system

Abstract

We provide the system. [Solution] A user interface for entering desired travel conditions, An analysis means for analyzing travel preferences obtained through the user interface, A plan generation means that automatically generates a travel plan based on the analysis results obtained by the aforementioned analysis means, A display means for displaying the travel plan generated by the plan generation means, A booking method for making travel reservations based on the aforementioned travel plan, A system that includes this.

Description

Technical Field

[0005]

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional travel planning, it is necessary for the user to manually check the budget, destination, type of meal, etc. that the user desires and complete the reservation individually, which is a very laborious and time-consuming problem. Furthermore, there are few systems that automatically generate a travel plan that optimally reflects the user's wishes, and it has been difficult to improve the user's travel experience. The present invention aims to solve these problems.

Means for Solving the Problems

[0005] The present invention solves the above problems with a system that includes the following means: It provides a user interface in which the user inputs their desired travel conditions and has an analysis means for analyzing those desired conditions. It includes a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means, and further includes a display means for displaying the generated travel plan. In addition, it has a reservation means for making actual travel reservations based on the travel plan, thereby significantly reducing the effort and time required for travel planning. Furthermore, the reservation means also includes a means for notifying the user of reservation information on the day of travel, thereby improving the user's travel experience. The analysis means can accurately analyze the desired conditions input by the user by using natural language processing technology.

[0006] A "user interface for entering travel preferences" is an interface that allows users to input their travel preferences, such as budget, destination, and food preferences, into the system in text or other formats.

[0007] "Analysis means" refers to a software module or hardware device that analyzes the travel preferences entered by the user and extracts necessary information based on that analysis.

[0008] A "plan generation means" is an algorithm or software module that automatically generates a travel plan that meets the user's preferences based on the analysis results obtained by the analysis means.

[0009] "Display means" refers to a display device or interface for visually presenting the travel plan generated by the plan generation means to the user.

[0010] "Reservation methods" refer to online systems or API integration functions that allow users to make necessary reservations (e.g., transportation tickets or hotel reservations) based on the generated travel plan.

[0011] "Means of notifying users on the day of travel" refers to communication methods and notification systems used to inform users of necessary reservation information, details of transportation, and check-in information for accommodations on the day of travel.

[0012] "Natural language processing technology" refers to the techniques and algorithms used by computers to analyze text entered by users in natural language and understand its meaning. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] 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] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] [[ID=2,3]] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] 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).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0035] Basic System Configuration

[0036] The system includes a user interface for the user to input their travel preferences, an analysis means for analyzing the input information, a plan generation means for generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, and a reservation means for making reservations. Furthermore, it also includes a means for notifying the user of travel information for the day.

[0037] User input

[0038] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might enter text such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0039] Data analysis

[0040] The server receives input data from the user and performs analysis using natural language processing techniques. Specifically, it analyzes the text and extracts important information such as budget, destination, and desired food.

[0041] Travel plan generation

[0042] The server's plan generation system automatically generates travel plans based on analysis results. This plan generation includes a function to search for the most suitable candidates from databases the system partners with (airlines, railway companies, hotels, restaurants, etc.). For example, it generates a plan that combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market based on the acquired information.

[0043] Presentation of the plan

[0044] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0045] Reservation operation

[0046] Based on the plan presented, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0047] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0048] Travel Guide

[0049] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0050] Specific example

[0051] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0052] 1. The analysis method extracts "100,000 yen," "Tokyo," and "sushi" from the text.

[0053] 2. The plan generation method collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate travel plans.

[0054] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0055] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0056] 5. The server uses the reservation method to complete the reservation in cooperation with the partner Shinkansen reservation system and hotel reservation system.

[0057] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0058] As described above, the system of the present invention allows users to easily and quickly create travel plans and make all reservations seamlessly.

[0059] The following describes the processing flow.

[0060] Step 1:

[0061] The user accesses the chat interface and enters their travel preferences. Specifically, they enter their budget, destination, and desired food in text format. For example, they might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0062] Step 2:

[0063] The terminal sends user input data to the server. The input data is sent to the server as an HTTP request. The data is composed of JSON or text format.

[0064] Step 3:

[0065] The server receives input data from the user and passes it to the analysis tool. The analysis tool uses natural language processing technology to extract important information from the input data. Specifically, it extracts keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[0066] Step 4:

[0067] The server's plan generation mechanism automatically generates travel plans based on analysis results obtained from the analysis mechanism. This includes searching and retrieving the most suitable candidates from affiliated databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares.

[0068] Step 5:

[0069] The server generates a travel plan (for example, Shinkansen bullet train tickets, a business hotel in Ginza, and three sushi restaurants around Tsukiji Market), converts it into data for display, and sends it to the terminal. The display data is in JSON format.

[0070] Step 6:

[0071] The device displays the received travel plan on the user interface. The user can then check the specific plan details via the chat interface.

[0072] Step 7:

[0073] Based on the plan presented, the user selects the necessary booking actions. Specifically, they select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0074] Step 8:

[0075] The device sends the user's selection to the server. The selection is sent to the server as an HTTP request in JSON format.

[0076] Step 9:

[0077] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API and sends the necessary information to execute the reservation.

[0078] Step 10:

[0079] The server receives the reservation confirmation and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[0080] Step 11:

[0081] The terminal displays the reservation confirmation result on the user interface and notifies the user. The user confirms that the reservation is complete.

[0082] Step 12:

[0083] On the day of travel, the server notifies the user of travel details (e.g., Shinkansen departure time, hotel check-in information, sushi restaurant map and operating hours). Notifications are sent via SMS, email, or a chat interface.

[0084] Step 13:

[0085] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[0086] (Example 1)

[0087] 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."

[0088] Traditional travel booking systems had a complex process for users to input their travel preferences, making it difficult to quickly and efficiently generate travel plans that met their needs. Furthermore, the need to use multiple booking sites meant users had to go through the process of making individual reservations, which was time-consuming. Additionally, the lack of adequate advance notification of travel-related information meant that users were unable to enjoy their trips smoothly.

[0089] 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.

[0090] In this invention, the server includes an information analysis means for analyzing travel preferences obtained through a user interface, a plan generation means for automatically generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, a reservation means for making reservations, and a search means for searching for the best candidate from affiliated information sources and constructing a travel plan. This allows users to easily and quickly create a travel plan and make all reservations seamlessly. Furthermore, by notifying users of detailed information on the day of travel in advance, users can enjoy their trip smoothly.

[0091] A "user interface" is the interface through which a user interacts with a system and inputs their travel preferences.

[0092] "Information analysis means" refers to a means of analyzing travel preferences obtained through a user interface and extracting important information.

[0093] A "plan generation means" is a means for automatically generating a travel plan based on the analysis results obtained by an information analysis means.

[0094] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[0095] "Reservation method" refers to the means of making travel reservations based on a travel plan.

[0096] "Search methods" refer to the means of searching for the best candidates from affiliated information sources and constructing a travel plan.

[0097] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0098] User input

[0099] First, the user enters their travel preferences. The user enters their preferences in text format using a chat interface or a dedicated application. For example, the user might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0100] Data analysis

[0101] The server receives user input data and uses analysis tools to analyze the text using natural language processing techniques. Specifically, it uses NLP libraries (e.g., spaCy, NLTK) to extract important information such as "100,000 yen," "Tokyo," and "sushi." This analysis clarifies the user's desired conditions.

[0102] Travel plan generation

[0103] Next, the server's plan generation mechanism automatically generates a travel plan based on the analysis results. To do this, the server obtains data from multiple partner information sources (e.g., airline databases, hotel reservation systems, restaurant information) via APIs. Specifically, it obtains Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market, and combines them to construct the optimal travel plan.

[0104] Presentation of the plan

[0105] The generated travel plan is sent from the server to the device. The device displays the received plan to the user. The user can review this plan through a chat interface or application.

[0106] Reservation operation

[0107] Based on the presented travel plan, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking." The terminal sends the user's selection information to the server, which then uses the booking method to complete the booking in conjunction with partner booking systems (e.g., Shinkansen booking API, hotel booking API).

[0108] Travel Guide

[0109] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0110] Specific example

[0111] As a concrete example, here's how the system would handle a user who enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface:

[0112] 1. The user enters the text "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface.

[0113] 2. The server analyzes this received text using an NLP library and extracts the information "100,000 yen," "Tokyo," and "sushi."

[0114] 3. The server retrieves Shinkansen (bullet train) operation information, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market from partner APIs, and generates the optimal travel plan based on this information.

[0115] 4. The server sends the generated travel plan to the terminal, and the terminal displays the plan to the user.

[0116] 5. The user makes a reservation based on the plan, and the device sends the selection information to the server.

[0117] 6. The server uses the reservation method to complete the reservation in cooperation with the partner reservation system.

[0118] 7. On the day of travel, the server will notify the user of detailed travel information to support a smooth trip.

[0119] This invention allows users to easily and quickly plan their trips through a series of operations and make all reservations seamlessly. Furthermore, detailed information for the day of travel is provided in advance, allowing users to enjoy their trip with peace of mind.

[0120] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0121] Step 1:

[0122] The user enters their travel preferences into the chat interface.

[0123] Specific actions: The user opens a browser or mobile app, enters text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" into the chat interface, and clicks the send button.

[0124] Input: Text information entered by the user.

[0125] Output: Text data containing the user's desired conditions.

[0126] Step 2:

[0127] The server receives input data sent from the user.

[0128] Specific operation: The server receives the user's input data as an HTTP request and begins processing to parse its contents.

[0129] Input: HTTP request sent by the user.

[0130] Output: A string containing the user's input data.

[0131] Step 3:

[0132] The server uses analysis tools to analyze the text using natural language processing techniques.

[0133] Specific operation: The server uses an NLP library (e.g., spaCy, NLTK) to extract the keywords "100,000 yen," "Tokyo," and "sushi" from the text.

[0134] Input: User-input text data.

[0135] Output: Extracted keyword information (e.g., "100,000 yen", "Tokyo", "sushi").

[0136] Step 4:

[0137] The server's plan generation mechanism automatically generates a travel plan based on the analysis results.

[0138] Specific operation: The server calls APIs it partners with (e.g., travel agency API, hotel booking API) and builds the optimal travel plan based on the information obtained. Specifically, it combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market.

[0139] Input: Extracted keyword information.

[0140] Output: Detailed data of an automatically generated travel plan.

[0141] Step 5:

[0142] The server sends the details of the generated travel plan to the user interface.

[0143] Specific operation: The server converts the generated travel plan into JSON format and sends it to the frontend.

[0144] Input: Detailed data of the travel plan.

[0145] Output: Travel plan converted to JSON format.

[0146] Step 6:

[0147] The terminal receives data from the server and displays it in the user interface.

[0148] Specific operation: The device (browser or mobile app) parses the JSON data received from the server and displays it in the user interface.

[0149] Input: JSON data received from the server.

[0150] Output: A screen display of the travel plan that the user can view.

[0151] Step 7:

[0152] The user reviews the presented travel plan and selects the necessary booking actions.

[0153] Specific actions: The user selects "Shinkansen ticket reservation" and "Hotel reservation" from the chat interface or reservation button, and then presses the submit button.

[0154] Input: Travel plan selection information.

[0155] Output: User-selected reservation details.

[0156] Step 8:

[0157] The terminal sends the user's selection to the server.

[0158] Specific operation: The terminal generates an HTTP request containing the user's selection information and sends it to the server.

[0159] Input: User selection information.

[0160] Output: HTTP request sent to the server.

[0161] Step 9:

[0162] The server uses the reservation method and completes the reservation in cooperation with partner reservation sites and services.

[0163] Specific operation: The server calls a reservation API (e.g., Shinkansen reservation API, hotel reservation API) and executes the reservation process.

[0164] Input: User selection information.

[0165] Output: Confirmed reservation information.

[0166] Step 10:

[0167] The server will notify the user of detailed information for the day of the trip.

[0168] Specific operation: The server generates a notification message containing information such as the Shinkansen departure time, hotel check-in information, and a map of a sushi restaurant, and sends it to the user.

[0169] Input: Confirmed reservation information.

[0170] Output: A notification message containing detailed information for the day of travel.

[0171] (Application Example 1)

[0172] 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."

[0173] In recent years, users have a growing need to efficiently plan and consume not only travel but also video content. However, current systems cannot integrate travel planning with content recommendations and scheduling. As a result, users must plan each piece of content individually, which is a time-consuming and laborious process. Therefore, there is a need for a system that, based on the user's input preferences, recommends content to watch and automatically generates a viewing schedule, in addition to providing travel plans.

[0174] 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.

[0175] In this invention, the server includes a user interface means for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation means for making a travel reservation based on the travel plan, a means for obtaining recommended content based on the desired travel conditions, and a means for generating a viewing schedule based on the recommended content. This makes it possible for the user to generate a travel plan, recommend viewing content, and generate a viewing schedule in an integrated manner, significantly reducing the effort required for planning.

[0176] "Travel preferences" refer to the various conditions that users desire when traveling, and specifically include budget, destination, and food preferences.

[0177] A "user interface" is a means by which a user interacts with a system and inputs or confirms information. Specific examples include chat interfaces and touchscreens.

[0178] "Analysis means" refers to a function that analyzes the desired conditions entered by the user and extracts useful information, and it is common to use natural language processing technology.

[0179] "Plan generation method" refers to a function that automatically generates travel plans and recommendations for viewing content based on analyzed preferences.

[0180] "Display means" refers to a function that presents the generated travel plan or viewing schedule to the user, and this includes displays and mobile screens.

[0181] "Reservation method" refers to a function that automatically makes necessary reservations (such as accommodation and transportation) based on the generated travel plan.

[0182] "Recommended content" refers to video content that is recommended for viewing based on the user's entered preferences.

[0183] A "viewing schedule" refers to a planned timetable designed to allow users to efficiently view recommended content.

[0184] This invention is a system that allows users to input their desired viewing conditions, automatically generates an optimal viewing plan based on those conditions, presents recommended content, and creates a viewing schedule. Embodiments of the present invention will be described in detail below.

[0185] Basic System Configuration

[0186] The system has the following main features:

[0187] 1. User Interface: A chat interface on a smartphone application or web browser will be used as a means for users to input their desired viewing conditions.

[0188] 2. Analysis method: The server uses natural language processing technology (e.g., Python's NLP library) to analyze the user's input preferences and extract important information such as budget, genre, and viewing time.

[0189] 3. Plan generation method: The server automatically generates a viewing plan based on the analysis results. To generate the viewing plan, recommended content is obtained using the API of a video content distribution service (e.g., video content distribution API), and a viewing schedule is created.

[0190] 4. Display method: The generated viewing plan will be displayed on the screen of a smartphone or computer and presented to the user visually.

[0191] User input

[0192] Users enter their viewing preferences using a chat interface. A typical prompt might be, "My budget is 5000 yen, the location is my home, and I want pizza." This interface is designed to be intuitive and allow users to easily enter their preferences.

[0193] Data analysis

[0194] The server receives input data from the user and performs analysis using natural language processing (NLP) techniques. The server uses Python's NLP library to analyze the text and extract important information such as budget, location, and desired cuisine. For example, it receives the text "My budget is 5000 yen, the location is my home, and the desired cuisine is pizza," and extracts the information for each item.

[0195] Creating a viewing plan

[0196] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation includes a function to search for the most suitable candidates using the API of a video content distribution service. For example, it generates a list of recommended movies and dramas based on the acquired information and schedules them according to viewing time.

[0197] Presentation of the plan

[0198] The server displays the details of the generated viewing plan on the user interface, and the device (smartphone or PC) presents it to the user. The user can confirm the generated plan through the chat interface.

[0199] for example,

[0200] The budget is 5000 yen, the location is my home, and the food I want to eat is pizza.

[0201] When you enter,

[0202] 1. The analysis method extracts "5000 yen," "home," and "pizza" from the text.

[0203] 2. The plan generation method uses a video content distribution service API to collect movies and dramas that can be viewed within the budget and generates a viewing schedule.

[0204] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0205] This allows users to easily and quickly create viewing plans and efficiently consume all available content.

[0206] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0207] Step 1:

[0208] The user accesses the chat interface and enters their desired viewing conditions. For example, they might enter, "My budget is 5000 yen, the location is my home, and I want pizza." This input data is then sent to the server.

[0209] Input: User's desired viewing conditions (e.g., "Budget: 5000 yen, Location: Home, Food I want to eat: Pizza")

[0210] Output: Input data is sent to the server.

[0211] Step 2:

[0212] The server analyzes the user's input data. Natural language processing techniques (e.g., Python's NLP library) are used for the analysis. Through this process, the server extracts each element of the desired conditions (budget, location, food).

[0213] Input: User viewing preferences submitted in Step 1

[0214] Processing: Use natural language processing techniques to extract budget, location, and desired cuisine.

[0215] Output: Analyzed desired conditions (e.g., budget = 5000 yen, location = home, food desired = pizza)

[0216] Step 3:

[0217] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation uses the API of the video content distribution service. Based on the acquired information, the server creates a list of movies and dramas that can be viewed.

[0218] Input: Desired conditions analyzed in Step 2

[0219] Process: Use the API of the video content distribution service to retrieve viewable content.

[0220] Output: List of recommended content (e.g., Movie A, TV series B)

[0221] Step 4:

[0222] The server generates a viewing schedule based on recommended content. The schedule is created based on the playback time of each piece of content and the user's viewing preferences.

[0223] Input: List of recommended content

[0224] Processing: Create a viewing schedule, taking into account the playback time of each piece of content.

[0225] Output: Viewing schedule (Example: 19:00 - Movie A, 21:00 - Drama B)

[0226] Step 5:

[0227] The server displays the details of the viewing plan generated by the server on the user interface, showing them on the screen of a smartphone or computer. This allows the user to check recommended content and viewing schedules.

[0228] Input: Viewing schedule

[0229] Processing: Display the viewing schedule in the user interface.

[0230] Output: Viewing schedule displayed on the user interface

[0231] Step 6:

[0232] Users can review the presented viewing plan and adjust their viewing schedule as needed. Furthermore, by initiating a viewing start, the server will coordinate with the video content distribution service and begin playback.

[0233] Input: User verification and adjustment instructions, instructions to start viewing.

[0234] Processing: Based on user instructions, adjust the viewing schedule and initiate viewing.

[0235] Output: Start playback (playback of video content)

[0236] 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.

[0237] This invention relates to a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, all while incorporating an emotion engine that recognizes and analyzes the user's emotions. Embodiments of this invention will be described in detail below.

[0238] Basic System Configuration

[0239] This system includes a user interface for users to input their travel preferences, an analysis means and emotion engine for analyzing the input information and associated emotions, a plan generation means for automatically generating a travel plan based on the analysis results and emotional state, a display means for displaying the generated travel plan, and a reservation means for making reservations based on the travel plan. Furthermore, it also includes a notification means for informing the user of travel information for the day.

[0240] User input

[0241] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might type, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0242] Data analysis

[0243] The server receives input data from the user and passes it to the analysis tool and the emotion engine. The analysis tool uses natural language processing technology to extract important information from the input data. For example, it might extract keywords such as "budget 100,000 yen," "Tokyo," and "sushi." Meanwhile, the emotion engine analyzes the user's input text and determines their emotional state, such as positive, negative, or neutral.

[0244] Travel plan generation

[0245] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. This includes searching and retrieving the most suitable candidates from partner databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares. Furthermore, it adjusts the content of the travel plan based on the user's emotional state. For example, if the emotional state is positive, it recommends a slightly more expensive restaurant, and if the emotional state is negative, it adds relaxing sightseeing spots.

[0246] Presentation of the plan

[0247] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0248] Reservation operation

[0249] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0250] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0251] Travel Guide

[0252] On the day of travel, the server notifies the user of detailed travel information (e.g., Shinkansen departure time, hotel check-in information, map to recommended sushi restaurant, etc.). This allows the user to enjoy their trip with peace of mind.

[0253] Specific example

[0254] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0255] 1. The analysis tool extracts "100,000 yen," "Tokyo," and "sushi" from the text. Meanwhile, the emotion engine analyzes the positive emotion of "enjoyment."

[0256] 2. The plan generation system collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate a travel plan. Based on the results of the emotion engine, it proposes a plan that includes a special dinner course.

[0257] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0258] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0259] 5. The server uses the reservation method to coordinate with the Shinkansen reservation system and the hotel reservation system to complete the reservation.

[0260] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0261] As described above, the system of the present invention allows users to easily and quickly plan their trips and provides them with a unique experience that takes their emotions into consideration.

[0262] The following describes the processing flow.

[0263] Step 1:

[0264] The user accesses the chat interface and enters their travel preferences. For example, they might type, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0265] Step 2:

[0266] The device sends the user's input data to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[0267] Step 3:

[0268] The server receives input data from the user and passes it to the analysis unit and the emotion engine. The analysis unit then passes the input data to the natural language processing engine.

[0269] Step 4:

[0270] The server's analysis tools extract important information from the input data. For example, it might extract the keywords "budget 100,000 yen," "Tokyo," and "sushi" from the input text.

[0271] Step 5:

[0272] The server's emotion engine analyzes the input data and determines the user's emotional state. For example, the emotion engine might analyze the input text to identify a positive emotion such as "enjoyment."

[0273] Step 6:

[0274] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. Specifically, it searches for the best candidates from partner databases (information on airlines, railway companies, hotels, and restaurants) and adjusts the plan content based on the user's emotional state.

[0275] Step 7:

[0276] The server converts the travel plan details it generates into display data and sends it to the terminal. The display data is in JSON format.

[0277] Step 8:

[0278] The device displays the received travel plan in the chat interface. The user can then review the specific plan details.

[0279] Step 9:

[0280] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0281] Step 10:

[0282] The terminal sends the user's selection to the server. The selection data is sent to the server as an HTTP request in JSON format.

[0283] Step 11: <I

[0284] The server uses the reservation means to make reservations for the bullet train and the hotel. Specifically, it calls the bullet train reservation API and the hotel reservation API, sends the necessary information, and completes the reservation.

[0285] Step 12:

[0286] The server receives the reservation confirmation result and sends the result to the terminal. The reservation details and the confirmed detailed information are sent in JSON format.

[0287] Step 13:

[0288] The terminal displays the reservation confirmation result on the chat interface and notifies the user. The user can confirm the completion of the reservation.

[0289] Step 14:

[0290] On the day of the trip, the server notifies the user of the trip details. For example, it notifies the departure time of the bullet train, the check-in information of the accommodation hotel, and the map and business information of the recommended sushi restaurants. The notification is made via SMS, email, or the chat interface.

[0291] Step 15:

[0292] The user can check the information necessary on the day of the trip and enjoy the trip with peace of mind.

[0293] (Example 2)

[0294] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0295] Conventional automated travel plan generation systems could provide plans based on user preferences, but they struggled to provide plans that took into account the user's emotional state at that moment. As a result, they were unable to provide the ideal travel experience that users envisioned, and thus failed to increase user satisfaction.

[0296] 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.

[0297] In this invention, the server includes a user interface means for inputting travel preferences, an analysis means including an emotion engine for analyzing the user's emotions, and a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotion engine. This makes it possible to provide a travel plan that takes into account both the user's preferences and emotional state.

[0298] A "user interface" is the interface through which a user enters their travel preferences.

[0299] "Analysis means" refers to a device or program that analyzes travel preferences obtained through a user interface.

[0300] An "emotion engine" is a technology that analyzes user input data to determine emotions and identify emotional states such as positive, negative, or neutral.

[0301] "Plan generation means" refers to a device or program that automatically generates a travel plan based on the analysis results obtained by the analysis means and the emotion engine.

[0302] "Display means" refers to a device or program that visualizes and displays the generated travel plan to the user.

[0303] A "booking method" refers to a device or program that makes an actual travel reservation based on a generated travel plan.

[0304] The "database" is an information aggregation system for collecting and managing information necessary for generating travel plans.

[0305] The "natural language processing technology" is a technology for analyzing text data input by a user and understanding its content.

[0306] The "notification means" is a device or program for notifying a user of detailed travel-related information on the day of travel.

[0307] The present invention is a system that inputs a user's travel wish conditions, automatically generates and presents a travel plan based on them, makes necessary reservations, and further combines an emotion engine that recognizes and analyzes the user's emotions.

[0308] The system is configured as follows. First, the user uses a user interface for inputting travel wish conditions. In the user interface, the wish conditions are input in a chat format that allows text input. For example, a prompt sentence such as "The budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" is input.

[0309] Next, this input data is sent to the server. After receiving the data, the server processes the data using analysis means and an emotion engine. Natural language processing technology (for example, Google (registered trademark) Cloud Natural Language API) is used for the analysis means. This technology extracts important information from the user's input text, for example, extracting keywords such as "budget 100,000 yen", "Tokyo", and "sushi".

[0310] The emotion engine analyzes the emotional state from the user's input text (for example, IBM Watson (registered trademark) Tone Analyzer), and thereby determines whether the user is in a positive, negative, neutral, or other emotional state. For example, a positive emotion such as "looking forward to" is analyzed from the input text.

[0311] Next, the server's plan generation mechanism automatically generates a travel plan based on the analyzed data and emotional state. The plan generation mechanism retrieves travel-related information from partner databases (e.g., travel agency databases, transportation databases, accommodation databases) and creates the optimal travel plan. For example, it collects information such as "bullet train operating times and fares," "hotel information," and "sushi restaurant information," and generates a plan that includes high-end restaurants based on a positive emotional state.

[0312] The generated travel plan is sent from the server to the user interface and displayed to the user via their device. The user can review the presented plan and select the necessary booking actions from the chat interface. For example, they can select "Shinkansen ticket booking" and "hotel booking."

[0313] Once the user has made their selection, the server uses the booking method to connect with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) and make the actual booking. Specifically, it accesses the Shinkansen (bullet train) booking system to reserve a ticket for the specified date and time, and similarly reserves a hotel.

[0314] Finally, on the day of travel, the server notifies the user of detailed travel information. For example, it sends the user the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant via the smartphone's notification function. This allows the user to enjoy their trip with peace of mind.

[0315] Thus, the system of the present invention allows users to easily and quickly plan their trips and to provide them with a unique experience that takes their emotions into consideration.

[0316] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0317] Step 1:

[0318] The user enters their travel preferences through a chat interface. Specifically, they enter prompts such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The input data obtained is "budget 100,000 yen," "Tokyo," and "sushi."

[0319] Step 2:

[0320] The terminal sends user input data to the server. The server receives this data and passes it on to the analysis tools and emotion engine. As input data, text obtained from the user interface is sent to the server.

[0321] Step 3:

[0322] The server's analysis method uses natural language processing technology (e.g., Google Cloud Natural Language API) to extract important information from the input data. Specifically, "budget of 100,000 yen," "Tokyo," and "sushi" are extracted. The extracted keywords are obtained as output data.

[0323] Step 4:

[0324] The server's emotion engine analyzes the user's input text and determines their emotional state (e.g., IBM Watson Tone Analyzer). Specifically, a positive emotion like "enjoyment" is analyzed. The analyzed emotional state is obtained as output data.

[0325] Step 5:

[0326] The server's plan generation mechanism generates an optimal travel plan based on input data (keywords and emotional states) obtained from the analysis mechanism and the emotion engine. It collects information such as "Shinkansen train schedules and fares," "hotel information," and "sushi restaurant information" from a partner database, and generates a plan including high-end restaurants based on positive emotional states. The generated travel plan is obtained as output data.

[0327] Step 6:

[0328] The server generates a travel plan and sends it to the user interface, which the terminal displays to the user. The user can then view the plan details on the user interface. The generated travel plan is sent to the user interface as input data.

[0329] Step 7:

[0330] The user reviews their travel plan via a chat interface and selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking." The user's booking selections are obtained as input data.

[0331] Step 8:

[0332] The terminal sends the user's selection to the server, which then coordinates with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) to make the actual booking. The Shinkansen (bullet train) and hotel bookings are completed. The booking completion information is provided as output data.

[0333] Step 9:

[0334] On the day of travel, the server notifies the user of detailed travel information. Specifically, this includes the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant. Detailed travel plan information is stored on the server as input data.

[0335] Through these steps, users can easily and quickly create travel plans based on their wishes and emotional state, make reservations, and enjoy their trip with peace of mind.

[0336] (Application Example 2)

[0337] 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".

[0338] Conventional travel plan generation systems have the functionality to generate and book travel plans based on user-inputted preferences, but they have the problem of not being able to adjust the suggested content to take into account the user's emotional state. Furthermore, even if travel plan generation and booking can be done in one go, a separate payment method is required, which is inconvenient for the user. In addition, there are insufficient means of notifying users of necessary information on the day of travel, which is an obstacle to the smooth running of the trip.

[0339] 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.

[0340] In this invention, the server includes a user interface for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions and associated emotional states obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results and emotional states obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation and payment means for making a reservation and payment for the trip in a single transaction based on the travel plan, and a notification means for displaying payment information associated with the travel plan on the user interface. This enables the proposal of a travel plan that takes the user's emotional state into consideration, and allows for a single reservation and payment. Furthermore, it enables smooth travel by quickly notifying the user of information they need on the day of the trip.

[0341] A "user interface" is the means by which a user interacts with a system and inputs their travel preferences.

[0342] "Analysis means" refers to means for analyzing travel preferences and related emotional states obtained through the user interface.

[0343] The "plan generation means" is a means for automatically generating a travel plan based on the analysis results and emotional state obtained by the analysis means.

[0344] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[0345] "Booking and payment methods" refer to the means of making a single booking and payment for a trip based on a travel plan.

[0346] "Notification methods" refer to means of notifying users of payment information related to their travel plan and detailed information for the day of travel.

[0347] "Emotional state" refers to the emotional state analyzed based on user input, and includes positive, negative, neutral, etc.

[0348] "Natural language processing technology" is a technology that analyzes text information entered by users to understand its meaning and intent.

[0349] This invention is a system that allows users to input their travel preferences, automatically generates a travel plan based on those preferences, and handles all necessary reservations and payments in a single process. Furthermore, it can promptly notify users of necessary information on the day of travel.

[0350] Basic System Configuration

[0351] The system includes the following components:

[0352] 1. User Interface: The means by which users input their travel preferences. Specifically, this refers to applications on smartphones.

[0353] 2. Analysis Method: A method for analyzing user input and extracting travel preferences and emotional states. As a specific example, natural language processing techniques implemented using the Python transformers library will be used.

[0354] 3. Plan generation means: A means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotional state. It generates a plan that combines hotels, restaurants, transportation, etc. at the travel destination and is adjusted according to the emotional state.

[0355] 4. Display means: Means for presenting the generated travel plan to the user. Specifically, the details of the plan are displayed on the smartphone application screen.

[0356] 5. Booking and Payment Methods: A method for booking and paying for travel in a single transaction based on a travel plan. A dummy API can be used, but in a real environment, it will be integrated with actual booking sites and payment systems.

[0357] 6. Notification method: A means of notifying the user of necessary information on the day of the trip.

[0358] System processing flow

[0359] The server first receives travel preferences from the user via the user interface. For example, text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" might be entered. At this time, the user's emotional state is also analyzed and classified as positive, negative, neutral, etc.

[0360] Next, the server generates a travel plan. Based on the information extracted by the analysis tools, it combines data on hotels, restaurants, and transportation options at the travel destination. If the user's emotional state is positive, suggestions are made to enhance user satisfaction, such as proposing a plan that includes a rich dinner course.

[0361] The generated travel plan is displayed on the smartphone application screen. Users can review this plan and make reservations and payments all at once. After the reservation and payment are complete, the system will notify the user in real time on the day of travel, providing all necessary information.

[0362] Specific example

[0363] For example, suppose the user entered the following:

[0364] My travel budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi. Please suggest a suitable itinerary.

[0365] In this case, the system automatically performs an analysis and extracts keywords such as "budget of 100,000 yen," "Tokyo," and "sushi," as well as positive emotions. The plan generation means then generates a plan combining the most suitable hotels, restaurants, bullet train information, etc., based on this information and presents it to the user. Once the user completes the reservation and payment, the necessary information for the day of travel is notified in a timely manner. In this way, as a form of implementing the invention, the user can create a travel plan simply and effectively.

[0366] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0367] Step 1:

[0368] Users enter their travel preferences via a smartphone application. The data entered is in text format and may include information such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The entered conditions include details about the trip, such as budget, desired destinations, and food preferences.

[0369] Step 2:

[0370] The terminal receives the user's desired conditions and sends them to the server. The server inputs the received data into an analysis device. This analysis device uses the Python transformers library to analyze the input data and extract important keywords ("Budget: 100,000 yen", "Place to go: Tokyo", "Food to eat: Sushi").

[0371] Step 3:

[0372] The server passes the data analyzed by the analysis means to the emotion state analysis engine. This engine analyzes the user's emotional state from the text obtained through the user interface. For example, if the user indicates a positive emotion such as excitement, the emotion analysis engine will determine that emotional state is "positive."

[0373] Step 4:

[0374] The server executes the plan generation means based on the information obtained from the analysis means and the sentiment analysis engine. The plan generation means accesses the database and automatically generates a travel plan based on the analyzed keywords. Specifically, it combines information on accommodations, restaurants, and bullet trains to create a plan that is adjusted according to the user's emotional state.

[0375] Step 5:

[0376] The server sends data to the display device to show the generated travel plan on the user's smartphone. The device then displays the details of the received travel plan to the user. The user interface displays a list of accommodations, restaurants, transportation, etc., included in the generated plan.

[0377] Step 6:

[0378] The user makes a reservation and payment based on the presented travel plan. The terminal receives the user's selection and sends that information to the server. The server, through the reservation and payment method, interacts with the reservation site and payment system included in the travel plan and executes the necessary reservations and payments in one go.

[0379] Step 7:

[0380] On the day of travel, the server notifies the user of payment information and other details related to the travel plan (such as Shinkansen departure times, hotel check-in information, and maps of recommended restaurants). This notification is made using the smartphone's notification function, allowing the user to receive the necessary information in real time.

[0381] 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.

[0382] 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.

[0383] 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.

[0384] [Second Embodiment]

[0385] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0386] 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.

[0387] 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).

[0388] 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.

[0389] 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.

[0390] 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).

[0391] 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.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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".

[0397] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0398] Basic System Configuration

[0399] The system includes a user interface for the user to input their travel preferences, an analysis means for analyzing the input information, a plan generation means for generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, and a reservation means for making reservations. Furthermore, it also includes a means for notifying the user of travel information for the day.

[0400] User input

[0401] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might enter text such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0402] Data analysis

[0403] The server receives input data from the user and performs analysis using natural language processing techniques. Specifically, it analyzes the text and extracts important information such as budget, destination, and desired food.

[0404] Travel plan generation

[0405] The server's plan generation system automatically generates travel plans based on analysis results. This plan generation includes a function to search for the most suitable candidates from databases the system partners with (airlines, railway companies, hotels, restaurants, etc.). For example, it generates a plan that combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market based on the acquired information.

[0406] Presentation of the plan

[0407] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0408] Reservation operation

[0409] Based on the plan presented, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0410] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0411] Travel Guide

[0412] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0413] Specific example

[0414] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0415] 1. The analysis method extracts "100,000 yen," "Tokyo," and "sushi" from the text.

[0416] 2. The plan generation method collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate travel plans.

[0417] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0418] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0419] 5. The server uses the reservation method to complete the reservation in cooperation with the partner Shinkansen reservation system and hotel reservation system.

[0420] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0421] As described above, the system of the present invention allows users to easily and quickly create travel plans and make all reservations seamlessly.

[0422] The following describes the processing flow.

[0423] Step 1:

[0424] The user accesses the chat interface and enters their travel preferences. Specifically, they enter their budget, destination, and desired food in text format. For example, they might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0425] Step 2:

[0426] The terminal sends user input data to the server. The input data is sent to the server as an HTTP request. The data is composed of JSON or text format.

[0427] Step 3:

[0428] The server receives input data from the user and passes it to the analysis tool. The analysis tool uses natural language processing technology to extract important information from the input data. Specifically, it extracts keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[0429] Step 4:

[0430] The server's plan generation mechanism automatically generates travel plans based on analysis results obtained from the analysis mechanism. This includes searching and retrieving the most suitable candidates from affiliated databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares.

[0431] Step 5:

[0432] The server generates a travel plan (for example, Shinkansen bullet train tickets, a business hotel in Ginza, and three sushi restaurants around Tsukiji Market), converts it into data for display, and sends it to the terminal. The display data is in JSON format.

[0433] Step 6:

[0434] The device displays the received travel plan on the user interface. The user can then check the specific plan details via the chat interface.

[0435] Step 7:

[0436] Based on the plan presented, the user selects the necessary booking actions. Specifically, they select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0437] Step 8:

[0438] The device sends the user's selection to the server. The selection is sent to the server as an HTTP request in JSON format.

[0439] Step 9:

[0440] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API and sends the necessary information to execute the reservation.

[0441] Step 10:

[0442] The server receives the reservation confirmation and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[0443] Step 11:

[0444] The terminal displays the reservation confirmation result on the user interface and notifies the user. The user confirms that the reservation is complete.

[0445] Step 12:

[0446] On the day of travel, the server notifies the user of travel details (e.g., Shinkansen departure time, hotel check-in information, sushi restaurant map and operating hours). Notifications are sent via SMS, email, or a chat interface.

[0447] Step 13:

[0448] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[0449] (Example 1)

[0450] 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".

[0451] Traditional travel booking systems had a complex process for users to input their travel preferences, making it difficult to quickly and efficiently generate travel plans that met their needs. Furthermore, the need to use multiple booking sites meant users had to go through the process of making individual reservations, which was time-consuming. Additionally, the lack of adequate advance notification of travel-related information meant that users were unable to enjoy their trips smoothly.

[0452] 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.

[0453] In this invention, the server includes an information analysis means for analyzing travel preferences obtained through a user interface, a plan generation means for automatically generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, a reservation means for making reservations, and a search means for searching for the best candidate from affiliated information sources and constructing a travel plan. This allows users to easily and quickly create a travel plan and make all reservations seamlessly. Furthermore, by notifying users of detailed information on the day of travel in advance, users can enjoy their trip smoothly.

[0454] A "user interface" is the interface through which a user interacts with a system and inputs their travel preferences.

[0455] "Information analysis means" refers to a means of analyzing travel preferences obtained through a user interface and extracting important information.

[0456] A "plan generation means" is a means for automatically generating a travel plan based on the analysis results obtained by an information analysis means.

[0457] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[0458] "Reservation method" refers to the means of making travel reservations based on a travel plan.

[0459] "Search methods" refer to the means of searching for the best candidates from affiliated information sources and constructing a travel plan.

[0460] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0461] User input

[0462] First, the user enters their travel preferences. The user enters their preferences in text format using a chat interface or a dedicated application. For example, the user might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0463] Data analysis

[0464] The server receives user input data and uses analysis tools to analyze the text using natural language processing techniques. Specifically, it uses NLP libraries (e.g., spaCy, NLTK) to extract important information such as "100,000 yen," "Tokyo," and "sushi." This analysis clarifies the user's desired conditions.

[0465] Travel plan generation

[0466] Next, the server's plan generation mechanism automatically generates a travel plan based on the analysis results. To do this, the server obtains data from multiple partner information sources (e.g., airline databases, hotel reservation systems, restaurant information) via APIs. Specifically, it obtains Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market, and combines them to construct the optimal travel plan.

[0467] Presentation of the plan

[0468] The generated travel plan is sent from the server to the device. The device displays the received plan to the user. The user can review this plan through a chat interface or application.

[0469] Reservation operation

[0470] Based on the presented travel plan, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking." The terminal sends the user's selection information to the server, which then uses the booking method to complete the booking in conjunction with partner booking systems (e.g., Shinkansen booking API, hotel booking API).

[0471] Travel Guide

[0472] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0473] Specific example

[0474] As a concrete example, here's how the system would handle a user who enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface:

[0475] 1. The user enters the text "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface.

[0476] 2. The server analyzes this received text using an NLP library and extracts the information "100,000 yen," "Tokyo," and "sushi."

[0477] 3. The server retrieves Shinkansen (bullet train) operation information, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market from partner APIs, and generates the optimal travel plan based on this information.

[0478] 4. The server sends the generated travel plan to the terminal, and the terminal displays the plan to the user.

[0479] 5. The user makes a reservation based on the plan, and the device sends the selection information to the server.

[0480] 6. The server uses the reservation method to complete the reservation in cooperation with the partner reservation system.

[0481] 7. On the day of travel, the server will notify the user of detailed travel information to support a smooth trip.

[0482] This invention allows users to easily and quickly plan their trips through a series of operations and make all reservations seamlessly. Furthermore, detailed information for the day of travel is provided in advance, allowing users to enjoy their trip with peace of mind.

[0483] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0484] Step 1:

[0485] The user enters their travel preferences into the chat interface.

[0486] Specific actions: The user opens a browser or mobile app, enters text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" into the chat interface, and clicks the send button.

[0487] Input: Text information entered by the user.

[0488] Output: Text data containing the user's desired conditions.

[0489] Step 2:

[0490] The server receives input data sent from the user.

[0491] Specific operation: The server receives the user's input data as an HTTP request and begins processing to parse its contents.

[0492] Input: HTTP request sent by the user.

[0493] Output: A string containing the user's input data.

[0494] Step 3:

[0495] The server uses analysis tools to analyze the text using natural language processing techniques.

[0496] Specific operation: The server uses an NLP library (e.g., spaCy, NLTK) to extract the keywords "100,000 yen," "Tokyo," and "sushi" from the text.

[0497] Input: User-input text data.

[0498] Output: Extracted keyword information (e.g., "100,000 yen", "Tokyo", "sushi").

[0499] Step 4:

[0500] The server's plan generation mechanism automatically generates a travel plan based on the analysis results.

[0501] Specific operation: The server calls APIs it partners with (e.g., travel agency API, hotel booking API) and builds the optimal travel plan based on the information obtained. Specifically, it combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market.

[0502] Input: Extracted keyword information.

[0503] Output: Detailed data of an automatically generated travel plan.

[0504] Step 5:

[0505] The server sends the details of the generated travel plan to the user interface.

[0506] Specific operation: The server converts the generated travel plan into JSON format and sends it to the frontend.

[0507] Input: Detailed data of the travel plan.

[0508] Output: Travel plan converted to JSON format.

[0509] Step 6:

[0510] The terminal receives data from the server and displays it in the user interface.

[0511] Specific operation: The device (browser or mobile app) parses the JSON data received from the server and displays it in the user interface.

[0512] Input: JSON data received from the server.

[0513] Output: A screen display of the travel plan that the user can view.

[0514] Step 7:

[0515] The user reviews the presented travel plan and selects the necessary booking actions.

[0516] Specific actions: The user selects "Shinkansen ticket reservation" and "Hotel reservation" from the chat interface or reservation button, and then presses the submit button.

[0517] Input: Travel plan selection information.

[0518] Output: User-selected reservation details.

[0519] Step 8:

[0520] The terminal sends the user's selection to the server.

[0521] Specific operation: The terminal generates an HTTP request containing the user's selection information and sends it to the server.

[0522] Input: User selection information.

[0523] Output: HTTP request sent to the server.

[0524] Step 9:

[0525] The server uses the reservation method and completes the reservation in cooperation with partner reservation sites and services.

[0526] Specific operation: The server calls a reservation API (e.g., Shinkansen reservation API, hotel reservation API) and executes the reservation process.

[0527] Input: User selection information.

[0528] Output: Confirmed reservation information.

[0529] Step 10:

[0530] The server will notify the user of detailed information for the day of the trip.

[0531] Specific operation: The server generates a notification message containing information such as the Shinkansen departure time, hotel check-in information, and a map of a sushi restaurant, and sends it to the user.

[0532] Input: Confirmed reservation information.

[0533] Output: A notification message containing detailed information for the day of travel.

[0534] (Application Example 1)

[0535] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0536] In recent years, users have a growing need to efficiently plan and consume not only travel but also video content. However, current systems cannot integrate travel planning with content recommendations and scheduling. As a result, users must plan each piece of content individually, which is a time-consuming and laborious process. Therefore, there is a need for a system that, based on the user's input preferences, recommends content to watch and automatically generates a viewing schedule, in addition to providing travel plans.

[0537] 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.

[0538] In this invention, the server includes a user interface means for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation means for making a travel reservation based on the travel plan, a means for obtaining recommended content based on the desired travel conditions, and a means for generating a viewing schedule based on the recommended content. This makes it possible for the user to generate a travel plan, recommend viewing content, and generate a viewing schedule in an integrated manner, significantly reducing the effort required for planning.

[0539] "Travel preferences" refer to the various conditions that users desire when traveling, and specifically include budget, destination, and food preferences.

[0540] A "user interface" is a means by which a user interacts with a system and inputs or confirms information. Specific examples include chat interfaces and touchscreens.

[0541] "Analysis means" refers to a function that analyzes the desired conditions entered by the user and extracts useful information, and it is common to use natural language processing technology.

[0542] "Plan generation method" refers to a function that automatically generates travel plans and recommendations for viewing content based on analyzed preferences.

[0543] "Display means" refers to a function that presents the generated travel plan or viewing schedule to the user, and this includes displays and mobile screens.

[0544] "Reservation method" refers to a function that automatically makes necessary reservations (such as accommodation and transportation) based on the generated travel plan.

[0545] "Recommended content" refers to video content that is recommended for viewing based on the user's entered preferences.

[0546] A "viewing schedule" refers to a planned timetable designed to allow users to efficiently view recommended content.

[0547] This invention is a system that allows users to input their desired viewing conditions, automatically generates an optimal viewing plan based on those conditions, presents recommended content, and creates a viewing schedule. Embodiments of the present invention will be described in detail below.

[0548] Basic System Configuration

[0549] The system has the following main features:

[0550] 1. User Interface: A chat interface on a smartphone application or web browser will be used as a means for users to input their desired viewing conditions.

[0551] 2. Analysis method: The server uses natural language processing technology (e.g., Python's NLP library) to analyze the user's input preferences and extract important information such as budget, genre, and viewing time.

[0552] 3. Plan generation method: The server automatically generates a viewing plan based on the analysis results. To generate the viewing plan, recommended content is obtained using the API of a video content distribution service (e.g., video content distribution API), and a viewing schedule is created.

[0553] 4. Display method: The generated viewing plan will be displayed on the screen of a smartphone or computer and presented to the user visually.

[0554] User input

[0555] Users enter their viewing preferences using a chat interface. A typical prompt might be, "My budget is 5000 yen, the location is my home, and I want pizza." This interface is designed to be intuitive and allow users to easily enter their preferences.

[0556] Data analysis

[0557] The server receives input data from the user and performs analysis using natural language processing (NLP) techniques. The server uses Python's NLP library to analyze the text and extract important information such as budget, location, and desired cuisine. For example, it receives the text "My budget is 5000 yen, the location is my home, and the desired cuisine is pizza," and extracts the information for each item.

[0558] Creating a viewing plan

[0559] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation includes a function to search for the most suitable candidates using the API of a video content distribution service. For example, it generates a list of recommended movies and dramas based on the acquired information and schedules them according to viewing time.

[0560] Presentation of the plan

[0561] The server displays the details of the generated viewing plan on the user interface, and the device (smartphone or PC) presents it to the user. The user can confirm the generated plan through the chat interface.

[0562] for example,

[0563] The budget is 5000 yen, the location is my home, and the food I want to eat is pizza.

[0564] When you enter,

[0565] 1. The analysis method extracts "5000 yen," "home," and "pizza" from the text.

[0566] 2. The plan generation method uses a video content distribution service API to collect movies and dramas that can be viewed within the budget and generates a viewing schedule.

[0567] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0568] This allows users to easily and quickly create viewing plans and efficiently consume all available content.

[0569] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0570] Step 1:

[0571] The user accesses the chat interface and enters their desired viewing conditions. For example, they might enter, "My budget is 5000 yen, the location is my home, and I want pizza." This input data is then sent to the server.

[0572] Input: User's desired viewing conditions (e.g., "Budget: 5000 yen, Location: Home, Food I want to eat: Pizza")

[0573] Output: Input data is sent to the server.

[0574] Step 2:

[0575] The server analyzes the user's input data. Natural language processing techniques (e.g., Python's NLP library) are used for the analysis. Through this process, the server extracts each element of the desired conditions (budget, location, food).

[0576] Input: User viewing preferences submitted in Step 1

[0577] Processing: Use natural language processing techniques to extract budget, location, and desired cuisine.

[0578] Output: Analyzed desired conditions (e.g., budget = 5000 yen, location = home, food desired = pizza)

[0579] Step 3:

[0580] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation uses the API of the video content distribution service. Based on the acquired information, the server creates a list of movies and dramas that can be viewed.

[0581] Input: Desired conditions analyzed in Step 2

[0582] Process: Use the API of the video content distribution service to retrieve viewable content.

[0583] Output: List of recommended content (e.g., Movie A, TV series B)

[0584] Step 4:

[0585] The server generates a viewing schedule based on recommended content. The schedule is created based on the playback time of each piece of content and the user's viewing preferences.

[0586] Input: List of recommended content

[0587] Processing: Create a viewing schedule, taking into account the playback time of each piece of content.

[0588] Output: Viewing schedule (Example: 19:00 - Movie A, 21:00 - Drama B)

[0589] Step 5:

[0590] The server displays the details of the viewing plan generated by the server on the user interface, showing them on the screen of a smartphone or computer. This allows the user to check recommended content and viewing schedules.

[0591] Input: Viewing schedule

[0592] Processing: Display the viewing schedule in the user interface.

[0593] Output: Viewing schedule displayed on the user interface

[0594] Step 6:

[0595] Users can review the presented viewing plan and adjust their viewing schedule as needed. Furthermore, by initiating a viewing start, the server will coordinate with the video content distribution service and begin playback.

[0596] Input: User verification and adjustment instructions, instructions to start viewing.

[0597] Processing: Based on user instructions, adjust the viewing schedule and initiate viewing.

[0598] Output: Start playback (playback of video content)

[0599] 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.

[0600] This invention relates to a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, all while incorporating an emotion engine that recognizes and analyzes the user's emotions. Embodiments of this invention will be described in detail below.

[0601] Basic System Configuration

[0602] This system includes a user interface for users to input their travel preferences, an analysis means and emotion engine for analyzing the input information and associated emotions, a plan generation means for automatically generating a travel plan based on the analysis results and emotional state, a display means for displaying the generated travel plan, and a reservation means for making reservations based on the travel plan. Furthermore, it also includes a notification means for informing the user of travel information for the day.

[0603] User input

[0604] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might type, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0605] Data analysis

[0606] The server receives input data from the user and passes it to the analysis tool and the emotion engine. The analysis tool uses natural language processing technology to extract important information from the input data. For example, it might extract keywords such as "budget 100,000 yen," "Tokyo," and "sushi." Meanwhile, the emotion engine analyzes the user's input text and determines their emotional state, such as positive, negative, or neutral.

[0607] Travel plan generation

[0608] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. This includes searching and retrieving the most suitable candidates from partner databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares. Furthermore, it adjusts the content of the travel plan based on the user's emotional state. For example, if the emotional state is positive, it recommends a slightly more expensive restaurant, and if the emotional state is negative, it adds relaxing sightseeing spots.

[0609] Presentation of the plan

[0610] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0611] Reservation operation

[0612] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0613] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0614] Travel Guide

[0615] On the day of travel, the server notifies the user of detailed travel information (e.g., Shinkansen departure time, hotel check-in information, map to recommended sushi restaurant, etc.). This allows the user to enjoy their trip with peace of mind.

[0616] Specific example

[0617] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0618] 1. The analysis tool extracts "100,000 yen," "Tokyo," and "sushi" from the text. Meanwhile, the emotion engine analyzes the positive emotion of "enjoyment."

[0619] 2. The plan generation system collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate a travel plan. Based on the results of the emotion engine, it proposes a plan that includes a special dinner course.

[0620] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0621] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0622] 5. The server uses the reservation method to coordinate with the Shinkansen reservation system and the hotel reservation system to complete the reservation.

[0623] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0624] As described above, the system of the present invention allows users to easily and quickly plan their trips and provides them with a unique experience that takes their emotions into consideration.

[0625] The following describes the processing flow.

[0626] Step 1:

[0627] The user accesses the chat interface and enters their travel preferences. For example, they might type, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0628] Step 2:

[0629] The device sends the user's input data to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[0630] Step 3:

[0631] The server receives input data from the user and passes it to the analysis unit and the emotion engine. The analysis unit then passes the input data to the natural language processing engine.

[0632] Step 4:

[0633] The server's analysis tools extract important information from the input data. For example, it might extract the keywords "budget 100,000 yen," "Tokyo," and "sushi" from the input text.

[0634] Step 5:

[0635] The server's emotion engine analyzes the input data and determines the user's emotional state. For example, the emotion engine might analyze the input text to identify a positive emotion such as "enjoyment."

[0636] Step 6:

[0637] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. Specifically, it searches for the best candidates from partner databases (information on airlines, railway companies, hotels, and restaurants) and adjusts the plan content based on the user's emotional state.

[0638] Step 7:

[0639] The server converts the travel plan details it generates into display data and sends it to the terminal. The display data is in JSON format.

[0640] Step 8:

[0641] The device displays the received travel plan in the chat interface. The user can then review the specific plan details.

[0642] Step 9:

[0643] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0644] Step 10:

[0645] The device sends the user's selection to the server. The selection data is sent to the server as an HTTP request in JSON format.

[0646] Step 11:

[0647] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API, sends the necessary information, and completes the reservation.

[0648] Step 12:

[0649] The server receives the reservation confirmation result and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[0650] Step 13:

[0651] The device displays the reservation confirmation result in the chat interface and notifies the user. The user can then confirm that the reservation is complete.

[0652] Step 14:

[0653] On the day of travel, the server notifies the user of travel details. For example, it may notify them of the Shinkansen departure time, hotel check-in information, and a map and operating hours of a recommended sushi restaurant. Notifications are sent via SMS, email, or a chat interface.

[0654] Step 15:

[0655] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[0656] (Example 2)

[0657] 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".

[0658] Conventional automated travel plan generation systems could provide plans based on user preferences, but they struggled to provide plans that took into account the user's emotional state at that moment. As a result, they were unable to provide the ideal travel experience that users envisioned, and thus failed to increase user satisfaction.

[0659] 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.

[0660] In this invention, the server includes a user interface means for inputting travel preferences, an analysis means including an emotion engine for analyzing the user's emotions, and a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotion engine. This makes it possible to provide a travel plan that takes into account both the user's preferences and emotional state.

[0661] A "user interface" is the interface through which a user enters their travel preferences.

[0662] "Analysis means" refers to a device or program that analyzes travel preferences obtained through a user interface.

[0663] An "emotion engine" is a technology that analyzes user input data to determine emotions and identify emotional states such as positive, negative, or neutral.

[0664] A "plan generation means" is a device or program that automatically generates a travel plan based on the analysis results obtained by the analysis means and the emotion engine.

[0665] "Display means" refers to a device or program that visualizes and displays the generated travel plan to the user.

[0666] A "booking method" refers to a device or program that makes an actual travel reservation based on a generated travel plan.

[0667] A "database" is an information aggregation system used to collect and manage the information necessary for generating travel plans.

[0668] "Natural language processing technology" is a technology that analyzes text data entered by a user and understands its content.

[0669] A "notification means" refers to a device or program that notifies the user of detailed travel-related information on the day of the trip.

[0670] This invention is a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, and further incorporates an emotion engine that recognizes and analyzes the user's emotions.

[0671] The system configuration is as follows: First, the user uses a user interface to enter their travel preferences. The user interface is a chat-style interface where users can enter their preferences as text. For example, they might enter a prompt message such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0672] Next, this input data is sent to the server. After receiving the data, the server processes it using analysis tools and an emotion engine. The analysis tools utilize natural language processing technology (e.g., Google Cloud Natural Language API). This technology extracts important information from the user's input text, for example, extracting keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[0673] An emotion engine analyzes the user's emotional state from their input text (for example, IBM Watson Tone Analyzer), determining whether the user is in a positive, negative, or neutral emotional state. For example, it might analyze the input text to identify a positive emotion like "enjoyment."

[0674] Next, the server's plan generation mechanism automatically generates a travel plan based on the analyzed data and emotional state. The plan generation mechanism retrieves travel-related information from partner databases (e.g., travel agency databases, transportation databases, accommodation databases) and creates the optimal travel plan. For example, it collects information such as "bullet train operating times and fares," "hotel information," and "sushi restaurant information," and generates a plan that includes high-end restaurants based on a positive emotional state.

[0675] The generated travel plan is sent from the server to the user interface and displayed to the user via their device. The user can review the presented plan and select the necessary booking actions from the chat interface. For example, they can select "Shinkansen ticket booking" and "hotel booking."

[0676] Once the user has made their selection, the server uses the booking method to connect with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) and make the actual booking. Specifically, it accesses the Shinkansen (bullet train) booking system to reserve a ticket for the specified date and time, and similarly reserves a hotel.

[0677] Finally, on the day of travel, the server notifies the user of detailed travel information. For example, it sends the user the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant via the smartphone's notification function. This allows the user to enjoy their trip with peace of mind.

[0678] Thus, the system of the present invention allows users to easily and quickly plan their trips and to provide them with a unique experience that takes their emotions into consideration.

[0679] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0680] Step 1:

[0681] The user enters their travel preferences through a chat interface. Specifically, they enter prompts such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The input data obtained is "budget 100,000 yen," "Tokyo," and "sushi."

[0682] Step 2:

[0683] The terminal sends user input data to the server. The server receives this data and passes it on to the analysis tools and emotion engine. As input data, text obtained from the user interface is sent to the server.

[0684] Step 3:

[0685] The server's analysis method uses natural language processing technology (e.g., Google Cloud Natural Language API) to extract important information from the input data. Specifically, "budget of 100,000 yen," "Tokyo," and "sushi" are extracted. The extracted keywords are obtained as output data.

[0686] Step 4:

[0687] The server's emotion engine analyzes the user's input text and determines their emotional state (e.g., IBM Watson Tone Analyzer). Specifically, a positive emotion like "enjoyment" is analyzed. The analyzed emotional state is obtained as output data.

[0688] Step 5:

[0689] The server's plan generation mechanism generates an optimal travel plan based on input data (keywords and emotional states) obtained from the analysis mechanism and the emotion engine. It collects information such as "Shinkansen train schedules and fares," "hotel information," and "sushi restaurant information" from a partner database, and generates a plan including high-end restaurants based on positive emotional states. The generated travel plan is obtained as output data.

[0690] Step 6:

[0691] The server generates a travel plan and sends it to the user interface, which the terminal displays to the user. The user can then view the plan details on the user interface. The generated travel plan is sent to the user interface as input data.

[0692] Step 7:

[0693] The user reviews their travel plan via a chat interface and selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking." The user's booking selections are obtained as input data.

[0694] Step 8:

[0695] The terminal sends the user's selection to the server, which then coordinates with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) to make the actual booking. The Shinkansen (bullet train) and hotel bookings are completed. The booking completion information is provided as output data.

[0696] Step 9:

[0697] On the day of travel, the server notifies the user of detailed travel information. Specifically, this includes the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant. Detailed travel plan information is stored on the server as input data.

[0698] Through these steps, users can easily and quickly create travel plans based on their wishes and emotional state, make reservations, and enjoy their trip with peace of mind.

[0699] (Application Example 2)

[0700] 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."

[0701] Conventional travel plan generation systems have the functionality to generate and book travel plans based on user-inputted preferences, but they have the problem of not being able to adjust the suggested content to take into account the user's emotional state. Furthermore, even if travel plan generation and booking can be done in one go, a separate payment method is required, which is inconvenient for the user. In addition, there are insufficient means of notifying users of necessary information on the day of travel, which is an obstacle to the smooth running of the trip.

[0702] 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.

[0703] In this invention, the server includes a user interface for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions and associated emotional states obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results and emotional states obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation and payment means for making a reservation and payment for the trip in a single transaction based on the travel plan, and a notification means for displaying payment information associated with the travel plan on the user interface. This enables the proposal of a travel plan that takes the user's emotional state into consideration, and allows for a single reservation and payment. Furthermore, it enables smooth travel by quickly notifying the user of information they need on the day of the trip.

[0704] A "user interface" is the means by which a user interacts with a system and inputs their travel preferences.

[0705] "Analysis means" refers to means for analyzing travel preferences and associated emotional states obtained through the user interface.

[0706] The "plan generation means" is a means for automatically generating a travel plan based on the analysis results and emotional state obtained by the analysis means.

[0707] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[0708] "Booking and payment methods" refer to the means of making a single booking and payment for a trip based on a travel plan.

[0709] "Notification methods" refer to means of notifying users of payment information related to their travel plan and detailed information for the day of travel.

[0710] "Emotional state" refers to the emotional state analyzed based on user input, and includes positive, negative, neutral, etc.

[0711] "Natural language processing technology" is a technology that analyzes text information entered by users to understand its meaning and intent.

[0712] This invention is a system that allows users to input their travel preferences, automatically generates a travel plan based on those preferences, and handles all necessary reservations and payments in a single process. Furthermore, it can promptly notify users of necessary information on the day of travel.

[0713] Basic System Configuration

[0714] The system includes the following components:

[0715] 1. User Interface: The means by which users input their travel preferences. Specifically, this refers to applications on smartphones.

[0716] 2. Analysis Method: A method for analyzing user input and extracting travel preferences and emotional states. As a specific example, natural language processing techniques implemented using the Python transformers library will be used.

[0717] 3. Plan generation means: A means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotional state. It generates a plan that combines hotels, restaurants, transportation, etc. at the travel destination and is adjusted according to the emotional state.

[0718] 4. Display means: Means for presenting the generated travel plan to the user. Specifically, the details of the plan are displayed on the smartphone application screen.

[0719] 5. Booking and Payment Methods: A method for booking and paying for travel in a single transaction based on a travel plan. A dummy API can be used, but in a real environment, it will integrate with actual booking sites and payment systems.

[0720] 6. Notification method: A means of notifying the user of necessary information on the day of the trip.

[0721] System processing flow

[0722] The server first receives travel preferences from the user via the user interface. For example, text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" might be entered. At this time, the user's emotional state is also analyzed and classified as positive, negative, neutral, etc.

[0723] Next, the server generates a travel plan. Based on the information extracted by the analysis tools, it combines data on hotels, restaurants, and transportation options at the travel destination. If the user's emotional state is positive, suggestions are made to enhance user satisfaction, such as proposing a plan that includes a rich dinner course.

[0724] The generated travel plan is displayed on the smartphone application screen. Users can review this plan and make reservations and payments all at once. After the reservation and payment are complete, the system will notify the user in real time on the day of travel, providing all necessary information.

[0725] Specific example

[0726] For example, suppose the user entered the following:

[0727] My travel budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi. Please suggest a suitable itinerary.

[0728] In this case, the system automatically performs an analysis and extracts keywords such as "budget of 100,000 yen," "Tokyo," and "sushi," as well as positive emotions. The plan generation means then generates a plan combining the most suitable hotels, restaurants, bullet train information, etc., based on this information and presents it to the user. Once the user completes the reservation and payment, the necessary information for the day of travel is notified in a timely manner. In this way, as a form of implementing the invention, the user can create a travel plan simply and effectively.

[0729] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0730] Step 1:

[0731] Users enter their travel preferences via a smartphone application. The data entered is in text format and may include information such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The entered conditions include details about the trip, such as budget, desired destinations, and food preferences.

[0732] Step 2:

[0733] The terminal receives the user's desired conditions and sends them to the server. The server inputs the received data into an analysis device. This analysis device uses the Python transformers library to analyze the input data and extract important keywords ("Budget: 100,000 yen", "Place to go: Tokyo", "Food to eat: Sushi").

[0734] Step 3:

[0735] The server passes the data analyzed by the analysis means to the emotion state analysis engine. This engine analyzes the user's emotional state from the text obtained through the user interface. For example, if the user indicates a positive emotion such as excitement, the emotion analysis engine will determine that emotional state is "positive."

[0736] Step 4:

[0737] The server executes the plan generation means based on the information obtained from the analysis means and the sentiment analysis engine. The plan generation means accesses the database and automatically generates a travel plan based on the analyzed keywords. Specifically, it combines information on accommodations, restaurants, and bullet trains to create a plan that is adjusted according to the user's emotional state.

[0738] Step 5:

[0739] The server sends data to the display device to show the generated travel plan on the user's smartphone. The device then displays the details of the received travel plan to the user. The user interface displays a list of accommodations, restaurants, transportation, etc., included in the generated plan.

[0740] Step 6:

[0741] The user makes a reservation and payment based on the presented travel plan. The terminal receives the user's selection and sends that information to the server. The server, through the reservation and payment method, interacts with the reservation site and payment system included in the travel plan and executes the necessary reservations and payments in one go.

[0742] Step 7:

[0743] On the day of travel, the server notifies the user of payment information and other details related to the travel plan (such as Shinkansen departure times, hotel check-in information, and maps of recommended restaurants). This notification is made using the smartphone's notification function, allowing the user to receive the necessary information in real time.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] [Third Embodiment]

[0748] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0749] 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.

[0750] 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).

[0751] 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.

[0752] 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.

[0753] 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).

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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".

[0760] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0761] Basic System Configuration

[0762] The system includes a user interface for the user to input their travel preferences, an analysis means for analyzing the input information, a plan generation means for generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, and a reservation means for making reservations. Furthermore, it also includes a means for notifying the user of travel information for the day.

[0763] User input

[0764] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might enter text such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0765] Data analysis

[0766] The server receives input data from the user and performs analysis using natural language processing techniques. Specifically, it analyzes the text and extracts important information such as budget, destination, and desired food.

[0767] Travel plan generation

[0768] The server's plan generation system automatically generates travel plans based on analysis results. This plan generation includes a function to search for the most suitable candidates from databases the system partners with (airlines, railway companies, hotels, restaurants, etc.). For example, it generates a plan that combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market based on the acquired information.

[0769] Presentation of the plan

[0770] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0771] Reservation operation

[0772] Based on the plan presented, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0773] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0774] Travel Guide

[0775] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0776] Specific example

[0777] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0778] 1. The analysis method extracts "100,000 yen," "Tokyo," and "sushi" from the text.

[0779] 2. The plan generation method collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate travel plans.

[0780] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0781] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0782] 5. The server uses the reservation method to complete the reservation in cooperation with the partner Shinkansen reservation system and hotel reservation system.

[0783] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0784] As described above, the system of the present invention allows users to easily and quickly create travel plans and make all reservations seamlessly.

[0785] The following describes the processing flow.

[0786] Step 1:

[0787] The user accesses the chat interface and enters their travel preferences. Specifically, they enter their budget, destination, and desired food in text format. For example, they might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0788] Step 2:

[0789] The terminal sends user input data to the server. The input data is sent to the server as an HTTP request. The data is composed of JSON or text format.

[0790] Step 3:

[0791] The server receives input data from the user and passes it to the analysis tool. The analysis tool uses natural language processing technology to extract important information from the input data. Specifically, it extracts keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[0792] Step 4:

[0793] The server's plan generation mechanism automatically generates travel plans based on analysis results obtained from the analysis mechanism. This includes searching and retrieving the most suitable candidates from affiliated databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares.

[0794] Step 5:

[0795] The server generates a travel plan (for example, Shinkansen bullet train tickets, a business hotel in Ginza, and three sushi restaurants around Tsukiji Market), converts it into data for display, and sends it to the terminal. The display data is in JSON format.

[0796] Step 6:

[0797] The device displays the received travel plan on the user interface. The user can then check the specific plan details via the chat interface.

[0798] Step 7:

[0799] Based on the plan presented, the user selects the necessary booking actions. Specifically, they select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0800] Step 8:

[0801] The device sends the user's selection to the server. The selection is sent to the server as an HTTP request in JSON format.

[0802] Step 9:

[0803] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API and sends the necessary information to execute the reservation.

[0804] Step 10:

[0805] The server receives the reservation confirmation and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[0806] Step 11:

[0807] The terminal displays the reservation confirmation result on the user interface and notifies the user. The user confirms that the reservation is complete.

[0808] Step 12:

[0809] On the day of travel, the server notifies the user of travel details (e.g., Shinkansen departure time, hotel check-in information, sushi restaurant map and operating hours). Notifications are sent via SMS, email, or a chat interface.

[0810] Step 13:

[0811] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[0812] (Example 1)

[0813] 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."

[0814] Traditional travel booking systems had a complex process for users to input their travel preferences, making it difficult to quickly and efficiently generate travel plans that met their needs. Furthermore, the need to use multiple booking sites meant users had to go through the process of making individual reservations, which was time-consuming. Additionally, the lack of adequate advance notification of travel-related information meant that users were unable to enjoy their trips smoothly.

[0815] 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.

[0816] In this invention, the server includes an information analysis means for analyzing travel preferences obtained through a user interface, a plan generation means for automatically generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, a reservation means for making reservations, and a search means for searching for the best candidate from affiliated information sources and constructing a travel plan. This allows users to easily and quickly create a travel plan and make all reservations seamlessly. Furthermore, by notifying users of detailed information on the day of travel in advance, users can enjoy their trip smoothly.

[0817] A "user interface" is the interface through which a user interacts with a system and inputs their travel preferences.

[0818] "Information analysis means" refers to a means of analyzing travel preferences obtained through a user interface and extracting important information.

[0819] A "plan generation means" is a means for automatically generating a travel plan based on the analysis results obtained by an information analysis means.

[0820] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[0821] "Reservation method" refers to the means of making travel reservations based on a travel plan.

[0822] "Search methods" refer to the means of searching for the best candidates from affiliated information sources and constructing a travel plan.

[0823] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[0824] User input

[0825] First, the user enters their travel preferences. The user enters their preferences in text format using a chat interface or a dedicated application. For example, the user might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0826] Data analysis

[0827] The server receives user input data and uses analysis tools to analyze the text using natural language processing techniques. Specifically, it uses NLP libraries (e.g., spaCy, NLTK) to extract important information such as "100,000 yen," "Tokyo," and "sushi." This analysis clarifies the user's desired conditions.

[0828] Travel plan generation

[0829] Next, the server's plan generation mechanism automatically generates a travel plan based on the analysis results. To do this, the server obtains data from multiple partner information sources (e.g., airline databases, hotel reservation systems, restaurant information) via APIs. Specifically, it obtains Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market, and combines them to construct the optimal travel plan.

[0830] Presentation of the plan

[0831] The generated travel plan is sent from the server to the device. The device displays the received plan to the user. The user can review this plan through a chat interface or application.

[0832] Reservation operation

[0833] Based on the presented travel plan, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking." The terminal sends the user's selection information to the server, which then uses the booking method to complete the booking in conjunction with partner booking systems (e.g., Shinkansen booking API, hotel booking API).

[0834] Travel Guide

[0835] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[0836] Specific example

[0837] As a concrete example, here's how the system would handle a user who enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface:

[0838] 1. The user enters the text "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface.

[0839] 2. The server analyzes this received text using an NLP library and extracts the information "100,000 yen," "Tokyo," and "sushi."

[0840] 3. The server retrieves Shinkansen (bullet train) operation information, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market from partner APIs, and generates the optimal travel plan based on this information.

[0841] 4. The server sends the generated travel plan to the terminal, and the terminal displays the plan to the user.

[0842] 5. The user makes a reservation based on the plan, and the device sends the selection information to the server.

[0843] 6. The server uses the reservation method to complete the reservation in cooperation with the partner reservation system.

[0844] 7. On the day of travel, the server will notify the user of detailed travel information to support a smooth trip.

[0845] This invention allows users to easily and quickly plan their trips through a series of operations and make all reservations seamlessly. Furthermore, detailed information for the day of travel is provided in advance, allowing users to enjoy their trip with peace of mind.

[0846] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0847] Step 1:

[0848] The user enters their travel preferences into the chat interface.

[0849] Specific actions: The user opens a browser or mobile app, enters text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" into the chat interface, and clicks the send button.

[0850] Input: Text information entered by the user.

[0851] Output: Text data containing the user's desired conditions.

[0852] Step 2:

[0853] The server receives input data sent from the user.

[0854] Specific operation: The server receives the user's input data as an HTTP request and begins processing to parse its contents.

[0855] Input: HTTP request sent by the user.

[0856] Output: A string containing the user's input data.

[0857] Step 3:

[0858] The server uses analysis tools to analyze the text using natural language processing techniques.

[0859] Specific operation: The server uses an NLP library (e.g., spaCy, NLTK) to extract the keywords "100,000 yen," "Tokyo," and "sushi" from the text.

[0860] Input: User-input text data.

[0861] Output: Extracted keyword information (e.g., "100,000 yen", "Tokyo", "sushi").

[0862] Step 4:

[0863] The server's plan generation mechanism automatically generates a travel plan based on the analysis results.

[0864] Specific operation: The server calls APIs it partners with (e.g., travel agency API, hotel booking API) and builds the optimal travel plan based on the information obtained. Specifically, it combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market.

[0865] Input: Extracted keyword information.

[0866] Output: Detailed data of an automatically generated travel plan.

[0867] Step 5:

[0868] The server sends the details of the generated travel plan to the user interface.

[0869] Specific operation: The server converts the generated travel plan into JSON format and sends it to the frontend.

[0870] Input: Detailed data of the travel plan.

[0871] Output: Travel plan converted to JSON format.

[0872] Step 6:

[0873] The terminal receives data from the server and displays it in the user interface.

[0874] Specific operation: The device (browser or mobile app) parses the JSON data received from the server and displays it in the user interface.

[0875] Input: JSON data received from the server.

[0876] Output: A screen display of the travel plan that the user can view.

[0877] Step 7:

[0878] The user reviews the presented travel plan and selects the necessary booking actions.

[0879] Specific actions: The user selects "Shinkansen ticket reservation" and "Hotel reservation" from the chat interface or reservation button, and then presses the submit button.

[0880] Input: Travel plan selection information.

[0881] Output: User-selected reservation details.

[0882] Step 8:

[0883] The terminal sends the user's selection to the server.

[0884] Specific operation: The terminal generates an HTTP request containing the user's selection information and sends it to the server.

[0885] Input: User selection information.

[0886] Output: HTTP request sent to the server.

[0887] Step 9:

[0888] The server uses the reservation method and completes the reservation in cooperation with partner reservation sites and services.

[0889] Specific operation: The server calls a reservation API (e.g., Shinkansen reservation API, hotel reservation API) and executes the reservation process.

[0890] Input: User selection information.

[0891] Output: Confirmed reservation information.

[0892] Step 10:

[0893] The server will notify the user of detailed information for the day of the trip.

[0894] Specific operation: The server generates a notification message containing information such as the Shinkansen departure time, hotel check-in information, and a map of a sushi restaurant, and sends it to the user.

[0895] Input: Confirmed reservation information.

[0896] Output: A notification message containing detailed information for the day of travel.

[0897] (Application Example 1)

[0898] 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."

[0899] In recent years, users have a growing need to efficiently plan and consume not only travel but also video content. However, current systems cannot integrate travel planning with content recommendations and scheduling. As a result, users must plan each piece of content individually, which is a time-consuming and laborious process. Therefore, there is a need for a system that, based on the user's input preferences, recommends content to watch and automatically generates a viewing schedule, in addition to providing travel plans.

[0900] 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.

[0901] In this invention, the server includes a user interface means for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation means for making a travel reservation based on the travel plan, a means for obtaining recommended content based on the desired travel conditions, and a means for generating a viewing schedule based on the recommended content. This makes it possible for the user to generate a travel plan, recommend viewing content, and generate a viewing schedule in an integrated manner, significantly reducing the effort required for planning.

[0902] "Travel preferences" refer to the various conditions that users desire when traveling, and specifically include budget, destination, and food preferences.

[0903] A "user interface" is a means by which a user interacts with a system and inputs or confirms information. Specific examples include chat interfaces and touchscreens.

[0904] "Analysis means" refers to a function that analyzes the desired conditions entered by the user and extracts useful information, and it is common to use natural language processing technology.

[0905] "Plan generation method" refers to a function that automatically generates travel plans and recommendations for viewing content based on analyzed preferences.

[0906] "Display means" refers to a function that presents the generated travel plan or viewing schedule to the user, and this includes displays and mobile screens.

[0907] "Reservation method" refers to a function that automatically makes necessary reservations (such as accommodation and transportation) based on the generated travel plan.

[0908] "Recommended content" refers to video content that is recommended for viewing based on the user's entered preferences.

[0909] A "viewing schedule" refers to a planned timetable designed to allow users to efficiently view recommended content.

[0910] This invention is a system that allows users to input their desired viewing conditions, automatically generates an optimal viewing plan based on those conditions, presents recommended content, and creates a viewing schedule. Embodiments of the present invention will be described in detail below.

[0911] Basic System Configuration

[0912] The system has the following main features:

[0913] 1. User Interface: A chat interface on a smartphone application or web browser will be used as a means for users to input their desired viewing conditions.

[0914] 2. Analysis method: The server uses natural language processing technology (e.g., Python's NLP library) to analyze the user's input preferences and extract important information such as budget, genre, and viewing time.

[0915] 3. Plan generation method: The server automatically generates a viewing plan based on the analysis results. To generate the viewing plan, recommended content is obtained using the API of a video content distribution service (e.g., video content distribution API), and a viewing schedule is created.

[0916] 4. Display method: The generated viewing plan will be displayed on the screen of a smartphone or computer and presented to the user visually.

[0917] User input

[0918] Users enter their viewing preferences using a chat interface. A typical prompt might be, "My budget is 5000 yen, the location is my home, and I want pizza." This interface is designed to be intuitive and allow users to easily enter their preferences.

[0919] Data analysis

[0920] The server receives input data from the user and performs analysis using natural language processing (NLP) techniques. The server uses Python's NLP library to analyze the text and extract important information such as budget, location, and desired cuisine. For example, it receives the text "My budget is 5000 yen, the location is my home, and the desired cuisine is pizza," and extracts the information for each item.

[0921] Creating a viewing plan

[0922] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation includes a function to search for the most suitable candidates using the API of a video content distribution service. For example, it generates a list of recommended movies and dramas based on the acquired information and schedules them according to viewing time.

[0923] Presentation of the plan

[0924] The server displays the details of the generated viewing plan on the user interface, and the device (smartphone or PC) presents it to the user. The user can confirm the generated plan through the chat interface.

[0925] for example,

[0926] The budget is 5000 yen, the location is my home, and the food I want to eat is pizza.

[0927] When you enter,

[0928] 1. The analysis method extracts "5000 yen," "home," and "pizza" from the text.

[0929] 2. The plan generation method uses a video content distribution service API to collect movies and dramas that can be viewed within the budget and generates a viewing schedule.

[0930] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0931] This allows users to easily and quickly create viewing plans and efficiently consume all available content.

[0932] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0933] Step 1:

[0934] The user accesses the chat interface and enters their desired viewing conditions. For example, they might enter, "My budget is 5000 yen, the location is my home, and I want pizza." This input data is then sent to the server.

[0935] Input: User's desired viewing conditions (e.g., "Budget: 5000 yen, Location: Home, Food I want to eat: Pizza")

[0936] Output: Input data is sent to the server.

[0937] Step 2:

[0938] The server analyzes the user's input data. Natural language processing techniques (e.g., Python's NLP library) are used for the analysis. Through this process, the server extracts each element of the desired conditions (budget, location, food).

[0939] Input: User viewing preferences submitted in Step 1

[0940] Processing: Use natural language processing techniques to extract budget, location, and desired cuisine.

[0941] Output: Analyzed desired conditions (e.g., budget = 5000 yen, location = home, food desired = pizza)

[0942] Step 3:

[0943] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation uses the API of the video content distribution service. Based on the acquired information, the server creates a list of movies and dramas that can be viewed.

[0944] Input: Desired conditions analyzed in Step 2

[0945] Process: Use the API of the video content distribution service to retrieve viewable content.

[0946] Output: List of recommended content (e.g., Movie A, TV series B)

[0947] Step 4:

[0948] The server generates a viewing schedule based on recommended content. The schedule is created based on the playback time of each piece of content and the user's viewing preferences.

[0949] Input: List of recommended content

[0950] Processing: Create a viewing schedule, taking into account the playback time of each piece of content.

[0951] Output: Viewing schedule (Example: 19:00 - Movie A, 21:00 - Drama B)

[0952] Step 5:

[0953] The server displays the details of the viewing plan generated by the server on the user interface, showing them on the screen of a smartphone or computer. This allows the user to check recommended content and viewing schedules.

[0954] Input: Viewing schedule

[0955] Processing: Display the viewing schedule in the user interface.

[0956] Output: Viewing schedule displayed on the user interface

[0957] Step 6:

[0958] Users can review the presented viewing plan and adjust their viewing schedule as needed. Furthermore, by initiating a viewing start, the server will coordinate with the video content distribution service and begin playback.

[0959] Input: User verification and adjustment instructions, instructions to start viewing.

[0960] Processing: Based on user instructions, adjust the viewing schedule and initiate viewing.

[0961] Output: Start playback (playback of video content)

[0962] 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.

[0963] This invention relates to a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, all while incorporating an emotion engine that recognizes and analyzes the user's emotions. Embodiments of this invention will be described in detail below.

[0964] Basic System Configuration

[0965] This system includes a user interface for users to input their travel preferences, an analysis means and emotion engine for analyzing the input information and associated emotions, a plan generation means for automatically generating a travel plan based on the analysis results and emotional state, a display means for displaying the generated travel plan, and a reservation means for making reservations based on the travel plan. Furthermore, it also includes a notification means for informing the user of travel information for the day.

[0966] User input

[0967] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might type, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[0968] Data analysis

[0969] The server receives input data from the user and passes it to the analysis tool and the emotion engine. The analysis tool uses natural language processing technology to extract important information from the input data. For example, it might extract keywords such as "budget 100,000 yen," "Tokyo," and "sushi." Meanwhile, the emotion engine analyzes the user's input text and determines their emotional state, such as positive, negative, or neutral.

[0970] Travel plan generation

[0971] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. This includes searching and retrieving the most suitable candidates from partner databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares. Furthermore, it adjusts the content of the travel plan based on the user's emotional state. For example, if the emotional state is positive, it recommends a slightly more expensive restaurant, and if the emotional state is negative, it adds relaxing sightseeing spots.

[0972] Presentation of the plan

[0973] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[0974] Reservation operation

[0975] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[0976] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[0977] Travel Guide

[0978] On the day of travel, the server notifies the user of detailed travel information (e.g., Shinkansen departure time, hotel check-in information, map to recommended sushi restaurant, etc.). This allows the user to enjoy their trip with peace of mind.

[0979] Specific example

[0980] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[0981] 1. The analysis tool extracts "100,000 yen," "Tokyo," and "sushi" from the text. Meanwhile, the emotion engine analyzes the positive emotion of "enjoyment."

[0982] 2. The plan generation system collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate a travel plan. Based on the results of the emotion engine, it proposes a plan that includes a special dinner course.

[0983] 3. The generated plan is displayed in the user interface, and the user confirms it.

[0984] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[0985] 5. The server uses the reservation method to coordinate with the Shinkansen reservation system and the hotel reservation system to complete the reservation.

[0986] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[0987] As described above, the system of the present invention allows users to easily and quickly plan their trips and provides them with a unique experience that takes their emotions into consideration.

[0988] The following describes the processing flow.

[0989] Step 1:

[0990] The user accesses the chat interface and enters their travel preferences. For example, they might type, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[0991] Step 2:

[0992] The device sends the user's input data to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[0993] Step 3:

[0994] The server receives input data from the user and passes it to the analysis unit and the emotion engine. The analysis unit then passes the input data to the natural language processing engine.

[0995] Step 4:

[0996] The server's analysis tools extract important information from the input data. For example, it might extract the keywords "budget 100,000 yen," "Tokyo," and "sushi" from the input text.

[0997] Step 5:

[0998] The server's emotion engine analyzes the input data and determines the user's emotional state. For example, the emotion engine might analyze the input text to identify a positive emotion such as "enjoyment."

[0999] Step 6:

[1000] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. Specifically, it searches for the best candidates from partner databases (information on airlines, railway companies, hotels, and restaurants) and adjusts the plan content based on the user's emotional state.

[1001] Step 7:

[1002] The server converts the travel plan details it generates into display data and sends it to the terminal. The display data is in JSON format.

[1003] Step 8:

[1004] The device displays the received travel plan in the chat interface. The user can then review the specific plan details.

[1005] Step 9:

[1006] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[1007] Step 10:

[1008] The device sends the user's selection to the server. The selection data is sent to the server as an HTTP request in JSON format.

[1009] Step 11:

[1010] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API, sends the necessary information, and completes the reservation.

[1011] Step 12:

[1012] The server receives the reservation confirmation result and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[1013] Step 13:

[1014] The device displays the reservation confirmation result in the chat interface and notifies the user. The user can then confirm that the reservation is complete.

[1015] Step 14:

[1016] On the day of travel, the server notifies the user of travel details. For example, it may notify them of the Shinkansen departure time, hotel check-in information, and a map and operating hours of a recommended sushi restaurant. Notifications are sent via SMS, email, or a chat interface.

[1017] Step 15:

[1018] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[1019] (Example 2)

[1020] 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."

[1021] Conventional automated travel plan generation systems could provide plans based on user preferences, but they struggled to provide plans that took into account the user's emotional state at that moment. As a result, they were unable to provide the ideal travel experience that users envisioned, and thus failed to increase user satisfaction.

[1022] 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.

[1023] In this invention, the server includes a user interface means for inputting travel preferences, an analysis means including an emotion engine for analyzing the user's emotions, and a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotion engine. This makes it possible to provide a travel plan that takes into account both the user's preferences and emotional state.

[1024] A "user interface" is the interface through which a user enters their travel preferences.

[1025] "Analysis means" refers to a device or program that analyzes travel preferences obtained through a user interface.

[1026] An "emotion engine" is a technology that analyzes user input data to determine emotions and identify emotional states such as positive, negative, or neutral.

[1027] A "plan generation means" is a device or program that automatically generates a travel plan based on the analysis results obtained by the analysis means and the emotion engine.

[1028] "Display means" refers to a device or program that visualizes and displays the generated travel plan to the user.

[1029] A "booking method" refers to a device or program that makes an actual travel reservation based on a generated travel plan.

[1030] A "database" is an information aggregation system used to collect and manage the information necessary for generating travel plans.

[1031] "Natural language processing technology" is a technology that analyzes text data entered by a user and understands its content.

[1032] A "notification means" refers to a device or program that notifies the user of detailed travel-related information on the day of the trip.

[1033] This invention is a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, and further incorporates an emotion engine that recognizes and analyzes the user's emotions.

[1034] The system configuration is as follows: First, the user uses a user interface to enter their travel preferences. The user interface is a chat-style interface where users can enter their preferences as text. For example, they might enter a prompt message such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[1035] Next, this input data is sent to the server. After receiving the data, the server processes it using analysis tools and an emotion engine. The analysis tools utilize natural language processing technology (e.g., Google Cloud Natural Language API). This technology extracts important information from the user's input text, for example, extracting keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[1036] An emotion engine analyzes the user's emotional state from their input text (for example, IBM Watson Tone Analyzer), determining whether the user is in a positive, negative, or neutral emotional state. For example, it might analyze the input text to identify a positive emotion like "enjoyment."

[1037] Next, the server's plan generation mechanism automatically generates a travel plan based on the analyzed data and emotional state. The plan generation mechanism retrieves travel-related information from partner databases (e.g., travel agency databases, transportation databases, accommodation databases) and creates the optimal travel plan. For example, it collects information such as "bullet train operating times and fares," "hotel information," and "sushi restaurant information," and generates a plan that includes high-end restaurants based on a positive emotional state.

[1038] The generated travel plan is sent from the server to the user interface and displayed to the user via their device. The user can review the presented plan and select the necessary booking actions from the chat interface. For example, they can select "Shinkansen ticket booking" and "hotel booking."

[1039] Once the user has made their selection, the server uses the booking method to connect with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) and make the actual booking. Specifically, it accesses the Shinkansen (bullet train) booking system to reserve a ticket for the specified date and time, and similarly reserves a hotel.

[1040] Finally, on the day of travel, the server notifies the user of detailed travel information. For example, it sends the user the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant via the smartphone's notification function. This allows the user to enjoy their trip with peace of mind.

[1041] Thus, the system of the present invention allows users to easily and quickly plan their trips and to provide them with a unique experience that takes their emotions into consideration.

[1042] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1043] Step 1:

[1044] The user enters their travel preferences through a chat interface. Specifically, they enter prompts such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The input data obtained is "budget 100,000 yen," "Tokyo," and "sushi."

[1045] Step 2:

[1046] The terminal sends user input data to the server. The server receives this data and passes it on to the analysis tools and emotion engine. As input data, text obtained from the user interface is sent to the server.

[1047] Step 3:

[1048] The server's analysis method uses natural language processing technology (e.g., Google Cloud Natural Language API) to extract important information from the input data. Specifically, "budget of 100,000 yen," "Tokyo," and "sushi" are extracted. The extracted keywords are obtained as output data.

[1049] Step 4:

[1050] The server's emotion engine analyzes the user's input text and determines their emotional state (e.g., IBM Watson Tone Analyzer). Specifically, a positive emotion like "enjoyment" is analyzed. The analyzed emotional state is obtained as output data.

[1051] Step 5:

[1052] The server's plan generation mechanism generates an optimal travel plan based on input data (keywords and emotional states) obtained from the analysis mechanism and the emotion engine. It collects information such as "Shinkansen train schedules and fares," "hotel information," and "sushi restaurant information" from a partner database, and generates a plan including high-end restaurants based on positive emotional states. The generated travel plan is obtained as output data.

[1053] Step 6:

[1054] The server generates a travel plan and sends it to the user interface, which the terminal displays to the user. The user can then view the plan details on the user interface. The generated travel plan is sent to the user interface as input data.

[1055] Step 7:

[1056] The user reviews their travel plan via a chat interface and selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking." The user's booking selections are obtained as input data.

[1057] Step 8:

[1058] The terminal sends the user's selection to the server, which then coordinates with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) to make the actual booking. The Shinkansen (bullet train) and hotel bookings are completed. The booking completion information is provided as output data.

[1059] Step 9:

[1060] On the day of travel, the server notifies the user of detailed travel information. Specifically, this includes the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant. Detailed travel plan information is stored on the server as input data.

[1061] Through these steps, users can easily and quickly create travel plans based on their wishes and emotional state, make reservations, and enjoy their trip with peace of mind.

[1062] (Application Example 2)

[1063] 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."

[1064] Conventional travel plan generation systems have the functionality to generate and book travel plans based on user-inputted preferences, but they have the problem of not being able to adjust the suggested content to take into account the user's emotional state. Furthermore, even if travel plan generation and booking can be done in one go, a separate payment method is required, which is inconvenient for the user. In addition, there are insufficient means of notifying users of necessary information on the day of travel, which is an obstacle to the smooth running of the trip.

[1065] 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.

[1066] In this invention, the server includes a user interface for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions and associated emotional states obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results and emotional states obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation and payment means for making a reservation and payment for the trip in a single transaction based on the travel plan, and a notification means for displaying payment information associated with the travel plan on the user interface. This enables the proposal of a travel plan that takes the user's emotional state into consideration, and allows for a single reservation and payment. Furthermore, it enables smooth travel by quickly notifying the user of information they need on the day of the trip.

[1067] A "user interface" is the means by which a user interacts with a system and inputs their travel preferences.

[1068] "Analysis means" refers to means for analyzing travel preferences and associated emotional states obtained through the user interface.

[1069] The "plan generation means" is a means for automatically generating a travel plan based on the analysis results and emotional state obtained by the analysis means.

[1070] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[1071] "Booking and payment methods" refer to the means of making a single booking and payment for a trip based on a travel plan.

[1072] "Notification methods" refer to means of notifying users of payment information related to their travel plan and detailed information for the day of travel.

[1073] "Emotional state" refers to the emotional state analyzed based on user input, and includes positive, negative, neutral, etc.

[1074] "Natural language processing technology" is a technology that analyzes text information entered by users to understand its meaning and intent.

[1075] This invention is a system that allows users to input their travel preferences, automatically generates a travel plan based on those preferences, and handles all necessary reservations and payments in a single process. Furthermore, it can promptly notify users of necessary information on the day of travel.

[1076] Basic System Configuration

[1077] The system includes the following components:

[1078] 1. User Interface: The means by which users input their travel preferences. Specifically, this refers to applications on smartphones.

[1079] 2. Analysis Method: A method for analyzing user input and extracting travel preferences and emotional states. As a specific example, natural language processing techniques implemented using the Python transformers library will be used.

[1080] 3. Plan generation means: A means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotional state. It generates a plan that combines hotels, restaurants, transportation, etc. at the travel destination and is adjusted according to the emotional state.

[1081] 4. Display means: Means for presenting the generated travel plan to the user. Specifically, the details of the plan are displayed on the smartphone application screen.

[1082] 5. Booking and Payment Methods: A method for booking and paying for travel in a single transaction based on a travel plan. A dummy API can be used, but in a real environment, it will integrate with actual booking sites and payment systems.

[1083] 6. Notification method: A means of notifying the user of necessary information on the day of the trip.

[1084] System processing flow

[1085] The server first receives travel preferences from the user via the user interface. For example, text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" might be entered. At this time, the user's emotional state is also analyzed and classified as positive, negative, neutral, etc.

[1086] Next, the server generates a travel plan. Based on the information extracted by the analysis tools, it combines data on hotels, restaurants, and transportation options at the travel destination. If the user's emotional state is positive, suggestions are made to enhance user satisfaction, such as proposing a plan that includes a rich dinner course.

[1087] The generated travel plan is displayed on the smartphone application screen. Users can review this plan and make reservations and payments all at once. After the reservation and payment are complete, the system will notify the user in real time on the day of travel, providing all necessary information.

[1088] Specific example

[1089] For example, suppose the user entered the following:

[1090] My travel budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi. Please suggest a suitable itinerary.

[1091] In this case, the system automatically performs an analysis and extracts keywords such as "budget of 100,000 yen," "Tokyo," and "sushi," as well as positive emotions. The plan generation means then generates a plan combining the most suitable hotels, restaurants, bullet train information, etc., based on this information and presents it to the user. Once the user completes the reservation and payment, the necessary information for the day of travel is notified in a timely manner. In this way, as a form of implementing the invention, the user can create a travel plan simply and effectively.

[1092] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1093] Step 1:

[1094] Users enter their travel preferences via a smartphone application. The data entered is in text format and may include information such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The entered conditions include details about the trip, such as budget, desired destinations, and food preferences.

[1095] Step 2:

[1096] The terminal receives the user's desired conditions and sends them to the server. The server inputs the received data into an analysis device. This analysis device uses the Python transformers library to analyze the input data and extract important keywords ("Budget: 100,000 yen", "Place to go: Tokyo", "Food to eat: Sushi").

[1097] Step 3:

[1098] The server passes the data analyzed by the analysis means to the emotion state analysis engine. This engine analyzes the user's emotional state from the text obtained through the user interface. For example, if the user indicates a positive emotion such as excitement, the emotion analysis engine will determine that emotional state is "positive."

[1099] Step 4:

[1100] The server executes the plan generation means based on the information obtained from the analysis means and the sentiment analysis engine. The plan generation means accesses the database and automatically generates a travel plan based on the analyzed keywords. Specifically, it combines information on accommodations, restaurants, and bullet trains to create a plan that is adjusted according to the user's emotional state.

[1101] Step 5:

[1102] The server sends data to the display device to show the generated travel plan on the user's smartphone. The device then displays the details of the received travel plan to the user. The user interface displays a list of accommodations, restaurants, transportation, etc., included in the generated plan.

[1103] Step 6:

[1104] The user makes a reservation and payment based on the presented travel plan. The terminal receives the user's selection and sends that information to the server. The server, through the reservation and payment method, interacts with the reservation site and payment system included in the travel plan and executes the necessary reservations and payments in one go.

[1105] Step 7:

[1106] On the day of travel, the server notifies the user of payment information and other details related to the travel plan (such as Shinkansen departure times, hotel check-in information, and maps of recommended restaurants). This notification is made using the smartphone's notification function, allowing the user to receive the necessary information in real time.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] [Fourth Embodiment]

[1111] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1112] 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.

[1113] 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).

[1114] 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.

[1115] 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.

[1116] 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).

[1117] 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.

[1118] 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.

[1119] 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.

[1120] 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.

[1121] 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.

[1122] 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.

[1123] 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".

[1124] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[1125] Basic System Configuration

[1126] The system includes a user interface for the user to input their travel preferences, an analysis means for analyzing the input information, a plan generation means for generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, and a reservation means for making reservations. Furthermore, it also includes a means for notifying the user of travel information for the day.

[1127] User input

[1128] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might enter text such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[1129] Data analysis

[1130] The server receives input data from the user and performs analysis using natural language processing techniques. Specifically, it analyzes the text and extracts important information such as budget, destination, and desired food.

[1131] Travel plan generation

[1132] The server's plan generation system automatically generates travel plans based on analysis results. This plan generation includes a function to search for the most suitable candidates from databases the system partners with (airlines, railway companies, hotels, restaurants, etc.). For example, it generates a plan that combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market based on the acquired information.

[1133] Presentation of the plan

[1134] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[1135] Reservation operation

[1136] Based on the plan presented, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[1137] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[1138] Travel Guide

[1139] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[1140] Specific example

[1141] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[1142] 1. The analysis method extracts "100,000 yen," "Tokyo," and "sushi" from the text.

[1143] 2. The plan generation method collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate travel plans.

[1144] 3. The generated plan is displayed in the user interface, and the user confirms it.

[1145] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[1146] 5. The server uses the reservation method to complete the reservation in cooperation with the partner Shinkansen reservation system and hotel reservation system.

[1147] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[1148] As described above, the system of the present invention allows users to easily and quickly create travel plans and make all reservations seamlessly.

[1149] The following describes the processing flow.

[1150] Step 1:

[1151] The user accesses the chat interface and enters their travel preferences. Specifically, they enter their budget, destination, and desired food in text format. For example, they might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[1152] Step 2:

[1153] The terminal sends user input data to the server. The input data is sent to the server as an HTTP request. The data is composed of JSON or text format.

[1154] Step 3:

[1155] The server receives input data from the user and passes it to the analysis tool. The analysis tool uses natural language processing technology to extract important information from the input data. Specifically, it extracts keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[1156] Step 4:

[1157] The server's plan generation mechanism automatically generates travel plans based on analysis results obtained from the analysis mechanism. This includes searching and retrieving the most suitable candidates from affiliated databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares.

[1158] Step 5:

[1159] The server generates a travel plan (for example, Shinkansen bullet train tickets, a business hotel in Ginza, and three sushi restaurants around Tsukiji Market), converts it into data for display, and sends it to the terminal. The display data is in JSON format.

[1160] Step 6:

[1161] The device displays the received travel plan on the user interface. The user can then check the specific plan details via the chat interface.

[1162] Step 7:

[1163] Based on the plan presented, the user selects the necessary booking actions. Specifically, they select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[1164] Step 8:

[1165] The device sends the user's selection to the server. The selection is sent to the server as an HTTP request in JSON format.

[1166] Step 9:

[1167] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API and sends the necessary information to execute the reservation.

[1168] Step 10:

[1169] The server receives the reservation confirmation and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[1170] Step 11:

[1171] The terminal displays the reservation confirmation result on the user interface and notifies the user. The user confirms that the reservation is complete.

[1172] Step 12:

[1173] On the day of travel, the server notifies the user of travel details (e.g., Shinkansen departure time, hotel check-in information, sushi restaurant map and operating hours). Notifications are sent via SMS, email, or a chat interface.

[1174] Step 13:

[1175] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[1176] (Example 1)

[1177] 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".

[1178] Traditional travel booking systems had a complex process for users to input their travel preferences, making it difficult to quickly and efficiently generate travel plans that met their needs. Furthermore, the need to use multiple booking sites meant users had to go through the process of making individual reservations, which was time-consuming. Additionally, the lack of adequate advance notification of travel-related information meant that users were unable to enjoy their trips smoothly.

[1179] 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.

[1180] In this invention, the server includes an information analysis means for analyzing travel preferences obtained through a user interface, a plan generation means for automatically generating a travel plan based on the analysis results, a display means for displaying the generated travel plan, a reservation means for making reservations, and a search means for searching for the best candidate from affiliated information sources and constructing a travel plan. This allows users to easily and quickly create a travel plan and make all reservations seamlessly. Furthermore, by notifying users of detailed information on the day of travel in advance, users can enjoy their trip smoothly.

[1181] A "user interface" is the interface through which a user interacts with a system and inputs their travel preferences.

[1182] "Information analysis means" refers to a means of analyzing travel preferences obtained through a user interface and extracting important information.

[1183] A "plan generation means" is a means for automatically generating a travel plan based on the analysis results obtained by an information analysis means.

[1184] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[1185] "Reservation method" refers to the means of making travel reservations based on a travel plan.

[1186] "Search methods" refer to the means of searching for the best candidates from affiliated information sources and constructing a travel plan.

[1187] This invention is a system that allows users to input their desired travel conditions, automatically generates and presents a travel plan based on those conditions, and makes the necessary reservations. Embodiments of this invention will be described in detail below.

[1188] User input

[1189] First, the user enters their travel preferences. The user enters their preferences in text format using a chat interface or a dedicated application. For example, the user might enter, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[1190] Data analysis

[1191] The server receives user input data and uses analysis tools to analyze the text using natural language processing techniques. Specifically, it uses NLP libraries (e.g., spaCy, NLTK) to extract important information such as "100,000 yen," "Tokyo," and "sushi." This analysis clarifies the user's desired conditions.

[1192] Travel plan generation

[1193] Next, the server's plan generation mechanism automatically generates a travel plan based on the analysis results. To do this, the server obtains data from multiple partner information sources (e.g., airline databases, hotel reservation systems, restaurant information) via APIs. Specifically, it obtains Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market, and combines them to construct the optimal travel plan.

[1194] Presentation of the plan

[1195] The generated travel plan is sent from the server to the device. The device displays the received plan to the user. The user can review this plan through a chat interface or application.

[1196] Reservation operation

[1197] Based on the presented travel plan, the user performs the necessary booking operations. For example, they might select "Shinkansen ticket booking" and "hotel booking." The terminal sends the user's selection information to the server, which then uses the booking method to complete the booking in conjunction with partner booking systems (e.g., Shinkansen booking API, hotel booking API).

[1198] Travel Guide

[1199] On the day of travel, the server notifies the user of detailed travel information (such as the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant). This allows the user to enjoy their trip with peace of mind.

[1200] Specific example

[1201] As a concrete example, here's how the system would handle a user who enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface:

[1202] 1. The user enters the text "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface.

[1203] 2. The server analyzes this received text using an NLP library and extracts the information "100,000 yen," "Tokyo," and "sushi."

[1204] 3. The server retrieves Shinkansen (bullet train) operation information, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market from partner APIs, and generates the optimal travel plan based on this information.

[1205] 4. The server sends the generated travel plan to the terminal, and the terminal displays the plan to the user.

[1206] 5. The user makes a reservation based on the plan, and the device sends the selection information to the server.

[1207] 6. The server uses the reservation method to complete the reservation in cooperation with the partner reservation system.

[1208] 7. On the day of travel, the server will notify the user of detailed travel information to support a smooth trip.

[1209] This invention allows users to easily and quickly plan their trips through a series of operations and make all reservations seamlessly. Furthermore, detailed information for the day of travel is provided in advance, allowing users to enjoy their trip with peace of mind.

[1210] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1211] Step 1:

[1212] The user enters their travel preferences into the chat interface.

[1213] Specific actions: The user opens a browser or mobile app, enters text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" into the chat interface, and clicks the send button.

[1214] Input: Text information entered by the user.

[1215] Output: Text data containing the user's desired conditions.

[1216] Step 2:

[1217] The server receives input data sent from the user.

[1218] Specific operation: The server receives the user's input data as an HTTP request and begins processing to parse its contents.

[1219] Input: HTTP request sent by the user.

[1220] Output: A string containing the user's input data.

[1221] Step 3:

[1222] The server uses analysis tools to analyze the text using natural language processing techniques.

[1223] Specific operation: The server uses an NLP library (e.g., spaCy, NLTK) to extract the keywords "100,000 yen," "Tokyo," and "sushi" from the text.

[1224] Input: User-input text data.

[1225] Output: Extracted keyword information (e.g., "100,000 yen", "Tokyo", "sushi").

[1226] Step 4:

[1227] The server's plan generation mechanism automatically generates a travel plan based on the analysis results.

[1228] Specific operation: The server calls APIs it partners with (e.g., travel agency API, hotel booking API) and builds the optimal travel plan based on the information obtained. Specifically, it combines Shinkansen (bullet train) operating times and fares, hotel information in Tokyo, and sushi restaurant information around Tsukiji Market.

[1229] Input: Extracted keyword information.

[1230] Output: Detailed data of an automatically generated travel plan.

[1231] Step 5:

[1232] The server sends the details of the generated travel plan to the user interface.

[1233] Specific operation: The server converts the generated travel plan into JSON format and sends it to the frontend.

[1234] Input: Detailed data of the travel plan.

[1235] Output: Travel plan converted to JSON format.

[1236] Step 6:

[1237] The terminal receives data from the server and displays it in the user interface.

[1238] Specific operation: The device (browser or mobile app) parses the JSON data received from the server and displays it in the user interface.

[1239] Input: JSON data received from the server.

[1240] Output: A screen display of the travel plan that the user can view.

[1241] Step 7:

[1242] The user reviews the presented travel plan and selects the necessary booking actions.

[1243] Specific actions: The user selects "Shinkansen ticket reservation" and "Hotel reservation" from the chat interface or reservation button, and then presses the submit button.

[1244] Input: Travel plan selection information.

[1245] Output: User-selected reservation details.

[1246] Step 8:

[1247] The terminal sends the user's selection to the server.

[1248] Specific operation: The terminal generates an HTTP request containing the user's selection information and sends it to the server.

[1249] Input: User selection information.

[1250] Output: HTTP request sent to the server.

[1251] Step 9:

[1252] The server uses the reservation method and completes the reservation in cooperation with partner reservation sites and services.

[1253] Specific operation: The server calls a reservation API (e.g., Shinkansen reservation API, hotel reservation API) and executes the reservation process.

[1254] Input: User selection information.

[1255] Output: Confirmed reservation information.

[1256] Step 10:

[1257] The server will notify the user of detailed information for the day of the trip.

[1258] Specific operation: The server generates a notification message containing information such as the Shinkansen departure time, hotel check-in information, and a map of a sushi restaurant, and sends it to the user.

[1259] Input: Confirmed reservation information.

[1260] Output: A notification message containing detailed information for the day of travel.

[1261] (Application Example 1)

[1262] 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".

[1263] In recent years, users have a growing need to efficiently plan and consume not only travel but also video content. However, current systems cannot integrate travel planning with content recommendations and scheduling. As a result, users must plan each piece of content individually, which is a time-consuming and laborious process. Therefore, there is a need for a system that, based on the user's input preferences, recommends content to watch and automatically generates a viewing schedule, in addition to providing travel plans.

[1264] 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.

[1265] In this invention, the server includes a user interface means for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation means for making a travel reservation based on the travel plan, a means for obtaining recommended content based on the desired travel conditions, and a means for generating a viewing schedule based on the recommended content. This makes it possible for the user to generate a travel plan, recommend viewing content, and generate a viewing schedule in an integrated manner, significantly reducing the effort required for planning.

[1266] "Travel preferences" refer to the various conditions that users desire when traveling, and specifically include budget, destination, and food preferences.

[1267] A "user interface" is a means by which a user interacts with a system and inputs or confirms information. Specific examples include chat interfaces and touchscreens.

[1268] "Analysis means" refers to a function that analyzes the desired conditions entered by the user and extracts useful information, and it is common to use natural language processing technology.

[1269] "Plan generation method" refers to a function that automatically generates travel plans and recommendations for viewing content based on analyzed preferences.

[1270] "Display means" refers to a function that presents the generated travel plan or viewing schedule to the user, and this includes displays and mobile screens.

[1271] "Reservation method" refers to a function that automatically makes necessary reservations (such as accommodation and transportation) based on the generated travel plan.

[1272] "Recommended content" refers to video content that is recommended for viewing based on the user's entered preferences.

[1273] A "viewing schedule" refers to a planned timetable designed to allow users to efficiently view recommended content.

[1274] This invention is a system that allows users to input their desired viewing conditions, automatically generates an optimal viewing plan based on those conditions, presents recommended content, and creates a viewing schedule. Embodiments of the present invention will be described in detail below.

[1275] Basic System Configuration

[1276] The system has the following main features:

[1277] 1. User Interface: A chat interface on a smartphone application or web browser will be used as a means for users to input their desired viewing conditions.

[1278] 2. Analysis method: The server uses natural language processing technology (e.g., Python's NLP library) to analyze the user's input preferences and extract important information such as budget, genre, and viewing time.

[1279] 3. Plan generation method: The server automatically generates a viewing plan based on the analysis results. To generate the viewing plan, recommended content is obtained using the API of a video content distribution service (e.g., video content distribution API), and a viewing schedule is created.

[1280] 4. Display method: The generated viewing plan will be displayed on the screen of a smartphone or computer and presented to the user visually.

[1281] User input

[1282] Users enter their viewing preferences using a chat interface. A typical prompt might be, "My budget is 5000 yen, the location is my home, and I want pizza." This interface is designed to be intuitive and allow users to easily enter their preferences.

[1283] Data analysis

[1284] The server receives input data from the user and performs analysis using natural language processing (NLP) techniques. The server uses Python's NLP library to analyze the text and extract important information such as budget, location, and desired cuisine. For example, it receives the text "My budget is 5000 yen, the location is my home, and the desired cuisine is pizza," and extracts the information for each item.

[1285] Creating a viewing plan

[1286] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation includes a function to search for the most suitable candidates using the API of a video content distribution service. For example, it generates a list of recommended movies and dramas based on the acquired information and schedules them according to viewing time.

[1287] Presentation of the plan

[1288] The server displays the details of the generated viewing plan on the user interface, and the device (smartphone or PC) presents it to the user. The user can confirm the generated plan through the chat interface.

[1289] for example,

[1290] The budget is 5000 yen, the location is my home, and the food I want to eat is pizza.

[1291] When you enter,

[1292] 1. The analysis method extracts "5000 yen," "home," and "pizza" from the text.

[1293] 2. The plan generation method uses a video content distribution service API to collect movies and dramas that can be viewed within the budget and generates a viewing schedule.

[1294] 3. The generated plan is displayed in the user interface, and the user confirms it.

[1295] This allows users to easily and quickly create viewing plans and efficiently consume all available content.

[1296] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1297] Step 1:

[1298] The user accesses the chat interface and enters their desired viewing conditions. For example, they might enter, "My budget is 5000 yen, the location is my home, and I want pizza." This input data is then sent to the server.

[1299] Input: User's desired viewing conditions (e.g., "Budget: 5000 yen, Location: Home, Food I want to eat: Pizza")

[1300] Output: Input data is sent to the server.

[1301] Step 2:

[1302] The server analyzes the user's input data. Natural language processing techniques (e.g., Python's NLP library) are used for the analysis. Through this process, the server extracts each element of the desired conditions (budget, location, food).

[1303] Input: User viewing preferences submitted in Step 1

[1304] Processing: Use natural language processing techniques to extract budget, location, and desired cuisine.

[1305] Output: Analyzed desired conditions (e.g., budget = 5000 yen, location = home, food desired = pizza)

[1306] Step 3:

[1307] The server's plan generation mechanism automatically generates a viewing plan based on the analysis results. This plan generation uses the API of the video content distribution service. Based on the acquired information, the server creates a list of movies and dramas that can be viewed.

[1308] Input: Desired conditions analyzed in Step 2

[1309] Process: Use the API of the video content distribution service to retrieve viewable content.

[1310] Output: List of recommended content (e.g., Movie A, TV series B)

[1311] Step 4:

[1312] The server generates a viewing schedule based on recommended content. The schedule is created based on the playback time of each piece of content and the user's viewing preferences.

[1313] Input: List of recommended content

[1314] Processing: Create a viewing schedule, taking into account the playback time of each piece of content.

[1315] Output: Viewing schedule (Example: 19:00 - Movie A, 21:00 - Drama B)

[1316] Step 5:

[1317] The server displays the details of the viewing plan generated by the server on the user interface, showing them on the screen of a smartphone or computer. This allows the user to check recommended content and viewing schedules.

[1318] Input: Viewing schedule

[1319] Processing: Display the viewing schedule in the user interface.

[1320] Output: Viewing schedule displayed on the user interface

[1321] Step 6:

[1322] Users can review the presented viewing plan and adjust their viewing schedule as needed. Furthermore, by initiating a viewing start, the server will coordinate with the video content distribution service and begin playback.

[1323] Input: User verification and adjustment instructions, instructions to start viewing.

[1324] Processing: Based on user instructions, adjust the viewing schedule and initiate viewing.

[1325] Output: Start playback (playback of video content)

[1326] 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.

[1327] This invention relates to a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, all while incorporating an emotion engine that recognizes and analyzes the user's emotions. Embodiments of this invention will be described in detail below.

[1328] Basic System Configuration

[1329] This system includes a user interface for users to input their travel preferences, an analysis means and emotion engine for analyzing the input information and associated emotions, a plan generation means for automatically generating a travel plan based on the analysis results and emotional state, a display means for displaying the generated travel plan, and a reservation means for making reservations based on the travel plan. Furthermore, it also includes a notification means for informing the user of travel information for the day.

[1330] User input

[1331] The user accesses the chat interface and enters their travel preferences (e.g., budget, desired destinations, food). For example, they might type, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[1332] Data analysis

[1333] The server receives input data from the user and passes it to the analysis tool and the emotion engine. The analysis tool uses natural language processing technology to extract important information from the input data. For example, it might extract keywords such as "budget 100,000 yen," "Tokyo," and "sushi." Meanwhile, the emotion engine analyzes the user's input text and determines their emotional state, such as positive, negative, or neutral.

[1334] Travel plan generation

[1335] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. This includes searching and retrieving the most suitable candidates from partner databases (e.g., information on airlines, railway companies, hotels, and restaurants). For example, it collects hotel information in Tokyo, sushi restaurant information around Tsukiji Market, and Shinkansen (bullet train) operating times and fares. Furthermore, it adjusts the content of the travel plan based on the user's emotional state. For example, if the emotional state is positive, it recommends a slightly more expensive restaurant, and if the emotional state is negative, it adds relaxing sightseeing spots.

[1336] Presentation of the plan

[1337] The server displays the details of the generated travel plan on the user interface, and the terminal presents it to the user. The user can then review the generated plan through the chat interface.

[1338] Reservation operation

[1339] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[1340] The terminal sends the user's selection to the server, which uses the booking method to coordinate with partner booking sites and services to make the actual booking.

[1341] Travel Guide

[1342] On the day of travel, the server notifies the user of detailed travel information (e.g., Shinkansen departure time, hotel check-in information, map to recommended sushi restaurant, etc.). This allows the user to enjoy their trip with peace of mind.

[1343] Specific example

[1344] For example, if a user enters "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi" into the chat interface, the process will proceed as follows:

[1345] 1. The analysis tool extracts "100,000 yen," "Tokyo," and "sushi" from the text. Meanwhile, the emotion engine analyzes the positive emotion of "enjoyment."

[1346] 2. The plan generation system collects and combines information on Shinkansen train schedules and fares, hotel information in Tokyo, and sushi restaurants around Tsukiji Market to generate a travel plan. Based on the results of the emotion engine, it proposes a plan that includes a special dinner course.

[1347] 3. The generated plan is displayed in the user interface, and the user confirms it.

[1348] 4. The user is satisfied with the plan and chooses to book the bullet train and hotel.

[1349] 5. The server uses the reservation method to coordinate with the Shinkansen reservation system and the hotel reservation system to complete the reservation.

[1350] 6. On the day of the trip, the server notifies the user of detailed travel information, allowing the user to enjoy the trip smoothly.

[1351] As described above, the system of the present invention allows users to easily and quickly plan their trips and provides them with a unique experience that takes their emotions into consideration.

[1352] The following describes the processing flow.

[1353] Step 1:

[1354] The user accesses the chat interface and enters their travel preferences. For example, they might type, "My budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi."

[1355] Step 2:

[1356] The device sends the user's input data to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[1357] Step 3:

[1358] The server receives input data from the user and passes it to the analysis unit and the emotion engine. The analysis unit then passes the input data to the natural language processing engine.

[1359] Step 4:

[1360] The server's analysis tools extract important information from the input data. For example, it might extract the keywords "budget 100,000 yen," "Tokyo," and "sushi" from the input text.

[1361] Step 5:

[1362] The server's emotion engine analyzes the input data and determines the user's emotional state. For example, the emotion engine might analyze the input text to identify a positive emotion such as "enjoyment."

[1363] Step 6:

[1364] The server's plan generation mechanism automatically generates travel plans based on analysis results and emotional states obtained from the analysis mechanism and emotion engine. Specifically, it searches for the best candidates from partner databases (information on airlines, railway companies, hotels, and restaurants) and adjusts the plan content based on the user's emotional state.

[1365] Step 7:

[1366] The server converts the travel plan details it generates into display data and sends it to the terminal. The display data is in JSON format.

[1367] Step 8:

[1368] The device displays the received travel plan in the chat interface. The user can then review the specific plan details.

[1369] Step 9:

[1370] Based on the plan presented, the user selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking" via the chat interface.

[1371] Step 10:

[1372] The device sends the user's selection to the server. The selection data is sent to the server as an HTTP request in JSON format.

[1373] Step 11:

[1374] The server uses a reservation system to make reservations for bullet trains and hotels. Specifically, it calls the bullet train reservation API and the hotel reservation API, sends the necessary information, and completes the reservation.

[1375] Step 12:

[1376] The server receives the reservation confirmation result and sends it to the terminal. The reservation details and confirmed information are sent in JSON format.

[1377] Step 13:

[1378] The device displays the reservation confirmation result in the chat interface and notifies the user. The user can then confirm that the reservation is complete.

[1379] Step 14:

[1380] On the day of travel, the server notifies the user of travel details. For example, it may notify them of the Shinkansen departure time, hotel check-in information, and a map and operating hours of a recommended sushi restaurant. Notifications are sent via SMS, email, or a chat interface.

[1381] Step 15:

[1382] Users can check the information they need on the day of their trip and enjoy their trip with peace of mind.

[1383] (Example 2)

[1384] 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".

[1385] Conventional automated travel plan generation systems could provide plans based on user preferences, but they struggled to provide plans that took into account the user's emotional state at that moment. As a result, they were unable to provide the ideal travel experience that users envisioned, and thus failed to increase user satisfaction.

[1386] 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.

[1387] In this invention, the server includes a user interface means for inputting travel preferences, an analysis means including an emotion engine for analyzing the user's emotions, and a plan generation means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotion engine. This makes it possible to provide a travel plan that takes into account both the user's preferences and emotional state.

[1388] A "user interface" is the interface through which a user enters their travel preferences.

[1389] "Analysis means" refers to a device or program that analyzes travel preferences obtained through a user interface.

[1390] An "emotion engine" is a technology that analyzes user input data to determine emotions and identify emotional states such as positive, negative, or neutral.

[1391] A "plan generation means" is a device or program that automatically generates a travel plan based on the analysis results obtained by the analysis means and the emotion engine.

[1392] "Display means" refers to a device or program that visualizes and displays the generated travel plan to the user.

[1393] A "booking method" refers to a device or program that makes an actual travel reservation based on a generated travel plan.

[1394] A "database" is an information aggregation system used to collect and manage the information necessary for generating travel plans.

[1395] "Natural language processing technology" is a technology that analyzes text data entered by a user and understands its content.

[1396] A "notification means" refers to a device or program that notifies the user of detailed travel-related information on the day of the trip.

[1397] This invention is a system that takes user travel preferences as input, automatically generates and presents travel plans based on those preferences, and makes necessary reservations, and further incorporates an emotion engine that recognizes and analyzes the user's emotions.

[1398] The system configuration is as follows: First, the user uses a user interface to enter their travel preferences. The user interface is a chat-style interface where users can enter their preferences as text. For example, they might enter a prompt message such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi."

[1399] Next, this input data is sent to the server. After receiving the data, the server processes it using analysis tools and an emotion engine. The analysis tools utilize natural language processing technology (e.g., Google Cloud Natural Language API). This technology extracts important information from the user's input text, for example, extracting keywords such as "budget 100,000 yen," "Tokyo," and "sushi."

[1400] An emotion engine analyzes the user's emotional state from their input text (for example, IBM Watson Tone Analyzer), determining whether the user is in a positive, negative, or neutral emotional state. For example, it might analyze the input text to identify a positive emotion like "enjoyment."

[1401] Next, the server's plan generation mechanism automatically generates a travel plan based on the analyzed data and emotional state. The plan generation mechanism retrieves travel-related information from partner databases (e.g., travel agency databases, transportation databases, accommodation databases) and creates the optimal travel plan. For example, it collects information such as "bullet train operating times and fares," "hotel information," and "sushi restaurant information," and generates a plan that includes high-end restaurants based on a positive emotional state.

[1402] The generated travel plan is sent from the server to the user interface and displayed to the user via their device. The user can review the presented plan and select the necessary booking actions from the chat interface. For example, they can select "Shinkansen ticket booking" and "hotel booking."

[1403] Once the user has made their selection, the server uses the booking method to connect with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) and make the actual booking. Specifically, it accesses the Shinkansen (bullet train) booking system to reserve a ticket for the specified date and time, and similarly reserves a hotel.

[1404] Finally, on the day of travel, the server notifies the user of detailed travel information. For example, it sends the user the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant via the smartphone's notification function. This allows the user to enjoy their trip with peace of mind.

[1405] Thus, the system of the present invention allows users to easily and quickly plan their trips and to provide them with a unique experience that takes their emotions into consideration.

[1406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1407] Step 1:

[1408] The user enters their travel preferences through a chat interface. Specifically, they enter prompts such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The input data obtained is "budget 100,000 yen," "Tokyo," and "sushi."

[1409] Step 2:

[1410] The terminal sends user input data to the server. The server receives this data and passes it on to the analysis tools and emotion engine. As input data, text obtained from the user interface is sent to the server.

[1411] Step 3:

[1412] The server's analysis method uses natural language processing technology (e.g., Google Cloud Natural Language API) to extract important information from the input data. Specifically, "budget of 100,000 yen," "Tokyo," and "sushi" are extracted. The extracted keywords are obtained as output data.

[1413] Step 4:

[1414] The server's emotion engine analyzes the user's input text and determines their emotional state (e.g., IBM Watson Tone Analyzer). Specifically, a positive emotion like "enjoyment" is analyzed. The analyzed emotional state is obtained as output data.

[1415] Step 5:

[1416] The server's plan generation mechanism generates an optimal travel plan based on input data (keywords and emotional states) obtained from the analysis mechanism and the emotion engine. It collects information such as "Shinkansen train schedules and fares," "hotel information," and "sushi restaurant information" from a partner database, and generates a plan including high-end restaurants based on positive emotional states. The generated travel plan is obtained as output data.

[1417] Step 6:

[1418] The server generates a travel plan and sends it to the user interface, which the terminal displays to the user. The user can then view the plan details on the user interface. The generated travel plan is sent to the user interface as input data.

[1419] Step 7:

[1420] The user reviews their travel plan via a chat interface and selects the necessary booking actions. For example, they might select "Shinkansen ticket booking" and "hotel booking." The user's booking selections are obtained as input data.

[1421] Step 8:

[1422] The terminal sends the user's selection to the server, which then coordinates with partner booking sites and services (e.g., transportation booking systems, accommodation booking systems) to make the actual booking. The Shinkansen (bullet train) and hotel bookings are completed. The booking completion information is provided as output data.

[1423] Step 9:

[1424] On the day of travel, the server notifies the user of detailed travel information. Specifically, this includes the Shinkansen departure time, hotel check-in information, and a map to a recommended sushi restaurant. Detailed travel plan information is stored on the server as input data.

[1425] Through these steps, users can easily and quickly create travel plans based on their wishes and emotional state, make reservations, and enjoy their trip with peace of mind.

[1426] (Application Example 2)

[1427] 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".

[1428] Conventional travel plan generation systems have the functionality to generate and book travel plans based on user-inputted preferences, but they have the problem of not being able to adjust the suggested content to take into account the user's emotional state. Furthermore, even if travel plan generation and booking can be done in one go, a separate payment method is required, which is inconvenient for the user. In addition, there are insufficient means of notifying users of necessary information on the day of travel, which is an obstacle to the smooth running of the trip.

[1429] 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.

[1430] In this invention, the server includes a user interface for inputting desired travel conditions, an analysis means for analyzing the desired travel conditions and associated emotional states obtained through the user interface, a plan generation means for automatically generating a travel plan based on the analysis results and emotional states obtained by the analysis means, a display means for displaying the travel plan generated by the plan generation means, a reservation and payment means for making a reservation and payment for the trip in a single transaction based on the travel plan, and a notification means for displaying payment information associated with the travel plan on the user interface. This enables the proposal of a travel plan that takes the user's emotional state into consideration, and allows for a single reservation and payment. Furthermore, it enables smooth travel by quickly notifying the user of information they need on the day of the trip.

[1431] A "user interface" is the means by which a user interacts with a system and inputs their travel preferences.

[1432] "Analysis means" refers to means for analyzing travel preferences and associated emotional states obtained through the user interface.

[1433] The "plan generation means" is a means for automatically generating a travel plan based on the analysis results and emotional state obtained by the analysis means.

[1434] "Display means" refers to means for displaying the travel plan generated by the plan generation means to the user.

[1435] "Booking and payment methods" refer to the means of making a single booking and payment for a trip based on a travel plan.

[1436] "Notification methods" refer to means of notifying users of payment information related to their travel plan and detailed information for the day of travel.

[1437] "Emotional state" refers to the emotional state analyzed based on user input, and includes positive, negative, neutral, etc.

[1438] "Natural language processing technology" is a technology that analyzes text information entered by users to understand its meaning and intent.

[1439] This invention is a system that allows users to input their travel preferences, automatically generates a travel plan based on those preferences, and handles all necessary reservations and payments in a single process. Furthermore, it can promptly notify users of necessary information on the day of travel.

[1440] Basic System Configuration

[1441] The system includes the following components:

[1442] 1. User Interface: The means by which users input their travel preferences. Specifically, this refers to applications on smartphones.

[1443] 2. Analysis Method: A method for analyzing user input and extracting travel preferences and emotional states. As a specific example, natural language processing techniques implemented using the Python transformers library will be used.

[1444] 3. Plan generation means: A means for automatically generating a travel plan based on the analysis results obtained by the analysis means and the emotional state. It generates a plan that combines hotels, restaurants, transportation, etc. at the travel destination and is adjusted according to the emotional state.

[1445] 4. Display means: Means for presenting the generated travel plan to the user. Specifically, the details of the plan are displayed on the smartphone application screen.

[1446] 5. Booking and Payment Methods: A method for booking and paying for travel in a single transaction based on a travel plan. A dummy API can be used, but in a real environment, it will integrate with actual booking sites and payment systems.

[1447] 6. Notification method: A means of notifying the user of necessary information on the day of the trip.

[1448] System processing flow

[1449] The server first receives travel preferences from the user via the user interface. For example, text such as "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi" might be entered. At this time, the user's emotional state is also analyzed and classified as positive, negative, neutral, etc.

[1450] Next, the server generates a travel plan. Based on the information extracted by the analysis tools, it combines data on hotels, restaurants, and transportation options at the travel destination. If the user's emotional state is positive, suggestions are made to enhance user satisfaction, such as proposing a plan that includes a rich dinner course.

[1451] The generated travel plan is displayed on the smartphone application screen. Users can review this plan and make reservations and payments all at once. After the reservation and payment are complete, the system will notify the user in real time on the day of travel, providing all necessary information.

[1452] Specific example

[1453] For example, suppose the user entered the following:

[1454] My travel budget is 100,000 yen, and I want to go to Tokyo. I want to eat sushi. Please suggest a suitable itinerary.

[1455] In this case, the system automatically performs an analysis and extracts keywords such as "budget of 100,000 yen," "Tokyo," and "sushi," as well as positive emotions. The plan generation means then generates a plan combining the most suitable hotels, restaurants, bullet train information, etc., based on this information and presents it to the user. Once the user completes the reservation and payment, the necessary information for the day of travel is notified in a timely manner. In this way, as a form of implementing the invention, the user can create a travel plan simply and effectively.

[1456] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1457] Step 1:

[1458] Users enter their travel preferences via a smartphone application. The data entered is in text format and may include information such as, "My budget is 100,000 yen, I want to go to Tokyo, and I want to eat sushi." The entered conditions include details about the trip, such as budget, desired destinations, and food preferences.

[1459] Step 2:

[1460] The terminal receives the user's desired conditions and sends them to the server. The server inputs the received data into an analysis device. This analysis device uses the Python transformers library to analyze the input data and extract important keywords ("Budget: 100,000 yen", "Place to go: Tokyo", "Food to eat: Sushi").

[1461] Step 3:

[1462] The server passes the data analyzed by the analysis means to the emotion state analysis engine. This engine analyzes the user's emotional state from the text obtained through the user interface. For example, if the user indicates a positive emotion such as excitement, the emotion analysis engine will determine that emotional state is "positive."

[1463] Step 4:

[1464] The server executes the plan generation means based on the information obtained from the analysis means and the sentiment analysis engine. The plan generation means accesses the database and automatically generates a travel plan based on the analyzed keywords. Specifically, it combines information on accommodations, restaurants, and bullet trains to create a plan that is adjusted according to the user's emotional state.

[1465] Step 5:

[1466] The server sends data to the display device to show the generated travel plan on the user's smartphone. The device then displays the details of the received travel plan to the user. The user interface displays a list of accommodations, restaurants, transportation, etc., included in the generated plan.

[1467] Step 6:

[1468] The user makes a reservation and payment based on the presented travel plan. The terminal receives the user's selection and sends that information to the server. The server, through the reservation and payment method, interacts with the reservation site and payment system included in the travel plan and executes the necessary reservations and payments in one go.

[1469] Step 7:

[1470] On the day of travel, the server notifies the user of payment information and other details related to the travel plan (such as Shinkansen departure times, hotel check-in information, and maps of recommended restaurants). This notification is made using the smartphone's notification function, allowing the user to receive the necessary information in real time.

[1471] 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.

[1472] 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.

[1473] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1474] 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.

[1475] 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.

[1476] 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.

[1477] 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.

[1478] 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.

[1479] 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."

[1480] 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.

[1481] 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.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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.

[1491] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1492] The following is further disclosed regarding the embodiments described above.

[1493] (Claim 1)

[1494] A user interface for entering travel preferences,

[1495] An analysis means for analyzing travel preferences obtained through the user interface,

[1496] A plan generation means that automatically generates a travel plan based on the analysis results obtained by the aforementioned analysis means,

[1497] A display means for displaying the travel plan generated by the plan generation means,

[1498] A booking method for making travel reservations based on the aforementioned travel plan,

[1499] A system that includes this.

[1500] (Claim 2)

[1501] The system according to claim 1, wherein the reservation means includes means for notifying the user of travel reservation information on the day of travel.

[1502] (Claim 3)

[1503] The system according to claim 1, wherein the analysis means analyzes the desired conditions input by the user using natural language processing technology.

[1504] "Example 1"

[1505] (Claim 1)

[1506] A user interface for entering travel preferences,

[1507] Information analysis means for analyzing travel preferences obtained through the user interface,

[1508] A plan generation means that automatically generates a travel plan based on the analysis results obtained by the information analysis means,

[1509] A display means for displaying the travel plan generated by the plan generation means,

[1510] A booking method for making travel reservations based on the aforementioned travel plan,

[1511] Search tools to find the best candidates from our partner information sources and build your travel plan,

[1512] A system that includes this.

[1513] (Claim 2)

[1514] The system according to claim 1, wherein the reservation means includes means for notifying the user of travel reservation information on the day of travel.

[1515] (Claim 3)

[1516] The system according to claim 1, wherein the information analysis means analyzes the desired conditions input by the user using natural language processing technology.

[1517] "Application Example 1"

[1518] (Claim 1)

[1519] A user interface for entering travel preferences,

[1520] An analysis means for analyzing travel preferences obtained through the user interface,

[1521] A plan generation means that automatically generates a travel plan based on the analysis results obtained by the aforementioned analysis means,

[1522] A display means for displaying the travel plan generated by the plan generation means,

[1523] A booking method for making travel reservations based on the aforementioned travel plan,

[1524] A means of obtaining recommended content based on the desired conditions for the aforementioned trip,

[1525] A means for generating a viewing schedule based on the recommended content,

[1526] A system that includes this.

[1527] (Claim 2)

[1528] The system according to claim 1, wherein the reservation means includes means for notifying the user of travel reservation information on the day of travel.

[1529] (Claim 3)

[1530] The system according to claim 1, wherein the analysis means analyzes the desired conditions input by the user using natural language processing technology.

[1531] "Example 2 of combining an emotion engine"

[1532] (Claim 1)

[1533] A user interface for entering travel preferences,

[1534] An analysis means for analyzing travel preferences obtained through the user interface,

[1535] The analysis means includes an emotion engine for analyzing the user's emotions,

[1536] A plan generation means that automatically generates a travel plan based on the analysis results obtained by the analysis means and the emotion engine,

[1537] A display means for displaying the travel plan generated by the plan generation means,

[1538] A booking method for making travel reservations based on the aforementioned travel plan,

[1539] A system that includes this.

[1540] (Claim 2)

[1541] The system according to claim 1, wherein the reservation means includes means for notifying the user of travel reservation information on the day of travel.

[1542] (Claim 3)

[1543] The system according to claim 1, wherein the analysis means analyzes the desired conditions input by the user using natural language processing technology.

[1544] (Claim 4)

[1545] The system according to claim 1, wherein the plan generation means includes means for collecting optimal travel data from a partner database.

[1546] (Claim 5)

[1547] The system according to claim 1, wherein the display means includes means for presenting the details of the generated travel plan via a user interface.

[1548] "Application example 2 when combining with an emotional engine"

[1549] (Claim 1)

[1550] A user interface for entering travel preferences,

[1551] An analysis means for analyzing travel preferences and related emotional states obtained through the user interface,

[1552] A plan generation means that automatically generates a travel plan based on the analysis results and emotional state obtained by the aforementioned analysis means,

[1553] A display means for displaying the travel plan generated by the plan generation means,

[1554] A booking and payment method that allows for the booking and payment of travel in a single transaction based on the aforementioned travel plan,

[1555] A notification means for displaying payment information associated with the aforementioned travel plan on the user interface,

[1556] A system that includes this.

[1557] (Claim 2)

[1558] The system according to claim 1, wherein the reservation and payment means includes means for notifying the user of travel reservation information and payment information on the day of travel.

[1559] (Claim 3)

[1560] The system according to claim 1, wherein the analysis means analyzes the user's input desired conditions and emotional state using natural language processing technology. [Explanation of Symbols]

[1561] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A user interface for entering travel preferences, An analysis means for analyzing travel preferences obtained through the user interface, A plan generation means that automatically generates a travel plan based on the analysis results obtained by the aforementioned analysis means, A display means for displaying the travel plan generated by the plan generation means, A booking method for making travel reservations based on the aforementioned travel plan, A system that includes this.

2. The system according to claim 1, wherein the reservation means includes means for notifying the user of travel reservation information on the day of travel.

3. The system according to claim 1, wherein the analysis means analyzes the desired conditions input by the user using natural language processing technology.

Images