483] (Application Example 1)

[0484] 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."

[0485] Traditional travel planning systems required users to make individual bookings separately, making it difficult to efficiently integrate the entire plan. Furthermore, creating optimal travel plans tailored to user needs was challenging, making travel planning a very time-consuming and laborious task. Additionally, they lacked sufficient intuitive voice-activated operation and the provision of virtual travel experiences utilizing modern technology.

[0486] 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.

[0487] In this invention, the server includes a data input device that receives travel requirements from a user, an information gathering device that acquires information from external sources based on the received travel requirements, and a plan generation device that analyzes the acquired information and generates multiple travel plans to present to the user. This enables the creation of intuitive travel plans using voice input and allows for the provision of more convenient travel plans utilizing natural language processing.

[0488] A "data input device" is a device that has the function of receiving travel conditions and requests from users and processing them within the system.

[0489] An "information gathering device" is a device that acquires necessary data from external sources based on the received travel requirements.

[0490] A "plan generation device" is a device that analyzes collected data and creates and presents the optimal travel plan to the user.

[0491] A "selection device" is a device that allows a user to choose their preferred travel plan from among the travel plans presented.

[0492] A "reservation device" is a device that allows users to make various reservations, such as for transportation and accommodation, all at once, based on the travel plan they have selected.

[0493] A "communication device" is a device used to notify the user that their reservation has been completed.

[0494] An "input support device" is a device that receives the user's travel requirements through voice input and then performs natural language processing on them.

[0495] An "optimization algorithm" is a computational method used to evaluate and rank travel plans and select the most suitable one.

[0496] A "generative AI model" is a model that uses artificial intelligence technology to generate the optimal travel plan for a user.

[0497] The system for carrying out the present invention comprises a user, a terminal, and a server. The user uses a terminal such as a smartphone or smart glasses to input travel preferences and requirements in voice or text. On the terminal, voice recognition technology, such as Google Cloud Speech-to-Text API, is used to convert the voice data into text data. This text data is analyzed using natural language processing technology and sent to the server as travel requirements.

[0498] The server retrieves necessary information from external sources (such as the internet or databases provided by partner companies) based on the received travel requirements. Cloud services, such as Google Cloud Platform, are utilized for this information retrieval. The collected information is analyzed by optimization algorithms and generative AI models to generate an optimal travel plan tailored to the user's needs. This AI model proposes plans that match the user's preferences, budget, and schedule.

[0499] The travel plan, returned to the device, is presented to the user. The user selects their preferred plan from the multiple options presented. The details of the selected plan are sent back to the server, which then makes reservations for transportation, accommodation, and activities all at once. After the reservations are complete, the server notifies the device of the details.

[0500] For example, if a user enters a request such as, "I want to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," the system will generate a plan combining the best Shinkansen (bullet train) times, highly-rated Japanese restaurants, and hotel information. Based on the plan approved by the user, the reservation is automatically completed, and a notification is sent to the device. An example of a prompt message would be, "Please suggest a relaxing hot spring trip plan. My budget is under 100,000 yen, I want a three-night, four-day stay, and preferably a Japanese-style inn."

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] Users input their travel preferences and requirements using their smartphones or smart glasses via voice or text. The system utilizes speech recognition technology to convert voice data into text. For example, if a user says, "I'd like to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," that text will appear on the device.

[0504] Step 2:

[0505] The terminal sends the converted text data to the server. The server analyzes the received text data using NLP (Natural Language Processing), a natural language processing technique, and understands it as travel requirements. Specifically, it extracts keywords such as "Tokyo," "Kyoto," "2 days," and "Japanese food" from the text.

[0506] Step 3:

[0507] The server collects relevant information from external sources based on the user's travel requirements. This information gathering utilizes the internet and partner databases via APIs. Specifically, this step retrieves information such as Shinkansen (bullet train) schedules, highly-rated Japanese restaurants, and accommodation availability.

[0508] Step 4:

[0509] The server generates multiple travel plans using optimization algorithms and generative AI models based on the collected information. As part of the data processing, it evaluates and ranks the plans based on the user's budget and schedule. Specifically, it lists the best plans that fit within the budget.

[0510] Step 5:

[0511] The device presents the user with proposed plans sent from the server. The user selects their preferred plan from the multiple options displayed on the device. Specifically, the user taps to indicate "This plan is good."

[0512] Step 6:

[0513] The selected travel plan information is sent to the server, which then makes bulk reservations for transportation and accommodation based on that information. Specifically, it accesses partner reservation services via API and automatically confirms the necessary reservations.

[0514] Step 7:

[0515] The server confirms that all reservations are complete and notifies the terminal of this completion. Users can then check the reservation details on their terminal to ensure there are no issues. Specifically, a reservation success message and detailed information will be displayed on a particular screen.

[0516] Step 8:

[0517] Users can change or cancel their reservations as needed. Actions taken on the device send a request to the server, which then processes the reservation change. For example, canceling a plan is done through a similar process.

[0518] 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.

[0519] This invention is a system that not only efficiently plans trips but also takes user emotions into account to provide a more personalized travel experience. The system includes a terminal interface for inputting travel requirements, a server-based information gathering and plan generation function, and an emotion engine to assist with plan selection and booking arrangements.

[0520] First, the user enters their travel requirements via a device. This information includes departure point, destination, travel duration, budget, and desired activities. The device then organizes this information and sends it to the server.

[0521] Based on the received requirements, the server collects the necessary data from external sources. After data collection, the plan generation function on the server generates multiple travel plans using an optimization algorithm and ranks them. A distinctive feature here is the use of an emotion engine; the server recognizes the user's emotions and reflects the results in plan generation, providing plans that match the traveler's mood and preferences.

[0522] For example, if a user expresses a desire to "relieve stress," the emotion engine can generate a plan that prioritizes activities with high relaxation and refreshing effects, as well as accommodations in lush, green spaces. The user's emotional information is derived from user input and, if necessary, other data obtained from the device.

[0523] Users select the plan that best suits them from the available options via their device. After selection, the server automatically arranges all necessary reservations based on the chosen plan. Once the reservations are complete, the server notifies the user, displaying the reservation details on their device. This emotionally conscious process not only reduces the hassle of travel arrangements but also enriches the user experience, making it more satisfying.

[0524] The following describes the processing flow.

[0525] Step 1:

[0526] The user enters their travel requirements using a terminal. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and activities. After the user enters this information, the terminal organizes the data and sends it to the server.

[0527] Step 2:

[0528] The server collects relevant data from external sources based on the received travel requirements. Specifically, it obtains information using APIs from databases and booking sites related to flights, hotels, and tourist activities.

[0529] Step 3:

[0530] The device generates emotional data using input and, if necessary, sensor data to understand the user's emotional state. This data is sent to a server.

[0531] Step 4:

[0532] The server combines collected data with user sentiment data and generates multiple travel plans using a generative AI model. The plans are evaluated and ranked using an optimization algorithm that takes user sentiment into account. At this stage, the sentiment engine prioritizes plans that match the user's mood.

[0533] Step 5:

[0534] A travel plan generated on the device is sent from the server, and the user reviews it and selects the most preferred plan. The plan includes detailed information such as price, schedule, and accommodation information.

[0535] Step 6:

[0536] The user sends their selected travel plan to the server. Based on this selection, the server makes various reservations in a single batch (e.g., transportation tickets, hotel rooms, activity bookings).

[0537] Step 7:

[0538] Once all reservations are confirmed, the server generates a reservation confirmation and sends it to the user's device. The user then reviews the reservation details on their device, completing their travel plan.

[0539] (Example 2)

[0540] 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."

[0541] Conventional travel planning systems have struggled to provide travel plans that adequately consider users' emotions and individual needs, resulting in insufficient user satisfaction. Furthermore, the booking process after selecting a travel plan is often cumbersome, requiring considerable time and effort from the user. To address these issues, there is a need for a system that generates travel plans that take emotions into account and enables efficient booking procedures.

[0542] 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.

[0543] In this invention, the server includes an interface means for receiving travel-related information from the user, an emotion analysis means for analyzing the user's emotional state and reflecting it in the travel plan, and a travel plan generation means for generating a travel plan using optimization technology. This makes it possible to provide personalized travel plans that take into account the user's individual emotions and needs, and to efficiently arrange reservations based on the selected travel plan.

[0544] "Interface means" refers to a device or software through which a user inputs travel-related information, and through which that information is transmitted to a server.

[0545] "Data acquisition means" refers to a device or method for collecting necessary data from external sources based on information received from the user.

[0546] A "travel plan generation means" is a device or software that analyzes acquired data and creates multiple optimized travel plans according to the user's requirements.

[0547] "Selection method" refers to a method or apparatus for a user to select their preferred travel plan from the generated travel plans.

[0548] A "booking arrangement device" is a device or system that automatically performs the necessary booking procedures based on the travel plan selected by the user.

[0549] "Communication means" refers to a method or system for transmitting information to the user, such as the completion of a reservation procedure.

[0550] "Emotional analysis means" refers to a technology or device that analyzes data related to a user's emotions and reflects the results in travel plans.

[0551] The system of this invention aims to provide personalized travel plans by taking into account the user's emotions and individual needs in travel planning. An embodiment thereof is shown below.

[0552] First, the user enters travel information using a device. This device can be a smartphone or a computer, and is accessible via a dedicated application or web interface. The user enters their departure point, destination, travel duration, budget, and desired activities. This information is compiled through the interface and sent to the server.

[0553] The server uses data acquisition methods based on information received from the terminal to collect necessary information through the internet and travel-related databases. External information includes accommodation, transportation, and tourist destination information, and data is acquired in real time using APIs.

[0554] Based on the acquired information, the server activates an emotion analysis system. This involves a process that uses natural language processing technology to analyze the user's input information to determine their emotions. For example, if the user inputs "I want to relax," the emotion analysis will recommend activities to reduce stress.

[0555] Subsequently, the server uses a travel plan generation mechanism and optimization techniques (e.g., genetic algorithms) to create multiple travel plans that match the user's requests. The generated travel plans are sent to the terminal in a visually easy-to-understand format, allowing the user to select one.

[0556] For example, if the prompt is "I want to get away from the hustle and bustle of the city," sentiment analysis will generate a plan that prioritizes quiet travel destinations surrounded by nature. A more specific example of a prompt would be, "Please create a travel plan that meets the following conditions: departure point is Tokyo, destination is a place surrounded by nature, travel duration is 3 days, budget is under 100,000 yen, and relaxing activities are prioritized."

[0557] Ultimately, the user selects the most suitable travel plan from the provided options. The server then automatically makes the necessary booking arrangements based on the selected travel plan using booking tools. This allows the user to prepare for their trip with minimal stress.

[0558] The above describes a specific embodiment for implementing this invention. By providing travel plans that take into account the user's emotions, a more personalized experience is realized, thereby improving user satisfaction.

[0559] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0560] Step 1:

[0561] Users enter travel information using their device. This information includes departure point, destination, travel duration, budget, and desired activities. This information is entered intuitively using forms and selection menus on the device screen. This input data is then prepared to be sent to the server in a structured format (e.g., JSON).

[0562] Step 2:

[0563] The terminal receives user input data, organizes it, and sends it to the server. Here, the data is encrypted using the HTTPS protocol to ensure security. The data sent to the server includes all travel requirements entered by the user.

[0564] Step 3:

[0565] The server receives user travel information sent from the terminal. Based on this information, it uses data acquisition methods to collect necessary external data from the internet and travel-related databases. Specifically, the server issues API requests, retrieves response data in real time, and stores it. The collected data includes information on accommodations and tourist attractions at the travel destination.

[0566] Step 4:

[0567] The server uses the collected data and user input to activate the sentiment analysis system. Here, natural language processing techniques are used to analyze the user's emotions. Based on the input (e.g., "I want to relax"), the system identifies the user's emotional state and prepares the results for use in the next step.

[0568] Step 5:

[0569] The server drives the travel plan generation mechanism using the results of sentiment analysis and collected data. It utilizes a generative AI model to process input data using an optimization algorithm (e.g., a genetic algorithm) and generate multiple travel plans. Each generated travel plan is adjusted to match the user's identified emotional state and then ranked.

[0570] Step 6:

[0571] The server sends the generated travel plan to the device. The device displays the travel plan to the user in a visually easy-to-understand format (e.g., map or schedule). At this time, the device presents the travel plan with a user interface designed to allow the user to easily compare and select options.

[0572] Step 7:

[0573] The user selects their preferred travel plan from those presented on the device. The information of the selected travel plan is then sent back to the server. If a selection is made at this stage, preparations for the next steps proceed based on that travel plan.

[0574] Step 8:

[0575] The server activates the booking system based on the selected travel plan and automatically makes the necessary bookings. At this stage, the server collaborates with external systems to make reservations for accommodations and activities. Booking information is recorded for later notifications.

[0576] Step 9:

[0577] After the server confirms the completion of the reservation, it sends the details to the device. The device then displays the details of the completed reservation to the user. At this time, detailed information is provided via confirmation email or in-app notification to give the user peace of mind.

[0578] (Application Example 2)

[0579] 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."

[0580] Traditional recommendation systems have struggled to provide personalized services that cater to users' emotions and individual needs. As a result, users often feel that the products and services offered do not suit their mood or circumstances, leading to decreased satisfaction.

[0581] 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.

[0582] In this invention, the server includes input means for receiving requirements from the user, information gathering means for acquiring data from external information sources, and sentiment analysis means for reflecting the user's emotions in plan generation. This makes it possible to provide personalized plans based on the user's emotions.

[0583] An "input means" is a device or interface for receiving requirements or instructions from the user.

[0584] "Information gathering means" refers to the processes and functions for obtaining necessary data from external databases and information sources.

[0585] The "plan generation method" is a function that creates multiple recommended plans to provide to the user based on the acquired data.

[0586] "Selection method" refers to an interface or function that allows a user to choose the plan they want from the options provided.

[0587] "Arrangement method" refers to the process or function of making arrangements such as reservations and orders based on the selected plan, all in one go.

[0588] "Notification means" refers to methods or functions for informing the user of the information once the arrangements have been completed.

[0589] "Emotional analysis tools" refer to technologies and functions that recognize a user's emotions and reflect them in plan generation.

[0590] This invention is a system that provides personalized recommendation plans that take user emotions into consideration. The system mainly consists of a server and user terminals.

[0591] The server will be implemented using Python or other programming languages. Sentiment analysis will utilize sentiment analysis libraries (e.g., TextBlob, Natural Language Toolkit). The system will include data collection mechanisms to gather data from external sources and generate plans based on user input.

[0592] The user terminal functions as a smartphone or tablet, where the user enters their requirements. When the user enters a specific situation or mood, that data is sent to the server. The server analyzes this information using sentiment analysis tools and generates an appropriate plan based on the user's emotions.

[0593] The generated plan is notified to the user's terminal, and the user can select it. After selection, the server makes all relevant arrangements via the arrangement mechanism and notifies the user of the completed information via the notification mechanism.

[0594] For example, if a user enters "I want to relax today," the server will collect relevant data and generate prompts suggesting items and activities with relaxation effects. For instance, the generating AI model can be run using a prompt such as, "Suggest the best products based on the emotion entered by the user. The user said, 'I want to relax.'"

[0595] This allows users to receive plans and items that better suit their emotions and needs, leading to increased satisfaction.

[0596] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0597] Step 1:

[0598] The user uses a device to input their current emotions and requirements. This input data includes the user's emotions and desired activities. The entered data is organized on the device and ready to be sent to the server.

[0599] Step 2:

[0600] The server receives user data sent from the terminal. The server uses information gathering tools to retrieve relevant data from external sources. Specifically, the server queries a database via a particular API to collect the necessary information. In data processing, information related to the user's emotions is extracted.

[0601] Step 3:

[0602] The server uses emotion analysis tools to analyze the received user input data. Here, an emotion analysis library is used to classify the user's input into emotion categories. For example, if the input is "I want to relax," it will be classified into the relaxation category.

[0603] Step 4:

[0604] The server uses a plan generation mechanism to generate multiple recommended plans based on acquired data and sentiment analysis results. A generation AI model is used to create recommended plans that match specific emotions. During this process, each plan is ranked, and the optimal recommended plan is selected.

[0605] Step 5:

[0606] The generated recommended plan is sent from the server to the device. The user can review the provided plan on the device and select their preferred plan using the selection tool.

[0607] Step 6:

[0608] Once a user selects a plan, the server uses its booking system to handle all related arrangements in a single operation. Specifically, it accesses hotel and activity reservation systems and completes the necessary procedures.

[0609] Step 7:

[0610] Finally, the server uses a notification system to inform the user that the arrangements are complete. The notification is sent to the terminal, and the user can check the reservation details from their terminal.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] [Fourth Embodiment]

[0615] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0616] 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.

[0617] 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).

[0618] 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.

[0619] 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.

[0620] 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).

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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.

[0627] 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".

[0628] This invention provides a system for users to efficiently plan their trips. Users input their travel requirements on a terminal, and the entered information is sent to a server. The server collects necessary data from external sources and generates an optimal travel plan. This plan generation process creates multiple options based on information about transportation, accommodation, and activities, taking into account price, convenience, and user preferences.

[0629] The generated plans are presented to the user via the device, and the user selects the plan that best matches their preferences. This selected plan information is then sent back to the server, which uses this information to make various reservations in bulk. This includes booking transportation, hotels, and activities.

[0630] Once a reservation is complete, the server confirms the reservation details and sends a notification to the user's device. The user can then review this reservation information through the device and make changes or cancellations as needed. In this way, this embodiment significantly reduces the complexity of travel planning for users and enables efficient travel arrangements.

[0631] For example, if a user enters a request such as, "I want to plan a 3-day trip from Osaka to Sapporo, where I can enjoy sightseeing and local cuisine," the server will generate a plan by optimally combining flights, hotels, sightseeing tours, and restaurant reservations. Once the user completes their selections, all arrangements are made automatically, and a notification is sent to their device, allowing the user to enjoy their trip with peace of mind.

[0632] The following describes the processing flow.

[0633] Step 1:

[0634] The user enters their travel requirements. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and desired activities. Once the user enters this information, the terminal collects the data and sends it to the server.

[0635] Step 2:

[0636] The server collects data from external sources based on the received travel requirements. It sends API requests to transportation databases, accommodation booking sites, activity information sites, and other similar resources. The collected information is then organized to be used as material for generating travel plans.

[0637] Step 3:

[0638] The server uses collected data and a generative AI model to generate multiple travel plans to suggest to the user. These plans are scored and optimized based on price, convenience, and user preferences.

[0639] Step 4:

[0640] The terminal displays a list of travel plan options sent from the server to the user. The user reviews the displayed plans and selects the one that best suits their preferences, considering the travel dates, details, and price.

[0641] Step 5:

[0642] The user sends the selected plan information from their device to the server. Based on the selected plan, the server automatically makes reservations for various modes of transportation, accommodations, and activities in a single batch.

[0643] Step 6:

[0644] After all reservations are complete, the server generates a reservation confirmation and detailed information and sends it to the user's device. The user can then check the reservation details on the device to ensure there are no problems.

[0645] (Example 1)

[0646] 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".

[0647] Conventional travel planning systems require users to research multiple sources and make reservations individually, which is extremely time-consuming and cumbersome. Furthermore, it is difficult to present optimal options quickly during travel planning, making it challenging to improve user satisfaction. This invention aims to solve the problem of efficiently generating optimal travel plans tailored to diverse travel requirements and automatically executing all necessary arrangements in a user-friendly manner.

[0648] 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.

[0649] In this invention, the server includes means for acquiring information from an external data source based on received travel requirements, means for generating multiple travel plans using a generative AI model, and means for executing various arrangements in a batch based on the travel plan selected by the user. This allows the user to centrally and efficiently acquire all the information necessary for their itinerary and easily utilize an optimized travel plan.

[0650] A "terminal device" is a device used by a user to input travel requirements and send that information to a server.

[0651] A "server system" is a computer system that retrieves relevant information from an external data source based on travel requirements received from a user.

[0652] The "plan generation method" is a function that analyzes acquired information and generates multiple travel plans to provide to the user using a generation AI model.

[0653] "Interface means" refers to a user interface that allows users to make selections from generated travel plans.

[0654] A "booking system" is a system that allows for the simultaneous execution of all necessary arrangements based on the selected travel plan.

[0655] "Communication means" refers to a communication function used to notify the user that arrangements have been completed.

[0656] "External data sources" refer to external systems and services used to obtain information such as transportation, accommodation, and activities.

[0657] "Generative AI models" refer to artificial intelligence technology used to generate optimal travel plans based on diverse travel requirements.

[0658] This invention is an information processing system aimed at improving the efficiency of travel planning, and consists of the following elements.

[0659] First, the user uses a device to enter their travel requirements. This device can be any device capable of inputting information, such as a computer, smartphone, or tablet. The device provides an interface for the user to input information such as their departure point, destination, travel duration, activities, and budget.

[0660] The terminal sends this entered information to the server. The server accesses external data sources via the information and communication network to collect data on transportation, accommodation, and activities. This includes utilizing external APIs and web services. For example, it may obtain flight information from airline APIs or accommodation information from hotel booking website APIs.

[0661] Subsequently, the server analyzes the collected data using a generative AI model and generates multiple travel plans for the user. The generative AI model has the ability to create multiple optimized plans that take into account the user's preferences and constraints. The generated plans offer a variety of options based on price, time efficiency, and the user's intended use, providing the best choice.

[0662] As a concrete example, suppose a user enters the prompt message, "I want to visit a resort with my family on the weekend two weeks from now and enjoy local activities." Based on this request, the server generates a travel plan combining family-friendly transportation, suitable accommodations, and popular activities. This information is presented to the user via the terminal, allowing the user to select the most suitable plan.

[0663] When a user selects a travel plan, the device sends that information to the server, which then executes all necessary arrangements based on the selected plan. This includes booking flights, accommodations, and activities. After the bookings are complete, the server verifies the details and sends a notification to the device, providing the user with the necessary information. This entire process allows users to plan and execute their trips efficiently and without hassle.

[0664] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0665] Step 1:

[0666] The user enters their travel requirements using a terminal. The terminal receives input such as departure point, destination, travel duration, budget, and activities. This data is formatted as overall foundational information for travel planning and sent to the server.

[0667] Step 2:

[0668] The terminal sends the entered travel requirements to the server. The server receives this data and prepares requests to retrieve data from the necessary external sources. This process involves constructing and sending API requests.

[0669] Step 3:

[0670] The server collects necessary information from external data sources. The server accesses each external data source to retrieve information on transportation, accommodation, and activities. Specifically, it obtains flight information from airline APIs and hotel information from accommodation booking site APIs, and stores this information in a database.

[0671] Step 4:

[0672] The server generates travel plans using a generative AI model. The server inputs collected data into the generative AI model and creates multiple travel plans to suggest to the user based on this data. The data calculations performed include price comparison, duration calculation, and matching with the user's preferences. The generated plans are then adjusted to each have distinct characteristics.

[0673] Step 5:

[0674] The server generates travel plans and sends them to the device. The device then displays these plans for the user to view. The user can review each plan and select the one that best suits their needs.

[0675] Step 6:

[0676] The user selects the optimal travel plan and sends that information to the server using their device. The server receives this selection information and prepares the data for the next step.

[0677] Step 7:

[0678] The server handles all arrangements based on the selected travel plan. The server sends the details of the selected plan to each service provider via API, completing bookings for flights, hotels, and activities. This includes booking confirmation and payment processing.

[0679] Step 8:

[0680] The server notifies the terminal of the booking completion information. The terminal displays this information to the user, providing options for confirming the booking details and making changes or cancellations as needed. The user can then proceed with their travel preparations with peace of mind.

[0681] (Application Example 1)

[0682] 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".

[0683] Traditional travel planning systems required users to make individual bookings separately, making it difficult to efficiently integrate the entire plan. Furthermore, creating optimal travel plans tailored to user needs was challenging, making travel planning a very time-consuming and laborious task. Additionally, they lacked sufficient intuitive voice-activated operation and the provision of virtual travel experiences utilizing modern technology.

[0684] 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.

[0685] In this invention, the server includes a data input device that receives travel requirements from a user, an information gathering device that acquires information from external sources based on the received travel requirements, and a plan generation device that analyzes the acquired information and generates multiple travel plans to present to the user. This enables the creation of intuitive travel plans using voice input and allows for the provision of more convenient travel plans utilizing natural language processing.

[0686] A "data input device" is a device that has the function of receiving travel conditions and requests from users and processing them within the system.

[0687] An "information gathering device" is a device that acquires necessary data from external sources based on the received travel requirements.

[0688] A "plan generation device" is a device that analyzes collected data and creates and presents the optimal travel plan to the user.

[0689] A "selection device" is a device that allows a user to choose their preferred travel plan from among the travel plans presented.

[0690] A "reservation device" is a device that allows users to make various reservations, such as for transportation and accommodation, all at once, based on the travel plan they have selected.

[0691] A "communication device" is a device used to notify the user that their reservation has been completed.

[0692] An "input support device" is a device that receives the user's travel requirements through voice input and then performs natural language processing on them.

[0693] An "optimization algorithm" is a computational method used to evaluate and rank travel plans and select the most suitable one.

[0694] A "generative AI model" is a model that uses artificial intelligence technology to generate the optimal travel plan for a user.

[0695] The system for carrying out the present invention comprises a user, a terminal, and a server. The user uses a terminal such as a smartphone or smart glasses to input travel preferences and requirements in voice or text. On the terminal, voice recognition technology, such as Google Cloud Speech-to-Text API, is used to convert the voice data into text data. This text data is analyzed using natural language processing technology and sent to the server as travel requirements.

[0696] The server retrieves necessary information from external sources (such as the internet or databases provided by partner companies) based on the received travel requirements. Cloud services, such as Google Cloud Platform, are utilized for this information retrieval. The collected information is analyzed by optimization algorithms and generative AI models to generate an optimal travel plan tailored to the user's needs. This AI model proposes plans that match the user's preferences, budget, and schedule.

[0697] The travel plan, returned to the device, is presented to the user. The user selects their preferred plan from the multiple options presented. The details of the selected plan are sent back to the server, which then makes reservations for transportation, accommodation, and activities all at once. After the reservations are complete, the server notifies the device of the details.

[0698] For example, if a user enters a request such as, "I want to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," the system will generate a plan combining the best Shinkansen (bullet train) times, highly-rated Japanese restaurants, and hotel information. Based on the plan approved by the user, the reservation is automatically completed, and a notification is sent to the device. An example of a prompt message would be, "Please suggest a relaxing hot spring trip plan. My budget is under 100,000 yen, I want a three-night, four-day stay, and preferably a Japanese-style inn."

[0699] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0700] Step 1:

[0701] Users input their travel preferences and requirements using their smartphones or smart glasses via voice or text. The system utilizes speech recognition technology to convert voice data into text. For example, if a user says, "I'd like to enjoy Japanese food on a two-day trip from Tokyo to Kyoto," that text will appear on the device.

[0702] Step 2:

[0703] The terminal sends the converted text data to the server. The server analyzes the received text data using NLP (Natural Language Processing), a natural language processing technique, and understands it as travel requirements. Specifically, it extracts keywords such as "Tokyo," "Kyoto," "2 days," and "Japanese food" from the text.

[0704] Step 3:

[0705] The server collects relevant information from external sources based on the user's travel requirements. This information gathering utilizes the internet and partner databases via APIs. Specifically, this step retrieves information such as Shinkansen (bullet train) schedules, highly-rated Japanese restaurants, and accommodation availability.

[0706] Step 4:

[0707] The server generates multiple travel plans using optimization algorithms and generative AI models based on the collected information. As part of the data processing, it evaluates and ranks the plans based on the user's budget and schedule. Specifically, it lists the best plans that fit within the budget.

[0708] Step 5:

[0709] The device presents the user with proposed plans sent from the server. The user selects their preferred plan from the multiple options displayed on the device. Specifically, the user taps to indicate "This plan is good."

[0710] Step 6:

[0711] The selected travel plan information is sent to the server, which then makes bulk reservations for transportation and accommodation based on that information. Specifically, it accesses partner reservation services via API and automatically confirms the necessary reservations.

[0712] Step 7:

[0713] The server confirms that all reservations are complete and notifies the terminal of this completion. Users can then check the reservation details on their terminal to ensure there are no issues. Specifically, a reservation success message and detailed information will be displayed on a particular screen.

[0714] Step 8:

[0715] Users can change or cancel their reservations as needed. Actions taken on the device send a request to the server, which then processes the reservation change. For example, canceling a plan is done through a similar process.

[0716] 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.

[0717] This invention is a system that not only efficiently plans trips but also takes user emotions into account to provide a more personalized travel experience. The system includes a terminal interface for inputting travel requirements, a server-based information gathering and plan generation function, and an emotion engine to assist with plan selection and booking arrangements.

[0718] First, the user enters their travel requirements via a device. This information includes departure point, destination, travel duration, budget, and desired activities. The device then organizes this information and sends it to the server.

[0719] Based on the received requirements, the server collects the necessary data from external sources. After data collection, the plan generation function on the server generates multiple travel plans using an optimization algorithm and ranks them. A distinctive feature here is the use of an emotion engine; the server recognizes the user's emotions and reflects the results in plan generation, providing plans that match the traveler's mood and preferences.

[0720] For example, if a user expresses a desire to "relieve stress," the emotion engine can generate a plan that prioritizes activities with high relaxation and refreshing effects, as well as accommodations in lush, green spaces. The user's emotional information is derived from user input and, if necessary, other data obtained from the device.

[0721] Users select the plan that best suits them from the available options via their device. After selection, the server automatically arranges all necessary reservations based on the chosen plan. Once the reservations are complete, the server notifies the user, displaying the reservation details on their device. This emotionally conscious process not only reduces the hassle of travel arrangements but also enriches the user experience, making it more satisfying.

[0722] The following describes the processing flow.

[0723] Step 1:

[0724] The user enters their travel requirements using a terminal. The terminal provides an interface for entering information such as departure point, destination, travel duration, budget, and activities. After the user enters this information, the terminal organizes the data and sends it to the server.

[0725] Step 2:

[0726] The server collects relevant data from external sources based on the received travel requirements. Specifically, it obtains information using APIs from databases and booking sites related to flights, hotels, and tourist activities.

[0727] Step 3:

[0728] The device generates emotional data using input and, if necessary, sensor data to understand the user's emotional state. This data is sent to a server.

[0729] Step 4:

[0730] The server combines collected data with user sentiment data and generates multiple travel plans using a generative AI model. The plans are evaluated and ranked using an optimization algorithm that takes user sentiment into account. At this stage, the sentiment engine prioritizes plans that match the user's mood.

[0731] Step 5:

[0732] A travel plan generated on the device is sent from the server, and the user reviews it and selects the most preferred plan. The plan includes detailed information such as price, schedule, and accommodation information.

[0733] Step 6:

[0734] The user sends their selected travel plan to the server. Based on this selection, the server makes various reservations in a single batch (e.g., transportation tickets, hotel rooms, activity bookings).

[0735] Step 7:

[0736] Once all reservations are confirmed, the server generates a reservation confirmation and sends it to the user's device. The user then reviews the reservation details on their device, completing their travel plan.

[0737] (Example 2)

[0738] 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".

[0739] Conventional travel planning systems have struggled to provide travel plans that adequately consider users' emotions and individual needs, resulting in insufficient user satisfaction. Furthermore, the booking process after selecting a travel plan is often cumbersome, requiring considerable time and effort from the user. To address these issues, there is a need for a system that generates travel plans that take emotions into account and enables efficient booking procedures.

[0740] 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.

[0741] In this invention, the server includes an interface means for receiving travel-related information from the user, an emotion analysis means for analyzing the user's emotional state and reflecting it in the travel plan, and a travel plan generation means for generating a travel plan using optimization technology. This makes it possible to provide personalized travel plans that take into account the user's individual emotions and needs, and to efficiently arrange reservations based on the selected travel plan.

[0742] "Interface means" refers to a device or software through which a user inputs travel-related information, and through which that information is transmitted to a server.

[0743] "Data acquisition means" refers to a device or method for collecting necessary data from external sources based on information received from the user.

[0744] A "travel plan generation means" is a device or software that analyzes acquired data and creates multiple optimized travel plans according to the user's requirements.

[0745] "Selection method" refers to a method or apparatus for a user to select their preferred travel plan from the generated travel plans.

[0746] A "booking arrangement device" is a device or system that automatically performs the necessary booking procedures based on the travel plan selected by the user.

[0747] "Communication means" refers to a method or system for transmitting information to the user, such as the completion of a reservation procedure.

[0748] "Emotional analysis means" refers to a technology or device that analyzes data related to a user's emotions and reflects the results in travel plans.

[0749] The system of this invention aims to provide personalized travel plans by taking into account the user's emotions and individual needs in travel planning. An embodiment thereof is shown below.

[0750] First, the user enters travel information using a device. This device can be a smartphone or a computer, and is accessible via a dedicated application or web interface. The user enters their departure point, destination, travel duration, budget, and desired activities. This information is compiled through the interface and sent to the server.

[0751] The server uses data acquisition methods based on information received from the terminal to collect necessary information through the internet and travel-related databases. External information includes accommodation, transportation, and tourist destination information, and data is acquired in real time using APIs.

[0752] Based on the acquired information, the server activates an emotion analysis system. This involves a process that uses natural language processing technology to analyze the user's input information to determine their emotions. For example, if the user inputs "I want to relax," the emotion analysis will recommend activities to reduce stress.

[0753] Subsequently, the server uses a travel plan generation mechanism and optimization techniques (e.g., genetic algorithms) to create multiple travel plans that match the user's requests. The generated travel plans are sent to the terminal in a visually easy-to-understand format, allowing the user to select one.

[0754] For example, if the prompt is "I want to get away from the hustle and bustle of the city," sentiment analysis will generate a plan that prioritizes quiet travel destinations surrounded by nature. A more specific example of a prompt would be, "Please create a travel plan that meets the following conditions: departure point is Tokyo, destination is a place surrounded by nature, travel duration is 3 days, budget is under 100,000 yen, and relaxing activities are prioritized."

[0755] Ultimately, the user selects the most suitable travel plan from the provided options. The server then automatically makes the necessary booking arrangements based on the selected travel plan using booking tools. This allows the user to prepare for their trip with minimal stress.

[0756] The above describes a specific embodiment for implementing this invention. By providing travel plans that take into account the user's emotions, a more personalized experience is realized, thereby improving user satisfaction.

[0757] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0758] Step 1:

[0759] Users enter travel information using their device. This information includes departure point, destination, travel duration, budget, and desired activities. This information is entered intuitively using forms and selection menus on the device screen. This input data is then prepared to be sent to the server in a structured format (e.g., JSON).

[0760] Step 2:

[0761] The terminal receives user input data, organizes it, and sends it to the server. Here, the data is encrypted using the HTTPS protocol to ensure security. The data sent to the server includes all travel requirements entered by the user.

[0762] Step 3:

[0763] The server receives user travel information sent from the terminal. Based on this information, it uses data acquisition methods to collect necessary external data from the internet and travel-related databases. Specifically, the server issues API requests, retrieves response data in real time, and stores it. The collected data includes information on accommodations and tourist attractions at the travel destination.

[0764] Step 4:

[0765] The server uses the collected data and user input to activate the sentiment analysis system. Here, natural language processing techniques are used to analyze the user's emotions. Based on the input (e.g., "I want to relax"), the system identifies the user's emotional state and prepares the results for use in the next step.

[0766] Step 5:

[0767] The server drives the travel plan generation mechanism using the results of sentiment analysis and collected data. It utilizes a generative AI model to process input data using an optimization algorithm (e.g., a genetic algorithm) and generate multiple travel plans. Each generated travel plan is adjusted to match the user's identified emotional state and then ranked.

[0768] Step 6:

[0769] The server sends the generated travel plan to the device. The device displays the travel plan to the user in a visually easy-to-understand format (e.g., map or schedule). At this time, the device presents the travel plan with a user interface designed to allow the user to easily compare and select options.

[0770] Step 7:

[0771] The user selects their preferred travel plan from those presented on the device. The information of the selected travel plan is then sent back to the server. If a selection is made at this stage, preparations for the next steps proceed based on that travel plan.

[0772] Step 8:

[0773] The server activates the booking system based on the selected travel plan and automatically makes the necessary bookings. At this stage, the server collaborates with external systems to make reservations for accommodations and activities. Booking information is recorded for later notifications.

[0774] Step 9:

[0775] After the server confirms the completion of the reservation, it sends the details to the device. The device then displays the details of the completed reservation to the user. At this time, detailed information is provided via confirmation email or in-app notification to give the user peace of mind.

[0776] (Application Example 2)

[0777] 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".

[0778] Traditional recommendation systems have struggled to provide personalized services that cater to users' emotions and individual needs. As a result, users often feel that the products and services offered do not suit their mood or circumstances, leading to decreased satisfaction.

[0779] 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.

[0780] In this invention, the server includes input means for receiving requirements from the user, information gathering means for acquiring data from external information sources, and sentiment analysis means for reflecting the user's emotions in plan generation. This makes it possible to provide personalized plans based on the user's emotions.

[0781] An "input means" is a device or interface for receiving requirements or instructions from the user.

[0782] "Information gathering means" refers to the processes and functions for obtaining necessary data from external databases and information sources.

[0783] The "plan generation method" is a function that creates multiple recommended plans to provide to the user based on the acquired data.

[0784] "Selection method" refers to an interface or function that allows a user to choose the plan they want from the options provided.

[0785] "Arrangement method" refers to the process or function of making arrangements such as reservations and orders based on the selected plan, all in one go.

[0786] "Notification means" refers to methods or functions for informing the user of the information once the arrangements have been completed.

[0787] "Emotional analysis tools" refer to technologies and functions that recognize a user's emotions and reflect them in plan generation.

[0788] This invention is a system that provides personalized recommendation plans that take user emotions into consideration. The system mainly consists of a server and user terminals.

[0789] The server will be implemented using Python or other programming languages. Sentiment analysis will utilize sentiment analysis libraries (e.g., TextBlob, Natural Language Toolkit). The system will include data collection mechanisms to gather data from external sources and generate plans based on user input.

[0790] The user terminal functions as a smartphone or tablet, where the user enters their requirements. When the user enters a specific situation or mood, that data is sent to the server. The server analyzes this information using sentiment analysis tools and generates an appropriate plan based on the user's emotions.

[0791] The generated plan is notified to the user's terminal, and the user can select it. After selection, the server makes all relevant arrangements via the arrangement mechanism and notifies the user of the completed information via the notification mechanism.

[0792] For example, if a user enters "I want to relax today," the server will collect relevant data and generate prompts suggesting items and activities with relaxation effects. For instance, the generating AI model can be run using a prompt such as, "Suggest the best products based on the emotion entered by the user. The user said, 'I want to relax.'"

[0793] This allows users to receive plans and items that better suit their emotions and needs, leading to increased satisfaction.

[0794] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0795] Step 1:

[0796] The user uses a device to input their current emotions and requirements. This input data includes the user's emotions and desired activities. The entered data is organized on the device and ready to be sent to the server.

[0797] Step 2:

[0798] The server receives user data sent from the terminal. The server uses information gathering tools to retrieve relevant data from external sources. Specifically, the server queries a database via a particular API to collect the necessary information. In data processing, information related to the user's emotions is extracted.

[0799] Step 3:

[0800] The server uses emotion analysis tools to analyze the received user input data. Here, an emotion analysis library is used to classify the user's input into emotion categories. For example, if the input is "I want to relax," it will be classified into the relaxation category.

[0801] Step 4:

[0802] The server uses a plan generation mechanism to generate multiple recommended plans based on acquired data and sentiment analysis results. A generation AI model is used to create recommended plans that match specific emotions. During this process, each plan is ranked, and the optimal recommended plan is selected.

[0803] Step 5:

[0804] The generated recommended plan is sent from the server to the device. The user can review the provided plan on the device and select their preferred plan using the selection tool.

[0805] Step 6:

[0806] Once a user selects a plan, the server uses its booking system to handle all related arrangements in a single operation. Specifically, it accesses hotel and activity reservation systems and completes the necessary procedures.

[0807] Step 7:

[0808] Finally, the server uses a notification system to inform the user that the arrangements are complete. The notification is sent to the terminal, and the user can check the reservation details from their terminal.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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."

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] The following is further disclosed regarding the embodiments described above.

[0831] (Claim 1)

[0832] An input means for receiving travel requirements from the user,

[0833] Information gathering means that obtain data from external sources based on received travel requirements,

[0834] A plan generation means that analyzes acquired data and generates multiple travel plans to provide to the user,

[0835] A selection method in which the user makes a choice from the generated travel plan,

[0836] A booking method that allows you to make various reservations in one go based on the selected travel plan,

[0837] A notification method to inform the user that the reservation has been completed,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, which receives requirements from a user regarding origin, destination, travel duration, budget, and activities.

[0841] (Claim 3)

[0842] The system according to claim 1, which evaluates and ranks acquired data using an optimization algorithm to generate a travel plan.

[0843] "Example 1"

[0844] (Claim 1)

[0845] A terminal means for receiving travel requirements from a user,

[0846] A server means that obtains information from an external data source based on the received travel requirements,

[0847] A plan generation means that analyzes acquired information and generates multiple travel plans to provide to the user using a generation AI model,

[0848] An interface means for the user to make selections from the generated travel plans,

[0849] A booking method that executes various arrangements in one go based on the selected travel plan,

[0850] A means of communication to notify the user that the arrangements have been completed,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, which receives requirements from a user regarding the starting point, destination, travel period, schedule, and activities.

[0854] (Claim 3)

[0855] The system according to claim 1, which evaluates and ranks acquired information using an optimization algorithm to generate a travel plan.

[0856] "Application Example 1"

[0857] (Claim 1)

[0858] A data entry device that receives travel requirements from the user,

[0859] An information gathering device that acquires information from external sources based on received travel requirements,

[0860] A plan generation device that analyzes acquired information and generates multiple travel plans to present to the user,

[0861] A selection device that allows the user to make a selection from the generated travel plan,

[0862] A reservation system that makes various reservations in one go based on the selected travel plan,

[0863] A communication device that notifies the user that the reservation has been completed,

[0864] An input assistance device that receives user requirements via voice input and generates a plan based on natural language processing,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, which receives requirements from a user regarding the starting point, destination, travel period, budget, and activities, and provides the user with a plan using a virtual display.

[0868] (Claim 3)

[0869] The system according to claim 1, which evaluates and ranks acquired information using an optimization algorithm and proposes a plan using a generated AI model.

[0870] "Example 2 of combining an emotion engine"

[0871] (Claim 1)

[0872] An interface means for receiving travel-related information from the user,

[0873] A data acquisition method that obtains external information based on the received information,

[0874] A travel plan generation means that analyzes acquired data and generates multiple travel plans using optimization technology,

[0875] A selection method in which the user makes a choice from the generated travel plan,

[0876] Based on the selected travel plan, a booking system that automates various procedures,

[0877] A communication method to notify the user that the reservation arrangement has been completed,

[0878] A means of analyzing the user's emotional state and reflecting it in travel plans,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] The system according to claim 1, which receives information from a user regarding the origin, destination, duration of travel, budget, and activities.

[0882] (Claim 3)

[0883] The system according to claim 1, which optimizes acquired data, performs evaluation and ranking that takes emotional states into account, and generates travel plans.

[0884] "Application example 2 when combining with an emotional engine"

[0885] (Claim 1)

[0886] An input means for receiving requirements from the user,

[0887] Information gathering means that obtain data from external sources based on received requirements,

[0888] A plan generation means that analyzes acquired data and generates multiple recommended plans to provide to the user,

[0889] A selection method for the user to choose from the generated recommended plans,

[0890] A means of making arrangements in bulk based on the selected recommended plan,

[0891] A notification method to inform the user that the arrangements have been completed,

[0892] A means of sentiment analysis that recognizes user emotions and reflects them in plan generation,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, which receives requirements from a user regarding origin, destination, duration, budget, and activities.

[0896] (Claim 3)

[0897] The system according to claim 1, which evaluates and ranks acquired data using an optimization algorithm, and further generates an optimal plan based on the user's emotions using emotion analysis means. [Explanation of Symbols]

[0898] 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. An input means for receiving travel requirements from the user, Information gathering means that obtain data from external sources based on received travel requirements, A plan generation means that analyzes acquired data and generates multiple travel plans to provide to the user, A selection method in which the user makes a choice from the generated travel plan, A booking method that allows you to make various reservations in one go based on the selected travel plan, A notification method to inform the user that the reservation has been completed, A system that includes this.

2. The system according to claim 1, which receives requirements from a user regarding the origin, destination, number of travel days, budget, and activities.

3. The system according to claim 1, which evaluates and ranks acquired data using an optimization algorithm to generate a travel plan.

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