system

Abstract

We provide the system. [Solution] A means for receiving travel-related inquiries from users, A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent, Based on the user's intent, a means for obtaining information about travel destinations, accommodations, and activities from a database, A means for generating a response to be provided to the user based on the acquired information, Means for sending the generated response to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

【Patent Document 」 Japanese Patent Application Laid-Open No. 2022-180282

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern travel planning, there is a need for a system that can efficiently propose travel destinations, accommodation facilities, and activities according to the conditions desired by users. In conventional travel agencies and online reservation systems, there are problems that users have to search a lot of information by themselves, which takes time and effort to find an optimal travel plan. In addition, it is difficult to accurately grasp the intentions of users and make personalized proposals. The present invention aims to solve these problems and provide a more convenient and efficient travel planning support system for users.

Means for Solving the Problems

[0005] The present invention provides a system that includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information on travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, and means for transmitting the generated response to the user. As a result, users can receive travel suggestions that meet their desired conditions without having to perform complex search operations, enabling them to efficiently proceed with their travel planning.

[0006] A "user" refers to an individual or group that uses the travel planning support system to make inquiries or obtain information.

[0007] "Inquiry" refers to the act of a user entering questions or requests regarding travel into the system using natural language.

[0008] "Means of receiving" refers to the functions or methods by which the system receives inquiries from users.

[0009] "Means of analysis" refers to methods and techniques for understanding the content of inquiries received by a system and identifying the user's intent and requests.

[0010] "User intent" refers to the purpose, requests, and desired conditions that the user wants to communicate to the system through their inquiry.

[0011] "Means of acquisition" refers to the methods and techniques used to search for and retrieve necessary information from a database.

[0012] A "database" refers to an information aggregation system that stores information about travel destinations, accommodations, activities, and so on.

[0013] "Means for generating responses" refers to methods and technologies for creating replies to users based on acquired information.

[0014] "Means of transmission" refers to the methods and technologies used to send the generated response to the user's device.

[0015] A "system" refers to an integrated set of technical means, including receiving user inquiries, analyzing their content, retrieving information from databases, and generating and sending responses. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and 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 combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

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

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

[0021] In the following embodiments, a labeled 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.

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention provides a system that enables users to efficiently plan their trips. Specifically, it aims to build a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This invention will be convenient for many users and support efficient travel planning.

[0038] System Configuration

[0039] This system consists of the following main components:

[0040] 1. User terminal

[0041] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0042] The user terminal has the function to send the inquiry details to the server.

[0043] 2. Server

[0044] The server plays a central role in receiving user inquiries and analyzing their content.

[0045] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0046] The server retrieves the appropriate information from the database based on the user's intent.

[0047] The server generates a response to provide to the user based on the information it has obtained.

[0048] The server sends the generated response to the user's terminal.

[0049] 3. Database

[0050] The database stores detailed information about travel destinations, accommodations, and activities.

[0051] The server queries the database to retrieve the necessary information.

[0052] System operation

[0053] Examples of user inquiries

[0054] The user enters the question, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0055] Server Processing

[0056] Reception: The server receives a query from the user's terminal.

[0057] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent. In this case, the analysis is based on the keyword "weekend trip with close friends."

[0058] Information retrieval: The server queries the database to retrieve information on suitable destinations, accommodations, and activities for weekend getaways.

[0059] Response Generation: Based on the information the server has obtained, it generates a response to provide to the user. In this case, the response would be something like, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0060] Sending: The server sends the generated response to the user's terminal.

[0061] Display on the user's terminal

[0062] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0063] Specific examples

[0064] For example, if a user asks, "Are there any good places for a family summer vacation?", the server retrieves information on suitable summer vacation destinations for families from its database and generates a response such as, "Okinawa is recommended. It has beautiful beaches, family-friendly resort hotels, cultural experiences, Okinawan cuisine, and more," and sends it to the user's terminal.

[0065] The system of the present invention can efficiently perform these series of processes to propose the optimal travel plan for the user.

[0066] The following describes the processing flow.

[0067] Step 1:

[0068] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0069] Step 2:

[0070] The terminal receives the user's inquiry and forms an API request to send to the server.

[0071] Step 3:

[0072] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0073] Step 4:

[0074] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0075] Step 5:

[0076] The server analyzes the received query using natural language processing technology. Models such as ChatGPT (registered trademark) are used to identify the information and intent the user is seeking.

[0077] Step 6:

[0078] The server executes queries against the database based on the user's intent. For example, it might search for information on suitable travel destinations, accommodations, and activities for a weekend getaway.

[0079] Step 7:

[0080] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0081] Step 8:

[0082] The server generates a response to provide to the user based on information retrieved from the database. Using ChatGPT, it can create a response such as, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0083] Step 9:

[0084] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0085] Step 10:

[0086] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0087] Step 11:

[0088] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0089] (Example 1)

[0090] 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."

[0091] Traditional travel planning systems had the problem of not being able to quickly and accurately provide users with the information they needed. In particular, accurately interpreting inquiries, understanding the user's intentions, and suggesting appropriate destinations, accommodations, and activities was technically challenging.

[0092] 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.

[0093] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, and means for displaying it on the user's terminal. This makes it possible to accurately understand the user's intent and support travel planning quickly and effectively.

[0094] A "user terminal" refers to a device used by a user to access the system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0095] A "server" is a central processing unit that receives user inquiries, analyzes their content, retrieves and generates appropriate information, and sends it to the user's terminal.

[0096] "Means for receiving inquiries" refers to the function that allows the server to receive travel-related inquiries sent from user terminals.

[0097] "Means for identifying intent" refers to the functionality that allows a server to analyze a user's inquiry and understand their intent. These means include natural language processing techniques and generative AI models.

[0098] "Means of obtaining information" refers to the function that allows a server to retrieve information about travel destinations, accommodations, and activities from a database by executing queries based on the user's intentions.

[0099] "Means for generating a response" refers to the function that creates a response to provide to the user based on the information acquired by the server.

[0100] "Means for sending a response" refers to the function that sends the response generated by the server to the user's terminal.

[0101] "Display means" refers to a function that allows the user terminal to visually display the response received from the server to the user.

[0102] Modes for carrying out the invention

[0103] This invention provides a system that enables users to efficiently plan their trips. Specifically, it is a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This system consists of the following components.

[0104] User terminal

[0105] User terminals include devices such as smartphones, tablets, and personal computers, which users access the system to enter inquiries. The inquiries entered by the user are sent to the server in text format.

[0106] server

[0107] The server is the central device of this system. It receives inquiries from user terminals and analyzes their content. The server uses natural language processing (NLP) and generative AI models (e.g., GPT-3®) to analyze the inquiry content and identify the user's intent. Based on the analysis, the server queries the database and retrieves the appropriate information. Based on the retrieved information, the server generates a response to provide to the user and sends it to the user terminal.

[0108] database

[0109] The database stores detailed information about travel destinations, accommodations, and activities. The server queries the database to retrieve relevant information based on the user's intent. The database is optimized to provide relevant information in real time.

[0110] Explanation of specific examples

[0111] When a user asks, "I'm planning a weekend trip with close friends. Do you have any recommendations?", the server receives the inquiry. Using NLP (Neuro-Linguistic Programming) techniques, the server analyzes the keyword "weekend trip with close friends" to identify the user's intent. The server then queries its database to retrieve information on suitable destinations, accommodations, and activities for a weekend trip. Based on the retrieved information, the server generates a response such as, "Tokyo is a good choice. You can enjoy sightseeing and shopping, as well as delicious food. Hotel XX in Chuo Ward is particularly popular for accommodations," and sends it to the user's terminal. The user's terminal displays the received response, and the user can then proceed with their travel planning based on it.

[0112] Example of a prompt

[0113] Examples of prompt statements for generative AI models include the following:

[0114] "I want to create travel plans. Please design a system that suggests the best travel destinations, accommodations, and activities in response to user inquiries. For example, please explain in detail how the system would generate a response if a user inquired, 'Are there any good places for a family summer vacation?'"

[0115] In this way, this system combines natural language processing technology and generative AI models to accurately understand user inquiries and provide prompt and accurate support for travel planning.

[0116] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0117] Step 1: User Inquiry

[0118] The user enters a question about their travel plans into the terminal using natural language. For example, they might enter, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" This is the input information. When the user presses the submit button, the inquiry is sent to the server. The output is the text data of the inquiry.

[0119] Step 2: Server Reception

[0120] The server receives a query sent from the user's terminal. The input is text data sent from the user's terminal. The server receives the network request and extracts the text content. The output is the received query text data.

[0121] Step 3: Analyzing the inquiry content

[0122] The server analyzes the received text content using natural language processing techniques. A generative AI model (e.g., GPT-3) is used to identify the user's intent. The input is the query text data received by the server. The server extracts and analyzes important keywords (e.g., "close friends," "weekend trip"). The output is data identifying the user's intent as a result of the analysis.

[0123] Step 4: Retrieve information from the database

[0124] The server executes queries against the appropriate database based on the analysis results. For example, it retrieves information on suitable travel destinations, accommodations, and activities for a weekend getaway. The inputs are the analysis results data and the database query. The server generates an SQL query and executes it against the database. The output is the retrieved travel information data.

[0125] Step 5: Generating a response

[0126] The server generates a response to provide to the user based on the information it has acquired. Using a generative AI model, the response is created in a way that is easy for the user to understand and provides useful information. The input is the acquired travel information data. The server passes the data to the generative AI model and instructs it to create a response in natural language. The output is the generated response text.

[0127] Step 6: Sending a response

[0128] The server sends the generated response to the user's terminal. The input is the generated response text. The server creates and sends a network request to send the text response to the user's terminal. The output is the sent response data.

[0129] Step 7: Display on the user's terminal

[0130] The user's terminal receives the response sent from the server and displays it to the user. This allows the user to proceed with their travel plan based on the suggested information. The input is the response data sent from the server. The user's terminal processes the received request and displays the response text in the chat box. The output is the response information displayed to the user.

[0131] (Application Example 1)

[0132] 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."

[0133] Traditional travel planning systems required users to individually research destinations, accommodations, and activities, which was inefficient. Furthermore, adjusting routes and stops during travel was difficult. Therefore, there was a need for a system that could perform real-time travel planning and information gathering, especially while traveling in vehicles like autonomous vehicles.

[0134] 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.

[0135] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, activities, places to stop along the way, and optimal routes from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, and means for transmitting the generated response to the user. This makes it possible to efficiently and conveniently plan a trip even while traveling and to obtain necessary information in real time.

[0136] A "user" is an individual or group that uses the system to make travel-related inquiries.

[0137] An "inquiry" is the act of a user asking the system for information about their travel plans or destination.

[0138] "Intention" refers to the specific purpose or desire that the user expects from the system.

[0139] "Travel destination" refers to the place or region that the user plans to visit.

[0140] "Accommodation facilities" refer to places of lodging, such as hotels and inns, where users stay during their travels.

[0141] "Activities" refer to activities such as sightseeing, leisure, and dining that you plan to do at your travel destination.

[0142] "Places to stop by" refers to tourist spots or rest areas that users should visit along their journey.

[0143] An "optimal route" refers to the most efficient and comfortable path or route for traveling to one's destination.

[0144] A "database" is a source of information that stores information about travel destinations, accommodations, activities, and routes.

[0145] "Natural language processing" is a technology that enables computers to understand and analyze natural human language.

[0146] A "server" is a central computing system that analyzes user inquiries, generates responses, and provides them.

[0147] A "query" is a search request made to retrieve specific information from a database.

[0148] A "response" is the answer that a server generates in response to a user's inquiry.

[0149] The system for realizing this invention includes the following components.

[0150] 1. User terminal:

[0151] The user terminal operates on the infotainment system of the autonomous vehicle. It provides an interface where the user can make travel-related inquiries by voice. The terminal converts the voice to text and sends that text to the server.

[0152] 2. Server:

[0153] The server is the primary processing unit that receives and analyzes queries sent from user terminals and provides the necessary information. Specifically, it uses the following hardware and software:

[0154] Hardware: High-performance server computer

[0155] Software: Python, SQLite database, transformers library

[0156] The server uses natural language processing (NLP) techniques to analyze user inquiries and identify user intent. For this purpose, it uses the BERT model available from the transformers library. It then executes database queries to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes.

[0157] 3. Database:

[0158] The database stores detailed information about travel destinations, accommodations, activities, and routes. It uses an SQLite database and provides the necessary information in response to queries from the server.

[0159] As a concrete example, if a user asks via voice, "I'm planning a weekend trip with a close friend. Do you have any recommendations?", the system will operate as follows:

[0160] The user's device converts the audio to text and sends that text data to the server.

[0161] The server processes the received text data using a natural language processing model to analyze the user's intent. For example, it might identify "recommended travel destinations to visit with close friends on the weekend."

[0162] The server executes relevant queries against the SQLite database to retrieve appropriate travel destination information.

[0163] Based on the information it retrieves, the server generates a response saying, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, and there's plenty of delicious food."

[0164] The server sends the generated response to the user's terminal, and the user's terminal displays its contents to the user.

[0165] This system allows users to efficiently and conveniently plan their trips while on the go and obtain necessary information in real time. Possible prompts include phrases like, "I'd like to travel with friends this weekend; what are some recommended destinations?"

[0166] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0167] Step 1:

[0168] Users make travel-related inquiries by voice. Specifically, they use the infotainment system of an autonomous vehicle to voice prompts such as, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" The input is the user's voice.

[0169] Step 2:

[0170] The device receives voice input and converts it to text. Specifically, it uses its voice recognition system to analyze the voice data and generate text data. The output is the user's inquiry in text format.

[0171] Step 3:

[0172] The terminal sends text data to the server. Specifically, it uses its communication module to send text data to the server's API endpoint. The input is the user's query in text format, and the output is a notification to the server that the transmission is complete.

[0173] Step 4:

[0174] The server receives text data and analyzes it using a natural language processing (NLP) model. Specifically, it uses Python scripts and the transformers library on the server to identify the user's intent. For example, it might identify "recommended travel destinations to go to with close friends on the weekend." The input is the user's inquiry in text format, and the output is the analyzed user intent.

[0175] Step 5:

[0176] The server executes queries against the database based on the user's intent. Specifically, it executes SQL queries related to an SQLite database to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes. The input is the user's intent, and the output is the database search results.

[0177] Step 6:

[0178] The server generates a response to provide to the user based on the database search results. Specifically, it creates a response message based on the retrieved information, for example, "Tokyo is recommended. You can enjoy sightseeing and shopping, and there are many delicious restaurants." The input is the database search results, and the output is the generated response message.

[0179] Step 7:

[0180] The server sends the generated response message to the terminal. Specifically, it uses the server's communication module to send the response message to the terminal. The input is the generated response message, and the output is a notification to the terminal that the transmission is complete.

[0181] Step 8:

[0182] The terminal displays the response received from the server to the user. Specifically, it uses the terminal's display or speaker to present the response message to the user. The input is the response message from the server, and the output is the information presented to the user.

[0183] 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.

[0184] This invention provides a system that enables users to efficiently plan their trips. Specifically, it proposes a system that receives and analyzes travel-related inquiries from users to identify their intentions and provide appropriate information. Furthermore, by combining this with an emotion engine, it offers suggestions and responses based on the user's emotions. This system can provide users with a more personalized experience.

[0185] System Configuration

[0186] This system consists of the following main components:

[0187] 1. User terminal

[0188] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0189] The user terminal has the function to send the inquiry details to the server.

[0190] 2. Server

[0191] The server plays a central role in receiving user inquiries and analyzing their content.

[0192] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0193] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0194] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0195] The server generates a response to provide to the user based on the information it has obtained.

[0196] The server sends the generated response to the user's terminal.

[0197] 3. Database

[0198] The database stores detailed information about travel destinations, accommodations, and activities.

[0199] The server queries the database to retrieve the necessary information.

[0200] 4. Emotional Engine

[0201] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0202] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[0203] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[0204] System operation

[0205] Examples of user inquiries

[0206] The user enters an inquiry saying, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0207] Server Processing

[0208] Reception: The server receives a query from the user's terminal.

[0209] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent and emotions. In this case, the keyword "stressed" leads to the conclusion that the user is seeking relaxation.

[0210] Emotion Recognition: The emotion engine recognizes the user's emotion as "stress."

[0211] Information retrieval: The server queries the database to find information on relaxing travel destinations, accommodations, and activities.

[0212] Response Generation: Based on the information the server has acquired, it uses an emotion engine to generate a response to provide to the user. In this case, it would generate a response such as, "Okinawa resorts are highly recommended. They offer relaxing beachfront environments and excellent spas. There are many resort hotels that provide a relaxing atmosphere."

[0213] Sending: The server sends the generated response to the user's terminal.

[0214] Display on the user's terminal

[0215] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0216] Specific example

[0217] For example, if a user asks, "I'm tired and would like to take a vacation. Are there any places where I can relax?", the server will use an emotion engine to analyze the emotional keywords "relax" and "vacation" and suggest relaxing travel destinations. In this case, it would generate and provide a response such as, "I recommend a resort in Bali. It has beautiful beaches and abundant spa services, where you can refresh both your mind and body."

[0218] The system of the present invention can efficiently perform these processes to propose the optimal travel plan for the user. Furthermore, by combining it with an emotion engine, it is possible to provide personalized services that are attentive to the user's emotions.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[0222] Step 2:

[0223] The terminal receives the user's inquiry and forms an API request to send to the server.

[0224] Step 3:

[0225] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0226] Step 4:

[0227] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0228] Step 5:

[0229] The server analyzes the received inquiry using natural language processing technology to identify the user's intent. In this case, keywords such as "I'm stressed" and "a relaxing travel destination" are analyzed.

[0230] Step 6:

[0231] The server uses an emotion engine to recognize the user's emotions from the content of their inquiry. For example, it might recognize from the keyword "stress" that the user is seeking relaxation.

[0232] Step 7:

[0233] The server queries the database based on the user's intentions and emotions. For example, it might search for information on relaxing travel destinations, accommodations, and activities.

[0234] Step 8:

[0235] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0236] Step 9:

[0237] The server generates a response to provide to the user based on information retrieved from the database. An emotion engine is used to adjust the tone and content of the response. For example, it might create a response like, "I recommend Okinawa resorts. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0238] Step 10:

[0239] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0240] Step 11:

[0241] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0242] Step 12:

[0243] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0244] (Example 2)

[0245] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0246] Conventional travel planning support systems typically provide generic responses to user inquiries, rarely offering personalized suggestions tailored to the user's emotions or specific needs. This made it difficult for users to obtain information about travel destinations that suited their feelings and circumstances, often leading to stress. Furthermore, generating responses that consider user emotions requires advanced technology, which was challenging for conventional systems. Therefore, there is a need for a travel planning support system capable of providing information that resonates with the user's emotions.

[0247] 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.

[0248] In this invention, the server includes means for receiving travel-related inquiries from users; means for analyzing the content of the user's inquiry and identifying the user's intentions and emotions; means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intentions and emotions; means for generating a response to provide the user with the obtained information using an emotion engine; and means for sending the generated response to the user. This makes it possible to provide personalized travel information that is attentive to the user's emotions.

[0249] A "user" refers to an individual or legal entity that uses the system to make travel-related inquiries.

[0250] "Travel-related inquiries" refer to questions or requests from users seeking information about accommodations, destinations, activities, etc., through the system.

[0251] A "server" refers to a central computing resource that receives and analyzes user inquiries, retrieves necessary information, and generates and sends responses.

[0252] "Natural language processing" refers to the techniques used by computers to understand and analyze human language, and specifically includes processes such as text tokenization, semantic analysis, and tagging.

[0253] An "emotion engine" refers to a technology that analyzes the emotions behind a user's inquiry and generates an appropriate response based on that analysis.

[0254] A "database" refers to a collection of stored data that contains information about travel destinations, accommodations, and activities, which a server uses to query and retrieve that information.

[0255] A "query" refers to a statement of inquiry executed to retrieve specific information from a database.

[0256] "Response" refers to the information that a server generates and provides to a user in response to a user's inquiry.

[0257] "Personalized suggestions" refer to specific travel information and advice tailored to the individual needs and feelings of the user.

[0258] This invention is a system that enables users to efficiently plan their travels. Specifically, it receives and analyzes user inquiries to identify the user's intentions and emotions, and then provides appropriate information. By combining this system with an emotion engine, it can offer suggestions and responses based on the user's emotions, providing a more personalized experience.

[0259] System Configuration

[0260] This system consists of the following main components:

[0261] 1. User terminal

[0262] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0263] The user terminal has the function to send the inquiry details to the server.

[0264] 2. Server

[0265] The server plays a central role in receiving user inquiries and analyzing their content.

[0266] The server uses natural language processing techniques to analyze the query content and identify the user's intent and sentiment.

[0267] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0268] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0269] The server generates a response to provide to the user based on the information it has obtained.

[0270] The server sends the generated response to the user's terminal.

[0271] 3. Database

[0272] The database stores detailed information about travel destinations, accommodations, and activities.

[0273] The server queries the database to retrieve the necessary information.

[0274] 4. Emotional Engine

[0275] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0276] Based on the results analyzed by the server, human-like responses are generated using the user's emotional data.

[0277] The emotion engine adjusts the tone and expression of the response and makes optimal suggestions according to the user's emotions.

[0278] Technologies Used

[0279] Natural Language Processing Technology:

[0280] The server uses natural language processing technologies such as Google's (registered trademark) BERT and OpenAI's (registered trademark) GPT-4 (registered trademark) to analyze the content of the user's inquiry.

[0281] Database Technology:

[0282] <##**## The server uses database management systems such as MySQL (registered trademark) and MongoDB to store travel-related information and execute queries to obtain information.

[0283] Emotion Analysis Technology:

[0284] The server uses an emotion analysis engine from the Affective Computing Lab, etc., to analyze the user's emotions and generate responses based on them.

[0285] Specific Example

[0286] Example of Inquiry

[0287] User: "I've been stressed lately. Please tell me a travel destination where I can relax."

[0288] As the server's processing, the following steps are taken:

[0289] 1. The server receives an inquiry from the user terminal.

[0290] 2. The server uses an NLP model (e.g., BERT or GPT-4) to analyze the query.

[0291] 3. The server identifies the user's intentions and emotions from the analysis. For example, it can understand the user's intention to relax from the phrase "I'm stressed."

[0292] 4. The emotion engine recognizes the user's emotions as "stress."

[0293] 5. The server queries the database to retrieve information about suitable travel destinations.

[0294] 6. Based on the information it has acquired, the server uses an emotion engine to generate a response to provide to the user. For example, it might create a response such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0295] 7. The server sends the generated response to the user's terminal.

[0296] 8. The user terminal displays the received response to the user.

[0297] Example of a prompt

[0298] "I'm tired and would like to take a vacation. Are there any places where I can relax?"

[0299] "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0300] With the above configuration, it becomes possible to efficiently propose travel plans that are tailored to the user's emotions.

[0301] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0302] Step 1:

[0303] User: The user accesses the system using a terminal and enters an inquiry regarding travel. For example, enter a specific prompt sentence such as "I've been stressed lately. Please tell me a travel destination where I can relax."

[0304] Terminal: Transmits the entered inquiry to the server. At this time, the terminal generates an HTTP request and sends data including the inquiry content to the server. The input is the user's text message, and the output is an HTTP request addressed to the server.

[0305] Step 2:

[0306] Server: The server receives the HTTP request sent from the terminal. Converts the received data into an analyzable format (e.g., JSON) and passes it to the internal system. The input is the HTTP request from the terminal, and the output is analyzable data.

[0307] Step 3:

[0308] Server: The server analyzes the inquiry content using natural language processing (NLP) technology. Specifically, uses a generative AI model (e.g., BERT or GPT-4) to perform text tokenization, semantic analysis, and tagging. The input is the user's inquiry text, and the output is the analyzed text data.

[0309] Step 4:

[0310] Server: Based on the analysis result of the NLP model, the server identifies the user's intention and sentiment. Uses a sentiment engine to extract sentiments and intentions such as "stress" and "want to relax". The input is the analyzed text data, and the output is the user's intention and sentiment information.

[0311] Step 5:

[0312] Server: The server queries the database to retrieve information on relaxing travel destinations, accommodations, and activities. The database contains detailed information about travel destinations, accommodations, and activities. The input is user intent and sentiment information, and the output is the retrieved travel-related information.

[0313] Step 6:

[0314] Server: Based on the information it retrieves, the server uses an emotion engine to generate responses to provide to the user. Specifically, it might create responses such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and excellent spas." The input is information retrieved from the database, and the output is the generated response message.

[0315] Step 7:

[0316] Server: Sends the generated response message to the user's terminal as an HTTP response. The input is the generated response message, and the output is the HTTP response sent to the terminal.

[0317] Step 8:

[0318] Terminal: The user terminal receives HTTP responses from the server and displays them on the screen. The user can then proceed with their travel plan based on the displayed suggestions. Input is the HTTP response from the server, and output is the response message displayed to the user.

[0319] (Application Example 2)

[0320] 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 device 14 will be referred to as the "terminal."

[0321] Conventional travel planning systems can provide basic information in response to user inquiries, but they have difficulty providing personalized suggestions that reflect the user's emotions and specific intentions. Furthermore, in-store customer service has limited detailed information provision regarding travel, making it difficult to improve customer satisfaction. This invention aims to solve these problems and provide a system that offers optimal travel suggestions based on the user's emotions, thereby improving in-store service.

[0322] 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. In this invention, the server includes means for receiving travel inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information on travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, means including an emotion recognition engine that recognizes emotions and adjusts the tone and expression of the response based on those emotions, and means for being installed in a customer support robot at a physical store. This makes it possible to provide personalized travel suggestions that are attentive to the user's emotions, and is expected to improve services at physical stores.

[0323] A "user terminal" is a device used by a user to access the system and enter inquiries, and includes smartphones, tablet devices, personal computers, etc.

[0324] A "server" is a central system that receives user inquiries, analyzes their content, identifies the user's intent, and provides appropriate information using an emotion recognition engine.

[0325] "Natural language processing" is a technology that analyzes user inquiries and identifies the user's intent, involving the analysis and interpretation of meaning of text data.

[0326] A "database" is a storage device that stores detailed information about travel destinations, accommodations, and activities, and provides the necessary information in response to queries from a server.

[0327] An "emotion recognition engine" is a system that recognizes emotions from the content of a user's inquiry and adjusts the tone and expression of the response, providing the most suitable suggestions based on the user's emotions.

[0328] A "customer support robot" is a robot designed to handle customer interactions in physical stores and has functions such as suggesting travel plans and providing customer service.

[0329] This invention is a system to be installed in a customer support robot designed to improve customer service in physical stores. The system consists of a user terminal, a server, a database, an emotion recognition engine, and a customer support robot for use in physical stores.

[0330] First, the user terminal is a device that customers use to access the system and enter travel-related inquiries. The inquiries entered from the user terminal are sent to the server.

[0331] The server receives inquiries from user terminals, analyzes them using natural language processing, and identifies the user's intent. The analysis uses the natural language processing library "transformers." This technology allows for the specific identification of what the user is requesting.

[0332] Next, the server uses an emotion recognition engine to recognize the user's emotions from the content of their inquiry. Here, an emotion analysis model is used to understand the user's emotional state. This step enables the server to provide optimal suggestions tailored to the user's emotions.

[0333] Based on the analyzed intentions and emotions, the server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities. The database contains detailed information on domestic and international travel destinations.

[0334] Based on the information acquired by the server, a response is generated to be provided to the user. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response to achieve a human-like dialogue that is attentive to the user's emotions.

[0335] Finally, the generated response is delivered to the user via a user terminal or a customer support robot in a physical store. This customer support robot provides detailed travel suggestions and advanced service to customers in the store.

[0336] For example, if a user asks, "I've been feeling stressed lately, so could you recommend a relaxing travel destination?", the server analyzes the user's request using keywords like "relax" and "stress." The emotion recognition engine then recognizes the user's emotional state as "stressed" and generates a response such as, "I recommend a resort in Okinawa. It has a relaxing beach environment and plenty of spas," which is then provided to the user.

[0337] Other examples of prompt statements include the following:

[0338] "I'm thinking about a road trip, but what would you recommend as a destination?"

[0339] "What hotels would you recommend for business travel?"

[0340] "What activities can we enjoy on a family trip?"

[0341] This system will enable personalized travel suggestions based on user emotions, which is expected to improve in-store services.

[0342] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0343] Step 1:

[0344] The system receives inquiries from user devices. Users use smartphones, tablets, etc., to input travel-related questions and send them to the server. The input is the user's inquiry, and the output is the inquiry data received by the server.

[0345] Step 2:

[0346] The server analyzes the received query. It uses natural language processing techniques to analyze the query content and identify the user's intent. Specifically, it uses the natural language processing library "transformers" to analyze text data. The input is the received query data, and the output is the analyzed user intent data.

[0347] Step 3:

[0348] The server uses an emotion recognition engine to recognize the user's emotions. The query is input into an emotion analysis model to identify the user's emotional state. The input is the analyzed user intent data, and the output is the user's emotion data.

[0349] Step 4:

[0350] The server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities based on the user's intent and sentiment. It issues queries to the database and searches for the necessary information. The input is user intent data and sentiment data, and the output is the retrieved travel information.

[0351] Step 5:

[0352] The server generates a response to provide to the user based on the acquired information. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response. The input is the acquired travel information, and the output is response data that corresponds to the emotion.

[0353] Step 6:

[0354] The server sends the generated response data to the user terminal or a customer support robot in a physical store. The user terminal or robot displays this response and provides it to the user. The input is emotion-sensitive response data, and the output is the displayed response information.

[0355] Step 7: The user decides on an action based on the suggestions. The travel plan is advanced based on the information provided by the user terminal or customer support robot. The input is the displayed response information, and the output is the user's next action.

[0356] 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.

[0357] 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 (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.

[0358] 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.

[0359] [Second Embodiment]

[0360] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0361] 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.

[0362] 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).

[0363] 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.

[0364] 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.

[0365] 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).

[0366] 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.

[0367] 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.

[0368] 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.

[0369] 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.

[0370] 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.

[0371] 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".

[0372] This invention provides a system that enables users to efficiently plan their trips. Specifically, it aims to build a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This invention will be convenient for many users and support efficient travel planning.

[0373] System Configuration

[0374] This system consists of the following main components:

[0375] 1. User terminal

[0376] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0377] The user terminal has the function to send the inquiry details to the server.

[0378] 2. Server

[0379] The server plays a central role in receiving user inquiries and analyzing their content.

[0380] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0381] The server retrieves the appropriate information from the database based on the user's intent.

[0382] The server generates a response to provide to the user based on the information it has obtained.

[0383] The server sends the generated response to the user's terminal.

[0384] 3. Database

[0385] The database stores detailed information about travel destinations, accommodations, and activities.

[0386] The server queries the database to retrieve the necessary information.

[0387] System operation

[0388] Examples of user inquiries

[0389] The user enters the question, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0390] Server Processing

[0391] Reception: The server receives a query from the user's terminal.

[0392] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent. In this case, the analysis is based on the keyword "weekend trip with close friends."

[0393] Information retrieval: The server queries the database to retrieve information on suitable destinations, accommodations, and activities for weekend getaways.

[0394] Response Generation: Based on the information the server has obtained, it generates a response to provide to the user. In this case, the response would be something like, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0395] Sending: The server sends the generated response to the user's terminal.

[0396] Display on the user's terminal

[0397] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0398] Specific examples

[0399] For example, if a user asks, "Are there any good places for a family summer vacation?", the server retrieves information on suitable summer vacation destinations for families from its database and generates a response such as, "Okinawa is recommended. It has beautiful beaches, family-friendly resort hotels, cultural experiences, Okinawan cuisine, and more," and sends it to the user's terminal.

[0400] The system of the present invention can efficiently perform these series of processes to propose the optimal travel plan for the user.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0404] Step 2:

[0405] The terminal receives the user's inquiry and forms an API request to send to the server.

[0406] Step 3:

[0407] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0408] Step 4:

[0409] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0410] Step 5:

[0411] The server analyzes the received query content using natural language processing techniques. Models such as ChatGPT are used to identify the information and intent the user is seeking.

[0412] Step 6:

[0413] The server executes queries against the database based on the user's intent. For example, it might search for information on suitable travel destinations, accommodations, and activities for a weekend getaway.

[0414] Step 7:

[0415] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0416] Step 8:

[0417] The server generates a response to provide to the user based on information retrieved from the database. Using ChatGPT, it can create a response such as, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0418] Step 9:

[0419] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0420] Step 10:

[0421] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0422] Step 11:

[0423] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0424] (Example 1)

[0425] 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".

[0426] Traditional travel planning systems had the problem of not being able to quickly and accurately provide users with the information they needed. In particular, accurately interpreting inquiries, understanding the user's intentions, and suggesting appropriate destinations, accommodations, and activities was technically challenging.

[0427] 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.

[0428] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, and means for displaying it on the user's terminal. This makes it possible to accurately understand the user's intent and support travel planning quickly and effectively.

[0429] A "user terminal" refers to a device used by a user to access the system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0430] A "server" is a central processing unit that receives user inquiries, analyzes their content, retrieves and generates appropriate information, and sends it to the user's terminal.

[0431] "Means for receiving inquiries" refers to the function that allows the server to receive travel-related inquiries sent from user terminals.

[0432] "Means for identifying intent" refers to the functionality that allows a server to analyze a user's inquiry and understand their intent. These means include natural language processing techniques and generative AI models.

[0433] "Means of obtaining information" refers to the function that allows a server to retrieve information about travel destinations, accommodations, and activities from a database by executing queries based on the user's intentions.

[0434] "Means for generating a response" refers to the function that creates a response to provide to the user based on the information acquired by the server.

[0435] "Means for sending a response" refers to the function that sends the response generated by the server to the user's terminal.

[0436] "Display means" refers to a function that allows the user terminal to visually display the response received from the server to the user.

[0437] Modes for carrying out the invention

[0438] This invention provides a system that enables users to efficiently plan their trips. Specifically, it is a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This system consists of the following components.

[0439] User terminal

[0440] User terminals include devices such as smartphones, tablets, and personal computers, which users access the system to enter inquiries. The inquiries entered by the user are sent to the server in text format.

[0441] server

[0442] The server is the central device of this system. It receives inquiries from user terminals and analyzes their content. The server uses natural language processing (NLP) and generative AI models (e.g., GPT-3) to analyze the inquiries and identify the user's intent. Based on the analysis, the server queries the database and retrieves the appropriate information. Based on the retrieved information, the server generates a response to provide to the user and sends it to the user terminal.

[0443] database

[0444] The database stores detailed information about travel destinations, accommodations, and activities. The server queries the database to retrieve relevant information based on the user's intent. The database is optimized to provide relevant information in real time.

[0445] Explanation of specific examples

[0446] When a user asks, "I'm planning a weekend trip with close friends. Do you have any recommendations?", the server receives the inquiry. Using NLP (Neuro-Linguistic Programming) techniques, the server analyzes the keyword "weekend trip with close friends" to identify the user's intent. The server then queries its database to retrieve information on suitable destinations, accommodations, and activities for a weekend trip. Based on the retrieved information, the server generates a response such as, "Tokyo is a good choice. You can enjoy sightseeing and shopping, as well as delicious food. Hotel XX in Chuo Ward is particularly popular for accommodations," and sends it to the user's terminal. The user's terminal displays the received response, and the user can then proceed with their travel planning based on it.

[0447] Example of a prompt

[0448] Examples of prompt statements for generative AI models include the following:

[0449] "I want to create travel plans. Please design a system that suggests the best travel destinations, accommodations, and activities in response to user inquiries. For example, please explain in detail how the system would generate a response if a user inquired, 'Are there any good places for a family summer vacation?'"

[0450] In this way, this system combines natural language processing technology and generative AI models to accurately understand user inquiries and provide prompt and accurate support for travel planning.

[0451] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0452] Step 1: User Inquiry

[0453] The user enters a question about their travel plans into the terminal using natural language. For example, they might enter, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" This is the input information. When the user presses the submit button, the inquiry is sent to the server. The output is the text data of the inquiry.

[0454] Step 2: Server Reception

[0455] The server receives a query sent from the user's terminal. The input is text data sent from the user's terminal. The server receives the network request and extracts the text content. The output is the received query text data.

[0456] Step 3: Analyzing the inquiry content

[0457] The server analyzes the received text content using natural language processing techniques. A generative AI model (e.g., GPT-3) is used to identify the user's intent. The input is the query text data received by the server. The server extracts and analyzes important keywords (e.g., "close friends," "weekend trip"). The output is data identifying the user's intent as a result of the analysis.

[0458] Step 4: Retrieve information from the database

[0459] The server executes queries against the appropriate database based on the analysis results. For example, it retrieves information on suitable travel destinations, accommodations, and activities for a weekend getaway. The inputs are the analysis results data and the database query. The server generates an SQL query and executes it against the database. The output is the retrieved travel information data.

[0460] Step 5: Generating a response

[0461] The server generates a response to provide to the user based on the information it has acquired. Using a generative AI model, the response is created in a way that is easy for the user to understand and provides useful information. The input is the acquired travel information data. The server passes the data to the generative AI model and instructs it to create a response in natural language. The output is the generated response text.

[0462] Step 6: Sending a response

[0463] The server sends the generated response to the user's terminal. The input is the generated response text. The server creates and sends a network request to send the text response to the user's terminal. The output is the sent response data.

[0464] Step 7: Display on the user's terminal

[0465] The user's terminal receives the response sent from the server and displays it to the user. This allows the user to proceed with their travel plan based on the suggested information. The input is the response data sent from the server. The user's terminal processes the received request and displays the response text in the chat box. The output is the response information displayed to the user.

[0466] (Application Example 1)

[0467] 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."

[0468] Traditional travel planning systems required users to individually research destinations, accommodations, and activities, which was inefficient. Furthermore, adjusting routes and stops during travel was difficult. Therefore, there was a need for a system that could perform real-time travel planning and information gathering, especially while traveling in vehicles like autonomous vehicles.

[0469] 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.

[0470] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, activities, places to stop along the way, and optimal routes from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, and means for transmitting the generated response to the user. This makes it possible to efficiently and conveniently plan a trip even while traveling and to obtain necessary information in real time.

[0471] A "user" is an individual or group that uses the system to make travel-related inquiries.

[0472] An "inquiry" is the act of a user asking the system for information about their travel plans or destination.

[0473] "Intention" refers to the specific purpose or desire that the user expects from the system.

[0474] "Travel destination" refers to the place or region that the user plans to visit.

[0475] "Accommodation facilities" refer to places of lodging, such as hotels and inns, where users stay during their travels.

[0476] "Activities" refer to activities such as sightseeing, leisure, and dining that you plan to do at your travel destination.

[0477] "Places to stop by" refers to tourist spots or rest areas that users should visit along their journey.

[0478] The "optimal route" refers to the path or route that allows for efficient and comfortable travel to a destination.

[0479] A "database" is a source of information that stores information about travel destinations, accommodations, activities, and routes.

[0480] "Natural language processing" is a technology that enables computers to understand and analyze natural human language.

[0481] A "server" is a central computing system that analyzes user inquiries, generates responses, and provides them.

[0482] A "query" is a search request made to retrieve specific information from a database.

[0483] A "response" is the answer that a server generates in response to a user's inquiry.

[0484] The system for realizing this invention includes the following components.

[0485] 1. User terminal:

[0486] The user terminal operates on the infotainment system of the autonomous vehicle. It provides an interface where the user can make travel-related inquiries by voice. The terminal converts the voice to text and sends that text to the server.

[0487] 2. Server:

[0488] The server is the primary processing unit that receives and analyzes queries sent from user terminals and provides the necessary information. Specifically, it uses the following hardware and software:

[0489] Hardware: High-performance server computer

[0490] Software: Python, SQLite database, transformers library

[0491] The server uses natural language processing (NLP) techniques to analyze user inquiries and identify user intent. For this purpose, it uses the BERT model available from the transformers library. It then executes database queries to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes.

[0492] 3. Database:

[0493] The database stores detailed information about travel destinations, accommodations, activities, and routes. It uses an SQLite database and provides the necessary information in response to queries from the server.

[0494] As a concrete example, if a user asks via voice, "I'm planning a weekend trip with a close friend. Do you have any recommendations?", the system will operate as follows:

[0495] The user's device converts the audio to text and sends that text data to the server.

[0496] The server processes the received text data using a natural language processing model to analyze the user's intent. For example, it might identify "recommended travel destinations to visit with close friends on the weekend."

[0497] The server executes relevant queries against the SQLite database to retrieve appropriate travel destination information.

[0498] Based on the information it retrieves, the server generates a response saying, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, and there's plenty of delicious food."

[0499] The server sends the generated response to the user's terminal, and the user's terminal displays its contents to the user.

[0500] This system allows users to efficiently and conveniently plan their trips while on the go and obtain necessary information in real time. Possible prompts include phrases like, "I'd like to travel with friends this weekend; what are some recommended destinations?"

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

[0502] Step 1:

[0503] Users make travel-related inquiries by voice. Specifically, they use the infotainment system of an autonomous vehicle to voice prompts such as, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" The input is the user's voice.

[0504] Step 2:

[0505] The device receives voice input and converts it to text. Specifically, it uses its voice recognition system to analyze the voice data and generate text data. The output is the user's inquiry in text format.

[0506] Step 3:

[0507] The terminal sends text data to the server. Specifically, it uses its communication module to send text data to the server's API endpoint. The input is the user's query in text format, and the output is a notification to the server that the transmission is complete.

[0508] Step 4:

[0509] The server receives text data and analyzes it using a natural language processing (NLP) model. Specifically, it uses Python scripts and the transformers library on the server to identify the user's intent. For example, it might identify "recommended travel destinations to go to with close friends on the weekend." The input is the user's inquiry in text format, and the output is the analyzed user intent.

[0510] Step 5:

[0511] The server executes queries against the database based on the user's intent. Specifically, it executes SQL queries related to an SQLite database to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes. The input is the user's intent, and the output is the database search results.

[0512] Step 6:

[0513] The server generates a response to provide to the user based on the database search results. Specifically, it creates a response message based on the retrieved information, for example, "Tokyo is recommended. You can enjoy sightseeing and shopping, and there are many delicious restaurants." The input is the database search results, and the output is the generated response message.

[0514] Step 7:

[0515] The server sends the generated response message to the terminal. Specifically, it uses the server's communication module to send the response message to the terminal. The input is the generated response message, and the output is a notification to the terminal that the transmission is complete.

[0516] Step 8:

[0517] The terminal displays the response received from the server to the user. Specifically, it uses the terminal's display or speaker to present the response message to the user. The input is the response message from the server, and the output is the information presented to the user.

[0518] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0519] This invention provides a system that enables users to efficiently plan their trips. Specifically, it proposes a system that receives and analyzes travel-related inquiries from users to identify their intentions and provide appropriate information. Furthermore, by combining this with an emotion engine, it offers suggestions and responses based on the user's emotions. This system can provide users with a more personalized experience.

[0520] System Configuration

[0521] This system consists of the following main components:

[0522] 1. User terminal

[0523] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0524] The user terminal has the function to send the inquiry details to the server.

[0525] 2. Server

[0526] The server plays a central role in receiving user inquiries and analyzing their content.

[0527] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0528] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0529] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0530] The server generates a response to provide to the user based on the information it has obtained.

[0531] The server sends the generated response to the user's terminal.

[0532] 3. Database

[0533] The database stores detailed information about travel destinations, accommodations, and activities.

[0534] The server queries the database to retrieve the necessary information.

[0535] 4. Emotional Engine

[0536] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0537] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[0538] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[0539] System operation

[0540] Examples of user inquiries

[0541] The user enters an inquiry saying, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0542] Server Processing

[0543] Reception: The server receives a query from the user's terminal.

[0544] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent and emotions. In this case, the keyword "stressed" leads to the conclusion that the user is seeking relaxation.

[0545] Emotion Recognition: The emotion engine recognizes the user's emotion as "stress."

[0546] Information retrieval: The server queries the database to find information on relaxing travel destinations, accommodations, and activities.

[0547] Response Generation: Based on the information the server has acquired, it uses an emotion engine to generate a response to provide to the user. In this case, it would generate a response such as, "Okinawa resorts are highly recommended. They offer relaxing beachfront environments and excellent spas. There are many resort hotels that provide a relaxing atmosphere."

[0548] Sending: The server sends the generated response to the user's terminal.

[0549] Display on the user's terminal

[0550] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0551] Specific example

[0552] For example, if a user asks, "I'm tired and would like to take a vacation. Are there any places where I can relax?", the server will use an emotion engine to analyze the emotional keywords "relax" and "vacation" and suggest relaxing travel destinations. In this case, it would generate and provide a response such as, "I recommend a resort in Bali. It has beautiful beaches and abundant spa services, where you can refresh both your mind and body."

[0553] The system of the present invention can efficiently perform these processes to propose the optimal travel plan for the user. Furthermore, by combining it with an emotion engine, it is possible to provide personalized services that are attentive to the user's emotions.

[0554] The following describes the processing flow.

[0555] Step 1:

[0556] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[0557] Step 2:

[0558] The terminal receives the user's inquiry and forms an API request to send to the server.

[0559] Step 3:

[0560] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0561] Step 4:

[0562] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0563] Step 5:

[0564] The server analyzes the received inquiry using natural language processing technology to identify the user's intent. In this case, keywords such as "I'm stressed" and "a relaxing travel destination" are analyzed.

[0565] Step 6:

[0566] The server uses an emotion engine to recognize the user's emotions from the content of their inquiry. For example, it might recognize from the keyword "stress" that the user is seeking relaxation.

[0567] Step 7:

[0568] The server queries the database based on the user's intentions and emotions. For example, it might search for information on relaxing travel destinations, accommodations, and activities.

[0569] Step 8:

[0570] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0571] Step 9:

[0572] The server generates a response to provide to the user based on information retrieved from the database. An emotion engine is used to adjust the tone and content of the response. For example, it might create a response like, "I recommend Okinawa resorts. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0573] Step 10:

[0574] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0575] Step 11:

[0576] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0577] Step 12:

[0578] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0579] (Example 2)

[0580] 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".

[0581] Conventional travel planning support systems typically provide generic responses to user inquiries, rarely offering personalized suggestions tailored to the user's emotions or specific needs. This made it difficult for users to obtain information about travel destinations that suited their feelings and circumstances, often leading to stress. Furthermore, generating responses that consider user emotions requires advanced technology, which was challenging for conventional systems. Therefore, there is a need for a travel planning support system capable of providing information that resonates with the user's emotions.

[0582] 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.

[0583] In this invention, the server includes means for receiving travel-related inquiries from users; means for analyzing the content of the user's inquiry and identifying the user's intentions and emotions; means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intentions and emotions; means for generating a response to provide the user with the obtained information using an emotion engine; and means for sending the generated response to the user. This makes it possible to provide personalized travel information that is attentive to the user's emotions.

[0584] A "user" refers to an individual or legal entity that uses the system to make travel-related inquiries.

[0585] "Travel-related inquiries" refer to questions or requests from users seeking information about accommodations, destinations, activities, etc., through the system.

[0586] A "server" refers to a central computing resource that receives and analyzes user inquiries, retrieves necessary information, and generates and sends responses.

[0587] "Natural language processing" refers to the techniques used by computers to understand and analyze human language, and specifically includes processes such as text tokenization, semantic analysis, and tagging.

[0588] An "emotion engine" refers to a technology that analyzes the emotions behind a user's inquiry and generates an appropriate response based on that analysis.

[0589] A "database" refers to a collection of stored data that contains information about travel destinations, accommodations, and activities, which a server uses to query and retrieve that information.

[0590] A "query" refers to a statement of inquiry executed to retrieve specific information from a database.

[0591] "Response" refers to the information that a server generates and provides to a user in response to a user's inquiry.

[0592] "Personalized suggestions" refer to specific travel information and advice tailored to the individual needs and feelings of the user.

[0593] This invention is a system that enables users to efficiently plan their travels. Specifically, it receives and analyzes user inquiries to identify the user's intentions and emotions, and then provides appropriate information. By combining this system with an emotion engine, it can offer suggestions and responses based on the user's emotions, providing a more personalized experience.

[0594] System Configuration

[0595] This system consists of the following main components:

[0596] 1. User terminal

[0597] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0598] The user terminal has the function to send the inquiry details to the server.

[0599] 2. Server

[0600] The server plays a central role in receiving user inquiries and analyzing their content.

[0601] The server uses natural language processing techniques to analyze the query content and identify the user's intent and sentiment.

[0602] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0603] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0604] The server generates a response to provide to the user based on the information it has obtained.

[0605] The server sends the generated response to the user's terminal.

[0606] 3. Database

[0607] The database stores detailed information about travel destinations, accommodations, and activities.

[0608] The server queries the database to retrieve the necessary information.

[0609] 4. Emotional Engine

[0610] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0611] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[0612] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[0613] The technologies used

[0614] Natural language processing technology:

[0615] The server uses natural language processing technologies such as Google's BERT and OpenAI's GPT-4 to analyze user inquiries.

[0616] Database technology:

[0617] The server uses database management systems such as MySQL and MongoDB to store travel-related information and retrieve it by executing queries.

[0618] Emotion analysis technology:

[0619] The server uses Affective Computing Lab's emotion analysis engine and other tools to analyze the user's emotions and generate responses based on that analysis.

[0620] Specific example

[0621] Examples of inquiries

[0622] User: "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[0623] The server will perform the following steps:

[0624] 1. The server receives a query from the user's terminal.

[0625] 2. The server uses an NLP model (e.g., BERT or GPT-4) to analyze the query.

[0626] 3. The server identifies the user's intentions and emotions from the analysis. For example, it can understand the user's intention to relax from the phrase "I'm stressed."

[0627] 4. The emotion engine recognizes the user's emotions as "stress."

[0628] 5. The server queries the database to retrieve information about suitable travel destinations.

[0629] 6. Based on the information it has acquired, the server uses an emotion engine to generate a response to provide to the user. For example, it might create a response such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0630] 7. The server sends the generated response to the user's terminal.

[0631] 8. The user terminal displays the received response to the user.

[0632] Example of a prompt

[0633] "I'm tired and would like to take a vacation. Are there any places where I can relax?"

[0634] "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0635] With the above configuration, it becomes possible to efficiently propose travel plans that are tailored to the user's emotions.

[0636] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0637] Step 1:

[0638] User: The user accesses the system using a terminal and enters travel-related inquiries. For example, they might enter a specific prompt such as, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0639] Terminal: Sends the entered query to the server. At this time, the terminal generates an HTTP request and sends data containing the query content to the server. The input is the user's text message, and the output is an HTTP request addressed to the server.

[0640] Step 2:

[0641] Server: The server receives HTTP requests sent from terminals. It converts the received data into a parseable format (e.g., JSON) and passes it to its internal system. The input is an HTTP request from a terminal, and the output is parseable data.

[0642] Step 3:

[0643] Server: The server uses natural language processing (NLP) techniques to analyze the query content. Specifically, it uses generative AI models (e.g., BERT or GPT-4) to tokenize, semantically analyze, and tag the text. The input is the user's query text, and the output is the analyzed text data.

[0644] Step 4:

[0645] Server: The server identifies the user's intentions and emotions based on the analysis results of the NLP model. It uses an emotion engine to extract emotions and intentions such as "stress" and "want to relax." The input is the analyzed text data, and the output is user intention and emotion information.

[0646] Step 5:

[0647] Server: The server queries the database to retrieve information on relaxing travel destinations, accommodations, and activities. The database contains detailed information about travel destinations, accommodations, and activities. The input is user intent and sentiment information, and the output is the retrieved travel-related information.

[0648] Step 6:

[0649] Server: Based on the information it retrieves, the server uses an emotion engine to generate responses to provide to the user. Specifically, it might create responses such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and excellent spas." The input is information retrieved from the database, and the output is the generated response message.

[0650] Step 7:

[0651] Server: Sends the generated response message to the user's terminal as an HTTP response. The input is the generated response message, and the output is the HTTP response sent to the terminal.

[0652] Step 8:

[0653] Terminal: The user terminal receives HTTP responses from the server and displays them on the screen. The user can then proceed with their travel plan based on the displayed suggestions. Input is the HTTP response from the server, and output is the response message displayed to the user.

[0654] (Application Example 2)

[0655] 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."

[0656] Conventional travel planning systems can provide basic information in response to user inquiries, but they have difficulty providing personalized suggestions that reflect the user's emotions and specific intentions. Furthermore, in-store customer service has limited detailed information provision regarding travel, making it difficult to improve customer satisfaction. This invention aims to solve these problems and provide a system that offers optimal travel suggestions based on the user's emotions, thereby improving in-store service.

[0657] 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. In this invention, the server includes means for receiving travel inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information on travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, means including an emotion recognition engine that recognizes emotions and adjusts the tone and expression of the response based on those emotions, and means for being installed in a customer support robot at a physical store. This makes it possible to provide personalized travel suggestions that are attentive to the user's emotions, and is expected to improve services at physical stores.

[0658] A "user terminal" is a device used by a user to access the system and enter inquiries, and includes smartphones, tablet devices, personal computers, etc.

[0659] A "server" is a central system that receives user inquiries, analyzes their content, identifies the user's intent, and provides appropriate information using an emotion recognition engine.

[0660] "Natural language processing" is a technology that analyzes user inquiries and identifies the user's intent, involving the analysis and interpretation of meaning of text data.

[0661] A "database" is a storage device that stores detailed information about travel destinations, accommodations, and activities, and provides the necessary information in response to queries from a server.

[0662] An "emotion recognition engine" is a system that recognizes emotions from the content of a user's inquiry and adjusts the tone and expression of the response, providing the most suitable suggestions based on the user's emotions.

[0663] A "customer support robot" is a robot designed to handle customer interactions in physical stores and has functions such as suggesting travel plans and providing customer service.

[0664] This invention is a system to be installed in a customer support robot designed to improve customer service in physical stores. The system consists of a user terminal, a server, a database, an emotion recognition engine, and a customer support robot for use in physical stores.

[0665] First, the user terminal is a device that customers use to access the system and enter travel-related inquiries. The inquiries entered from the user terminal are sent to the server.

[0666] The server receives inquiries from user terminals, analyzes them using natural language processing, and identifies the user's intent. The analysis uses the natural language processing library "transformers." This technology allows for the specific identification of what the user is requesting.

[0667] Next, the server uses an emotion recognition engine to recognize the user's emotions from the content of their inquiry. Here, an emotion analysis model is used to understand the user's emotional state. This step enables the server to provide optimal suggestions tailored to the user's emotions.

[0668] Based on the analyzed intentions and emotions, the server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities. The database contains detailed information on domestic and international travel destinations.

[0669] Based on the information acquired by the server, a response is generated to be provided to the user. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response to achieve a human-like dialogue that is attentive to the user's emotions.

[0670] Finally, the generated response is delivered to the user via a user terminal or a customer support robot in a physical store. This customer support robot provides detailed travel suggestions and advanced service to customers in the store.

[0671] For example, if a user asks, "I've been feeling stressed lately, so could you recommend a relaxing travel destination?", the server analyzes the user's request using keywords like "relax" and "stress." The emotion recognition engine then recognizes the user's emotional state as "stressed" and generates a response such as, "I recommend a resort in Okinawa. It has a relaxing beach environment and plenty of spas," which is then provided to the user.

[0672] Other examples of prompt statements include the following:

[0673] "I'm thinking about a road trip, but what would you recommend as a destination?"

[0674] "What hotels would you recommend for business travel?"

[0675] "What activities can we enjoy on a family trip?"

[0676] This system will enable personalized travel suggestions based on user emotions, which is expected to improve in-store services.

[0677] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0678] Step 1:

[0679] The system receives inquiries from user devices. Users use smartphones, tablets, etc., to input travel-related questions and send them to the server. The input is the user's inquiry, and the output is the inquiry data received by the server.

[0680] Step 2:

[0681] The server analyzes the received query. It uses natural language processing techniques to analyze the query content and identify the user's intent. Specifically, it uses the natural language processing library "transformers" to analyze text data. The input is the received query data, and the output is the analyzed user intent data.

[0682] Step 3:

[0683] The server uses an emotion recognition engine to recognize the user's emotions. The query is input into an emotion analysis model to identify the user's emotional state. The input is the analyzed user intent data, and the output is the user's emotion data.

[0684] Step 4:

[0685] The server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities based on the user's intent and sentiment. It issues queries to the database and searches for the necessary information. The input is user intent data and sentiment data, and the output is the retrieved travel information.

[0686] Step 5:

[0687] The server generates a response to provide to the user based on the acquired information. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response. The input is the acquired travel information, and the output is response data that corresponds to the emotion.

[0688] Step 6:

[0689] The server sends the generated response data to the user terminal or a customer support robot in a physical store. The user terminal or robot displays this response and provides it to the user. The input is emotion-sensitive response data, and the output is the displayed response information.

[0690] Step 7: The user decides on an action based on the suggestions. The travel plan is advanced based on the information provided by the user terminal or customer support robot. The input is the displayed response information, and the output is the user's next action.

[0691] 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.

[0692] 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.

[0693] 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.

[0694] [Third Embodiment]

[0695] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0696] 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.

[0697] 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).

[0698] 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.

[0699] 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.

[0700] 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).

[0701] 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.

[0702] 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.

[0703] 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.

[0704] 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.

[0705] 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.

[0706] 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".

[0707] This invention provides a system that enables users to efficiently plan their trips. Specifically, it aims to build a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This invention will be convenient for many users and support efficient travel planning.

[0708] System Configuration

[0709] This system consists of the following main components:

[0710] 1. User terminal

[0711] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0712] The user terminal has the function to send the inquiry details to the server.

[0713] 2. Server

[0714] The server plays a central role in receiving user inquiries and analyzing their content.

[0715] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0716] The server retrieves the appropriate information from the database based on the user's intent.

[0717] The server generates a response to provide to the user based on the information it has obtained.

[0718] The server sends the generated response to the user's terminal.

[0719] 3. Database

[0720] The database stores detailed information about travel destinations, accommodations, and activities.

[0721] The server queries the database to retrieve the necessary information.

[0722] System operation

[0723] Examples of user inquiries

[0724] The user enters the question, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0725] Server Processing

[0726] Reception: The server receives a query from the user's terminal.

[0727] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent. In this case, the analysis is based on the keyword "weekend trip with close friends."

[0728] Information retrieval: The server queries the database to retrieve information on suitable destinations, accommodations, and activities for weekend getaways.

[0729] Response Generation: Based on the information the server has obtained, it generates a response to provide to the user. In this case, the response would be something like, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0730] Sending: The server sends the generated response to the user's terminal.

[0731] Display on the user's terminal

[0732] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0733] Specific examples

[0734] For example, if a user asks, "Are there any good places for a family summer vacation?", the server retrieves information on suitable summer vacation destinations for families from its database and generates a response such as, "Okinawa is recommended. It has beautiful beaches, family-friendly resort hotels, cultural experiences, Okinawan cuisine, and more," and sends it to the user's terminal.

[0735] The system of the present invention can efficiently perform these series of processes to propose the optimal travel plan for the user.

[0736] The following describes the processing flow.

[0737] Step 1:

[0738] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[0739] Step 2:

[0740] The terminal receives the user's inquiry and forms an API request to send to the server.

[0741] Step 3:

[0742] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0743] Step 4:

[0744] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0745] Step 5:

[0746] The server analyzes the received query content using natural language processing techniques. Models such as ChatGPT are used to identify the information and intent the user is seeking.

[0747] Step 6:

[0748] The server executes queries against the database based on the user's intent. For example, it might search for information on suitable travel destinations, accommodations, and activities for a weekend getaway.

[0749] Step 7:

[0750] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0751] Step 8:

[0752] The server generates a response to provide to the user based on information retrieved from the database. Using ChatGPT, it can create a response such as, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[0753] Step 9:

[0754] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0755] Step 10:

[0756] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0757] Step 11:

[0758] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0759] (Example 1)

[0760] 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."

[0761] Traditional travel planning systems had the problem of not being able to quickly and accurately provide users with the information they needed. In particular, accurately interpreting inquiries, understanding the user's intentions, and suggesting appropriate destinations, accommodations, and activities was technically challenging.

[0762] 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.

[0763] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, and means for displaying it on the user's terminal. This makes it possible to accurately understand the user's intent and support travel planning quickly and effectively.

[0764] A "user terminal" refers to a device used by a user to access the system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0765] A "server" is a central processing unit that receives user inquiries, analyzes their content, retrieves and generates appropriate information, and sends it to the user's terminal.

[0766] "Means for receiving inquiries" refers to the function that allows the server to receive travel-related inquiries sent from user terminals.

[0767] "Means for identifying intent" refers to the functionality that allows a server to analyze a user's inquiry and understand their intent. These means include natural language processing techniques and generative AI models.

[0768] "Means of obtaining information" refers to the function that allows a server to retrieve information about travel destinations, accommodations, and activities from a database by executing queries based on the user's intentions.

[0769] "Means for generating a response" refers to the function that creates a response to provide to the user based on the information acquired by the server.

[0770] "Means for sending a response" refers to the function that sends the response generated by the server to the user's terminal.

[0771] "Display means" refers to a function that allows the user terminal to visually display the response received from the server to the user.

[0772] Modes for carrying out the invention

[0773] This invention provides a system that enables users to efficiently plan their trips. Specifically, it is a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This system consists of the following components.

[0774] User terminal

[0775] User terminals include devices such as smartphones, tablets, and personal computers, which users access the system to enter inquiries. The inquiries entered by the user are sent to the server in text format.

[0776] server

[0777] The server is the central device of this system. It receives inquiries from user terminals and analyzes their content. The server uses natural language processing (NLP) and generative AI models (e.g., GPT-3) to analyze the inquiries and identify the user's intent. Based on the analysis, the server queries the database and retrieves the appropriate information. Based on the retrieved information, the server generates a response to provide to the user and sends it to the user terminal.

[0778] database

[0779] The database stores detailed information about travel destinations, accommodations, and activities. The server queries the database to retrieve relevant information based on the user's intent. The database is optimized to provide relevant information in real time.

[0780] Explanation of specific examples

[0781] When a user asks, "I'm planning a weekend trip with close friends. Do you have any recommendations?", the server receives the inquiry. Using NLP (Neuro-Linguistic Programming) techniques, the server analyzes the keyword "weekend trip with close friends" to identify the user's intent. The server then queries its database to retrieve information on suitable destinations, accommodations, and activities for a weekend trip. Based on the retrieved information, the server generates a response such as, "Tokyo is a good choice. You can enjoy sightseeing and shopping, as well as delicious food. Hotel XX in Chuo Ward is particularly popular for accommodations," and sends it to the user's terminal. The user's terminal displays the received response, and the user can then proceed with their travel planning based on it.

[0782] Example of a prompt

[0783] Examples of prompt statements for generative AI models include the following:

[0784] "I want to create travel plans. Please design a system that suggests the best travel destinations, accommodations, and activities in response to user inquiries. For example, please explain in detail how the system would generate a response if a user inquired, 'Are there any good places for a family summer vacation?'"

[0785] In this way, this system combines natural language processing technology and generative AI models to accurately understand user inquiries and provide prompt and accurate support for travel planning.

[0786] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0787] Step 1: User Inquiry

[0788] The user enters a question about their travel plans into the terminal using natural language. For example, they might enter, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" This is the input information. When the user presses the submit button, the inquiry is sent to the server. The output is the text data of the inquiry.

[0789] Step 2: Server Reception

[0790] The server receives a query sent from the user's terminal. The input is text data sent from the user's terminal. The server receives the network request and extracts the text content. The output is the received query text data.

[0791] Step 3: Analyzing the inquiry content

[0792] The server analyzes the received text content using natural language processing techniques. A generative AI model (e.g., GPT-3) is used to identify the user's intent. The input is the query text data received by the server. The server extracts and analyzes important keywords (e.g., "close friends," "weekend trip"). The output is data identifying the user's intent as a result of the analysis.

[0793] Step 4: Retrieve information from the database

[0794] The server executes queries against the appropriate database based on the analysis results. For example, it retrieves information on suitable travel destinations, accommodations, and activities for a weekend getaway. The inputs are the analysis results data and the database query. The server generates an SQL query and executes it against the database. The output is the retrieved travel information data.

[0795] Step 5: Generating a response

[0796] The server generates a response to provide to the user based on the information it has acquired. Using a generative AI model, the response is created in a way that is easy for the user to understand and provides useful information. The input is the acquired travel information data. The server passes the data to the generative AI model and instructs it to create a response in natural language. The output is the generated response text.

[0797] Step 6: Sending a response

[0798] The server sends the generated response to the user's terminal. The input is the generated response text. The server creates and sends a network request to send the text response to the user's terminal. The output is the sent response data.

[0799] Step 7: Display on the user's terminal

[0800] The user's terminal receives the response sent from the server and displays it to the user. This allows the user to proceed with their travel plan based on the suggested information. The input is the response data sent from the server. The user's terminal processes the received request and displays the response text in the chat box. The output is the response information displayed to the user.

[0801] (Application Example 1)

[0802] 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."

[0803] Traditional travel planning systems required users to individually research destinations, accommodations, and activities, which was inefficient. Furthermore, adjusting routes and stops during travel was difficult. Therefore, there was a need for a system that could perform real-time travel planning and information gathering, especially while traveling in vehicles like autonomous vehicles.

[0804] 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.

[0805] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, activities, places to stop along the way, and optimal routes from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, and means for transmitting the generated response to the user. This makes it possible to efficiently and conveniently plan a trip even while traveling and to obtain necessary information in real time.

[0806] A "user" is an individual or group that uses the system to make travel-related inquiries.

[0807] An "inquiry" is the act of a user asking the system for information about their travel plans or destination.

[0808] "Intention" refers to the specific purpose or desire that the user expects from the system.

[0809] "Travel destination" refers to the place or region that the user plans to visit.

[0810] "Accommodation facilities" refer to places of lodging, such as hotels and inns, where users stay during their travels.

[0811] "Activities" refer to activities such as sightseeing, leisure, and dining that you plan to do at your travel destination.

[0812] "Places to stop by" refers to tourist spots or rest areas that users should visit along their journey.

[0813] The "optimal route" refers to the path or route that allows for efficient and comfortable travel to a destination.

[0814] A "database" is a source of information that stores information about travel destinations, accommodations, activities, and routes.

[0815] "Natural language processing" is a technology that enables computers to understand and analyze natural human language.

[0816] A "server" is a central computing system that analyzes user inquiries, generates responses, and provides them.

[0817] A "query" is a search request made to retrieve specific information from a database.

[0818] A "response" is the answer that a server generates in response to a user's inquiry.

[0819] The system for realizing this invention includes the following components.

[0820] 1. User terminal:

[0821] The user terminal operates on the infotainment system of the autonomous vehicle. It provides an interface where the user can make travel-related inquiries by voice. The terminal converts the voice to text and sends that text to the server.

[0822] 2. Server:

[0823] The server is the primary processing unit that receives and analyzes queries sent from user terminals and provides the necessary information. Specifically, it uses the following hardware and software:

[0824] Hardware: High-performance server computer

[0825] Software: Python, SQLite database, transformers library

[0826] The server uses natural language processing (NLP) techniques to analyze user inquiries and identify user intent. For this purpose, it uses the BERT model available from the transformers library. It then executes database queries to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes.

[0827] 3. Database:

[0828] The database stores detailed information about travel destinations, accommodations, activities, and routes. It uses an SQLite database and provides the necessary information in response to queries from the server.

[0829] As a concrete example, if a user asks via voice, "I'm planning a weekend trip with a close friend. Do you have any recommendations?", the system will operate as follows:

[0830] The user's device converts the audio to text and sends that text data to the server.

[0831] The server processes the received text data using a natural language processing model to analyze the user's intent. For example, it might identify "recommended travel destinations to visit with close friends on the weekend."

[0832] The server executes relevant queries against the SQLite database to retrieve appropriate travel destination information.

[0833] Based on the information it retrieves, the server generates a response saying, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, and there's plenty of delicious food."

[0834] The server sends the generated response to the user's terminal, and the user's terminal displays its contents to the user.

[0835] This system allows users to efficiently and conveniently plan their trips while on the go and obtain necessary information in real time. Possible prompts include phrases like, "I'd like to travel with friends this weekend; what are some recommended destinations?"

[0836] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0837] Step 1:

[0838] Users make travel-related inquiries by voice. Specifically, they use the infotainment system of an autonomous vehicle to voice prompts such as, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" The input is the user's voice.

[0839] Step 2:

[0840] The device receives voice input and converts it to text. Specifically, it uses its voice recognition system to analyze the voice data and generate text data. The output is the user's inquiry in text format.

[0841] Step 3:

[0842] The terminal sends text data to the server. Specifically, it uses its communication module to send text data to the server's API endpoint. The input is the user's query in text format, and the output is a notification to the server that the transmission is complete.

[0843] Step 4:

[0844] The server receives text data and analyzes it using a natural language processing (NLP) model. Specifically, it uses Python scripts and the transformers library on the server to identify the user's intent. For example, it might identify "recommended travel destinations to go to with close friends on the weekend." The input is the user's inquiry in text format, and the output is the analyzed user intent.

[0845] Step 5:

[0846] The server executes queries against the database based on the user's intent. Specifically, it executes SQL queries related to an SQLite database to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes. The input is the user's intent, and the output is the database search results.

[0847] Step 6:

[0848] The server generates a response to provide to the user based on the database search results. Specifically, it creates a response message based on the retrieved information, for example, "Tokyo is recommended. You can enjoy sightseeing and shopping, and there are many delicious restaurants." The input is the database search results, and the output is the generated response message.

[0849] Step 7:

[0850] The server sends the generated response message to the terminal. Specifically, it uses the server's communication module to send the response message to the terminal. The input is the generated response message, and the output is a notification to the terminal that the transmission is complete.

[0851] Step 8:

[0852] The terminal displays the response received from the server to the user. Specifically, it uses the terminal's display or speaker to present the response message to the user. The input is the response message from the server, and the output is the information presented to the user.

[0853] 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.

[0854] This invention provides a system that enables users to efficiently plan their trips. Specifically, it proposes a system that receives and analyzes travel-related inquiries from users to identify their intentions and provide appropriate information. Furthermore, by combining this with an emotion engine, it offers suggestions and responses based on the user's emotions. This system can provide users with a more personalized experience.

[0855] System Configuration

[0856] This system consists of the following main components:

[0857] 1. User terminal

[0858] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0859] The user terminal has the function to send the inquiry details to the server.

[0860] 2. Server

[0861] The server plays a central role in receiving user inquiries and analyzing their content.

[0862] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[0863] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0864] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0865] The server generates a response to provide to the user based on the information it has obtained.

[0866] The server sends the generated response to the user's terminal.

[0867] 3. Database

[0868] The database stores detailed information about travel destinations, accommodations, and activities.

[0869] The server queries the database to retrieve the necessary information.

[0870] 4. Emotional Engine

[0871] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0872] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[0873] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[0874] System operation

[0875] Examples of user inquiries

[0876] The user enters an inquiry saying, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0877] Server Processing

[0878] Reception: The server receives a query from the user's terminal.

[0879] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent and emotions. In this case, the keyword "stressed" leads to the conclusion that the user is seeking relaxation.

[0880] Emotion Recognition: The emotion engine recognizes the user's emotion as "stress."

[0881] Information retrieval: The server queries the database to find information on relaxing travel destinations, accommodations, and activities.

[0882] Response Generation: Based on the information the server has acquired, it uses an emotion engine to generate a response to provide to the user. In this case, it would generate a response such as, "Okinawa resorts are highly recommended. They offer relaxing beachfront environments and excellent spas. There are many resort hotels that provide a relaxing atmosphere."

[0883] Sending: The server sends the generated response to the user's terminal.

[0884] Display on the user's terminal

[0885] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0886] Specific example

[0887] For example, if a user asks, "I'm tired and would like to take a vacation. Are there any places where I can relax?", the server will use an emotion engine to analyze the emotional keywords "relax" and "vacation" and suggest relaxing travel destinations. In this case, it would generate and provide a response such as, "I recommend a resort in Bali. It has beautiful beaches and abundant spa services, where you can refresh both your mind and body."

[0888] The system of the present invention can efficiently perform these processes to propose the optimal travel plan for the user. Furthermore, by combining it with an emotion engine, it is possible to provide personalized services that are attentive to the user's emotions.

[0889] The following describes the processing flow.

[0890] Step 1:

[0891] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[0892] Step 2:

[0893] The terminal receives the user's inquiry and forms an API request to send to the server.

[0894] Step 3:

[0895] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[0896] Step 4:

[0897] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[0898] Step 5:

[0899] The server analyzes the received inquiry using natural language processing technology to identify the user's intent. In this case, keywords such as "I'm stressed" and "a relaxing travel destination" are analyzed.

[0900] Step 6:

[0901] The server uses an emotion engine to recognize the user's emotions from the content of their inquiry. For example, it might recognize from the keyword "stress" that the user is seeking relaxation.

[0902] Step 7:

[0903] The server queries the database based on the user's intentions and emotions. For example, it might search for information on relaxing travel destinations, accommodations, and activities.

[0904] Step 8:

[0905] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[0906] Step 9:

[0907] The server generates a response to provide to the user based on information retrieved from the database. An emotion engine is used to adjust the tone and content of the response. For example, it might create a response like, "I recommend Okinawa resorts. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0908] Step 10:

[0909] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[0910] Step 11:

[0911] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[0912] Step 12:

[0913] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[0914] (Example 2)

[0915] 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."

[0916] Conventional travel planning support systems typically provide generic responses to user inquiries, rarely offering personalized suggestions tailored to the user's emotions or specific needs. This made it difficult for users to obtain information about travel destinations that suited their feelings and circumstances, often leading to stress. Furthermore, generating responses that consider user emotions requires advanced technology, which was challenging for conventional systems. Therefore, there is a need for a travel planning support system capable of providing information that resonates with the user's emotions.

[0917] 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.

[0918] In this invention, the server includes means for receiving travel-related inquiries from users; means for analyzing the content of the user's inquiry and identifying the user's intentions and emotions; means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intentions and emotions; means for generating a response to provide the user with the obtained information using an emotion engine; and means for sending the generated response to the user. This makes it possible to provide personalized travel information that is attentive to the user's emotions.

[0919] A "user" refers to an individual or legal entity that uses the system to make travel-related inquiries.

[0920] "Travel-related inquiries" refer to questions or requests from users seeking information about accommodations, destinations, activities, etc., through the system.

[0921] A "server" refers to a central computing resource that receives and analyzes user inquiries, retrieves necessary information, and generates and sends responses.

[0922] "Natural language processing" refers to the techniques used by computers to understand and analyze human language, and specifically includes processes such as text tokenization, semantic analysis, and tagging.

[0923] An "emotion engine" refers to a technology that analyzes the emotions behind a user's inquiry and generates an appropriate response based on that analysis.

[0924] A "database" refers to a collection of stored data that contains information about travel destinations, accommodations, and activities, which a server uses to query and retrieve that information.

[0925] A "query" refers to a statement of inquiry executed to retrieve specific information from a database.

[0926] "Response" refers to the information that a server generates and provides to a user in response to a user's inquiry.

[0927] "Personalized suggestions" refer to specific travel information and advice tailored to the individual needs and feelings of the user.

[0928] This invention is a system that enables users to efficiently plan their travels. Specifically, it receives and analyzes user inquiries to identify the user's intentions and emotions, and then provides appropriate information. By combining this system with an emotion engine, it can offer suggestions and responses based on the user's emotions, providing a more personalized experience.

[0929] System Configuration

[0930] This system consists of the following main components:

[0931] 1. User terminal

[0932] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[0933] The user terminal has the function to send the inquiry details to the server.

[0934] 2. Server

[0935] The server plays a central role in receiving user inquiries and analyzing their content.

[0936] The server uses natural language processing techniques to analyze the query content and identify the user's intent and sentiment.

[0937] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[0938] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[0939] The server generates a response to provide to the user based on the information it has obtained.

[0940] The server sends the generated response to the user's terminal.

[0941] 3. Database

[0942] The database stores detailed information about travel destinations, accommodations, and activities.

[0943] The server queries the database to retrieve the necessary information.

[0944] 4. Emotional Engine

[0945] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[0946] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[0947] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[0948] The technologies used

[0949] Natural language processing technology:

[0950] The server uses natural language processing technologies such as Google's BERT and OpenAI's GPT-4 to analyze user inquiries.

[0951] Database technology:

[0952] The server uses database management systems such as MySQL and MongoDB to store travel-related information and retrieve it by executing queries.

[0953] Emotion analysis technology:

[0954] The server uses Affective Computing Lab's emotion analysis engine and other tools to analyze the user's emotions and generate responses based on that analysis.

[0955] Specific example

[0956] Examples of inquiries

[0957] User: "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[0958] The server will perform the following steps:

[0959] 1. The server receives a query from the user's terminal.

[0960] 2. The server uses an NLP model (e.g., BERT or GPT-4) to analyze the query.

[0961] 3. The server identifies the user's intentions and emotions from the analysis. For example, it can understand the user's intention to relax from the phrase "I'm stressed."

[0962] 4. The emotion engine recognizes the user's emotions as "stress."

[0963] 5. The server queries the database to retrieve information about suitable travel destinations.

[0964] 6. Based on the information it has acquired, the server uses an emotion engine to generate a response to provide to the user. For example, it might create a response such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[0965] 7. The server sends the generated response to the user's terminal.

[0966] 8. The user terminal displays the received response to the user.

[0967] Example of a prompt

[0968] "I'm tired and would like to take a vacation. Are there any places where I can relax?"

[0969] "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0970] With the above configuration, it becomes possible to efficiently propose travel plans that are tailored to the user's emotions.

[0971] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0972] Step 1:

[0973] User: The user accesses the system using a terminal and enters travel-related inquiries. For example, they might enter a specific prompt such as, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[0974] Terminal: Sends the entered query to the server. At this time, the terminal generates an HTTP request and sends data containing the query content to the server. The input is the user's text message, and the output is an HTTP request addressed to the server.

[0975] Step 2:

[0976] Server: The server receives HTTP requests sent from terminals. It converts the received data into a parseable format (e.g., JSON) and passes it to its internal system. The input is an HTTP request from a terminal, and the output is parseable data.

[0977] Step 3:

[0978] Server: The server uses natural language processing (NLP) techniques to analyze the query content. Specifically, it uses generative AI models (e.g., BERT or GPT-4) to tokenize, semantically analyze, and tag the text. The input is the user's query text, and the output is the analyzed text data.

[0979] Step 4:

[0980] Server: The server identifies the user's intentions and emotions based on the analysis results of the NLP model. It uses an emotion engine to extract emotions and intentions such as "stress" and "want to relax." The input is the analyzed text data, and the output is user intention and emotion information.

[0981] Step 5:

[0982] Server: The server queries the database to retrieve information on relaxing travel destinations, accommodations, and activities. The database contains detailed information about travel destinations, accommodations, and activities. The input is user intent and sentiment information, and the output is the retrieved travel-related information.

[0983] Step 6:

[0984] Server: Based on the information it retrieves, the server uses an emotion engine to generate responses to provide to the user. Specifically, it might create responses such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and excellent spas." The input is information retrieved from the database, and the output is the generated response message.

[0985] Step 7:

[0986] Server: Sends the generated response message to the user's terminal as an HTTP response. The input is the generated response message, and the output is the HTTP response sent to the terminal.

[0987] Step 8:

[0988] Terminal: The user terminal receives HTTP responses from the server and displays them on the screen. The user can then proceed with their travel plan based on the displayed suggestions. Input is the HTTP response from the server, and output is the response message displayed to the user.

[0989] (Application Example 2)

[0990] 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."

[0991] Conventional travel planning systems can provide basic information in response to user inquiries, but they have difficulty providing personalized suggestions that reflect the user's emotions and specific intentions. Furthermore, in-store customer service has limited detailed information provision regarding travel, making it difficult to improve customer satisfaction. This invention aims to solve these problems and provide a system that offers optimal travel suggestions based on the user's emotions, thereby improving in-store service.

[0992] 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. In this invention, the server includes means for receiving travel inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information on travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, means including an emotion recognition engine that recognizes emotions and adjusts the tone and expression of the response based on those emotions, and means for being installed in a customer support robot at a physical store. This makes it possible to provide personalized travel suggestions that are attentive to the user's emotions, and is expected to improve services at physical stores.

[0993] A "user terminal" is a device used by a user to access the system and enter inquiries, and includes smartphones, tablet devices, personal computers, etc.

[0994] A "server" is a central system that receives user inquiries, analyzes their content, identifies the user's intent, and provides appropriate information using an emotion recognition engine.

[0995] "Natural language processing" is a technology that analyzes user inquiries and identifies the user's intent, involving the analysis and interpretation of meaning of text data.

[0996] A "database" is a storage device that stores detailed information about travel destinations, accommodations, and activities, and provides the necessary information in response to queries from a server.

[0997] An "emotion recognition engine" is a system that recognizes emotions from the content of a user's inquiry and adjusts the tone and expression of the response, providing the most suitable suggestions based on the user's emotions.

[0998] A "customer support robot" is a robot designed to handle customer interactions in physical stores and has functions such as suggesting travel plans and providing customer service.

[0999] This invention is a system to be installed in a customer support robot designed to improve customer service in physical stores. The system consists of a user terminal, a server, a database, an emotion recognition engine, and a customer support robot for use in physical stores.

[1000] First, the user terminal is a device that customers use to access the system and enter travel-related inquiries. The inquiries entered from the user terminal are sent to the server.

[1001] The server receives inquiries from user terminals, analyzes them using natural language processing, and identifies the user's intent. The analysis uses the natural language processing library "transformers." This technology allows for the specific identification of what the user is requesting.

[1002] Next, the server uses an emotion recognition engine to recognize the user's emotions from the content of their inquiry. Here, an emotion analysis model is used to understand the user's emotional state. This step enables the server to provide optimal suggestions tailored to the user's emotions.

[1003] Based on the analyzed intentions and emotions, the server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities. The database contains detailed information on domestic and international travel destinations.

[1004] Based on the information acquired by the server, a response is generated to be provided to the user. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response to achieve a human-like dialogue that is attentive to the user's emotions.

[1005] Finally, the generated response is delivered to the user via a user terminal or a customer support robot in a physical store. This customer support robot provides detailed travel suggestions and advanced service to customers in the store.

[1006] For example, if a user asks, "I've been feeling stressed lately, so could you recommend a relaxing travel destination?", the server analyzes the user's request using keywords like "relax" and "stress." The emotion recognition engine then recognizes the user's emotional state as "stressed" and generates a response such as, "I recommend a resort in Okinawa. It has a relaxing beach environment and plenty of spas," which is then provided to the user.

[1007] Other examples of prompt statements include the following:

[1008] "I'm thinking about a road trip, but what would you recommend as a destination?"

[1009] "What hotels would you recommend for business travel?"

[1010] "What activities can we enjoy on a family trip?"

[1011] This system will enable personalized travel suggestions based on user emotions, which is expected to improve in-store services.

[1012] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1013] Step 1:

[1014] The system receives inquiries from user devices. Users use smartphones, tablets, etc., to input travel-related questions and send them to the server. The input is the user's inquiry, and the output is the inquiry data received by the server.

[1015] Step 2:

[1016] The server analyzes the received query. It uses natural language processing techniques to analyze the query content and identify the user's intent. Specifically, it uses the natural language processing library "transformers" to analyze text data. The input is the received query data, and the output is the analyzed user intent data.

[1017] Step 3:

[1018] The server uses an emotion recognition engine to recognize the user's emotions. The query is input into an emotion analysis model to identify the user's emotional state. The input is the analyzed user intent data, and the output is the user's emotion data.

[1019] Step 4:

[1020] The server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities based on the user's intent and sentiment. It issues queries to the database and searches for the necessary information. The input is user intent data and sentiment data, and the output is the retrieved travel information.

[1021] Step 5:

[1022] The server generates a response to provide to the user based on the acquired information. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response. The input is the acquired travel information, and the output is response data that corresponds to the emotion.

[1023] Step 6:

[1024] The server sends the generated response data to the user terminal or a customer support robot in a physical store. The user terminal or robot displays this response and provides it to the user. The input is emotion-sensitive response data, and the output is the displayed response information.

[1025] Step 7: The user decides on an action based on the suggestions. The travel plan is advanced based on the information provided by the user terminal or customer support robot. The input is the displayed response information, and the output is the user's next action.

[1026] 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.

[1027] 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.

[1028] 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.

[1029] [Fourth Embodiment]

[1030] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1031] 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.

[1032] 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).

[1033] 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.

[1034] 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.

[1035] 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).

[1036] 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.

[1037] 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.

[1038] 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.

[1039] 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.

[1040] 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.

[1041] 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.

[1042] 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".

[1043] This invention provides a system that enables users to efficiently plan their trips. Specifically, it aims to build a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This invention will be convenient for many users and support efficient travel planning.

[1044] System Configuration

[1045] This system consists of the following main components:

[1046] 1. User terminal

[1047] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[1048] The user terminal has the function to send the inquiry details to the server.

[1049] 2. Server

[1050] The server plays a central role in receiving user inquiries and analyzing their content.

[1051] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[1052] The server retrieves the appropriate information from the database based on the user's intent.

[1053] The server generates a response to provide to the user based on the information it has obtained.

[1054] The server sends the generated response to the user's terminal.

[1055] 3. Database

[1056] The database stores detailed information about travel destinations, accommodations, and activities.

[1057] The server queries the database to retrieve the necessary information.

[1058] System operation

[1059] Examples of user inquiries

[1060] The user enters the question, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[1061] Server Processing

[1062] Reception: The server receives a query from the user's terminal.

[1063] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent. In this case, the analysis is based on the keyword "weekend trip with close friends."

[1064] Information retrieval: The server queries the database to retrieve information on suitable destinations, accommodations, and activities for weekend getaways.

[1065] Response Generation: Based on the information the server has obtained, it generates a response to provide to the user. In this case, the response would be something like, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[1066] Sending: The server sends the generated response to the user's terminal.

[1067] Display on the user's terminal

[1068] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[1069] Specific examples

[1070] For example, if a user asks, "Are there any good places for a family summer vacation?", the server retrieves information on suitable summer vacation destinations for families from its database and generates a response such as, "Okinawa is recommended. It has beautiful beaches, family-friendly resort hotels, cultural experiences, Okinawan cuisine, and more," and sends it to the user's terminal.

[1071] The system of the present invention can efficiently perform these series of processes to propose the optimal travel plan for the user.

[1072] The following describes the processing flow.

[1073] Step 1:

[1074] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I'm planning a weekend trip with a close friend. Do you have any recommendations?"

[1075] Step 2:

[1076] The terminal receives the user's inquiry and forms an API request to send to the server.

[1077] Step 3:

[1078] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[1079] Step 4:

[1080] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[1081] Step 5:

[1082] The server analyzes the received query content using natural language processing techniques. Models such as ChatGPT are used to identify the information and intent the user is seeking.

[1083] Step 6:

[1084] The server executes queries against the database based on the user's intent. For example, it might search for information on suitable travel destinations, accommodations, and activities for a weekend getaway.

[1085] Step 7:

[1086] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[1087] Step 8:

[1088] The server generates a response to provide to the user based on information retrieved from the database. Using ChatGPT, it can create a response such as, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, as well as delicious food. For accommodation, Hotel XX in Chuo Ward is particularly popular."

[1089] Step 9:

[1090] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[1091] Step 10:

[1092] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[1093] Step 11:

[1094] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[1095] (Example 1)

[1096] 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".

[1097] Traditional travel planning systems had the problem of not being able to quickly and accurately provide users with the information they needed. In particular, accurately interpreting inquiries, understanding the user's intentions, and suggesting appropriate destinations, accommodations, and activities was technically challenging.

[1098] 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.

[1099] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, and means for displaying it on the user's terminal. This makes it possible to accurately understand the user's intent and support travel planning quickly and effectively.

[1100] A "user terminal" refers to a device used by a user to access the system and enter inquiries. This includes smartphones, tablets, and personal computers.

[1101] A "server" is a central processing unit that receives user inquiries, analyzes their content, retrieves and generates appropriate information, and sends it to the user's terminal.

[1102] "Means for receiving inquiries" refers to the function that allows the server to receive travel-related inquiries sent from user terminals.

[1103] "Means for identifying intent" refers to the functionality that allows a server to analyze a user's inquiry and understand their intent. These means include natural language processing techniques and generative AI models.

[1104] "Means of obtaining information" refers to the function that allows a server to retrieve information about travel destinations, accommodations, and activities from a database by executing queries based on the user's intentions.

[1105] "Means for generating a response" refers to the function that creates a response to provide to the user based on the information acquired by the server.

[1106] "Means for sending a response" refers to the function that sends the response generated by the server to the user's terminal.

[1107] "Display means" refers to a function that allows the user terminal to visually display the response received from the server to the user.

[1108] Modes for carrying out the invention

[1109] This invention provides a system that enables users to efficiently plan their trips. Specifically, it is a system that allows users to make travel-related inquiries in natural language, analyzes the content of those inquiries, and suggests appropriate destinations, accommodations, and activities. This system consists of the following components.

[1110] User terminal

[1111] User terminals include devices such as smartphones, tablets, and personal computers, which users access the system to enter inquiries. The inquiries entered by the user are sent to the server in text format.

[1112] server

[1113] The server is the central device of this system. It receives inquiries from user terminals and analyzes their content. The server uses natural language processing (NLP) and generative AI models (e.g., GPT-3) to analyze the inquiries and identify the user's intent. Based on the analysis, the server queries the database and retrieves the appropriate information. Based on the retrieved information, the server generates a response to provide to the user and sends it to the user terminal.

[1114] database

[1115] The database stores detailed information about travel destinations, accommodations, and activities. The server queries the database to retrieve relevant information based on the user's intent. The database is optimized to provide relevant information in real time.

[1116] Explanation of specific examples

[1117] When a user asks, "I'm planning a weekend trip with close friends. Do you have any recommendations?", the server receives the inquiry. Using NLP (Neuro-Linguistic Programming) techniques, the server analyzes the keyword "weekend trip with close friends" to identify the user's intent. The server then queries its database to retrieve information on suitable destinations, accommodations, and activities for a weekend trip. Based on the retrieved information, the server generates a response such as, "Tokyo is a good choice. You can enjoy sightseeing and shopping, as well as delicious food. Hotel XX in Chuo Ward is particularly popular for accommodations," and sends it to the user's terminal. The user's terminal displays the received response, and the user can then proceed with their travel planning based on it.

[1118] Example of a prompt

[1119] Examples of prompt statements for generative AI models include the following:

[1120] "I want to create travel plans. Please design a system that suggests the best travel destinations, accommodations, and activities in response to user inquiries. For example, please explain in detail how the system would generate a response if a user inquired, 'Are there any good places for a family summer vacation?'"

[1121] In this way, this system combines natural language processing technology and generative AI models to accurately understand user inquiries and provide prompt and accurate support for travel planning.

[1122] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1123] Step 1: User Inquiry

[1124] The user enters a question about their travel plans into the terminal using natural language. For example, they might enter, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" This is the input information. When the user presses the submit button, the inquiry is sent to the server. The output is the text data of the inquiry.

[1125] Step 2: Server Reception

[1126] The server receives a query sent from the user's terminal. The input is text data sent from the user's terminal. The server receives the network request and extracts the text content. The output is the received query text data.

[1127] Step 3: Analyzing the inquiry content

[1128] The server analyzes the received text content using natural language processing techniques. A generative AI model (e.g., GPT-3) is used to identify the user's intent. The input is the query text data received by the server. The server extracts and analyzes important keywords (e.g., "close friends," "weekend trip"). The output is data identifying the user's intent as a result of the analysis.

[1129] Step 4: Retrieve information from the database

[1130] The server executes queries against the appropriate database based on the analysis results. For example, it retrieves information on suitable travel destinations, accommodations, and activities for a weekend getaway. The inputs are the analysis results data and the database query. The server generates an SQL query and executes it against the database. The output is the retrieved travel information data.

[1131] Step 5: Generating a response

[1132] The server generates a response to provide to the user based on the information it has acquired. Using a generative AI model, the response is created in a way that is easy for the user to understand and provides useful information. The input is the acquired travel information data. The server passes the data to the generative AI model and instructs it to create a response in natural language. The output is the generated response text.

[1133] Step 6: Sending a response

[1134] The server sends the generated response to the user's terminal. The input is the generated response text. The server creates and sends a network request to send the text response to the user's terminal. The output is the sent response data.

[1135] Step 7: Display on the user's terminal

[1136] The user's terminal receives the response sent from the server and displays it to the user. This allows the user to proceed with their travel plan based on the suggested information. The input is the response data sent from the server. The user's terminal processes the received request and displays the response text in the chat box. The output is the response information displayed to the user.

[1137] (Application Example 1)

[1138] 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".

[1139] Traditional travel planning systems required users to individually research destinations, accommodations, and activities, which was inefficient. Furthermore, adjusting routes and stops during travel was difficult. Therefore, there was a need for a system that could perform real-time travel planning and information gathering, especially while traveling in vehicles like autonomous vehicles.

[1140] 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.

[1141] In this invention, the server includes means for receiving travel-related inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information about travel destinations, accommodations, activities, places to stop along the way, and optimal routes from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, and means for transmitting the generated response to the user. This makes it possible to efficiently and conveniently plan a trip even while traveling and to obtain necessary information in real time.

[1142] A "user" is an individual or group that uses the system to make travel-related inquiries.

[1143] An "inquiry" is the act of a user asking the system for information about their travel plans or destination.

[1144] "Intention" refers to the specific purpose or desire that the user expects from the system.

[1145] "Travel destination" refers to the place or region that the user plans to visit.

[1146] "Accommodation facilities" refer to places of lodging, such as hotels and inns, where users stay during their travels.

[1147] "Activities" refer to activities such as sightseeing, leisure, and dining that you plan to do at your travel destination.

[1148] "Places to stop by" refers to tourist spots or rest areas that users should visit along their journey.

[1149] The "optimal route" refers to the path or route that allows for efficient and comfortable travel to a destination.

[1150] A "database" is a source of information that stores information about travel destinations, accommodations, activities, and routes.

[1151] "Natural language processing" is a technology that enables computers to understand and analyze natural human language.

[1152] A "server" is a central computing system that analyzes user inquiries, generates responses, and provides them.

[1153] A "query" is a search request made to retrieve specific information from a database.

[1154] A "response" is the answer that a server generates in response to a user's inquiry.

[1155] The system for realizing this invention includes the following components.

[1156] 1. User terminal:

[1157] The user terminal operates on the infotainment system of the autonomous vehicle. It provides an interface where the user can make travel-related inquiries by voice. The terminal converts the voice to text and sends that text to the server.

[1158] 2. Server:

[1159] The server is the primary processing unit that receives and analyzes queries sent from user terminals and provides the necessary information. Specifically, it uses the following hardware and software:

[1160] Hardware: High-performance server computer

[1161] Software: Python, SQLite database, transformers library

[1162] The server uses natural language processing (NLP) techniques to analyze user inquiries and identify user intent. For this purpose, it uses the BERT model available from the transformers library. It then executes database queries to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes.

[1163] 3. Database:

[1164] The database stores detailed information about travel destinations, accommodations, activities, and routes. It uses an SQLite database and provides the necessary information in response to queries from the server.

[1165] As a concrete example, if a user asks via voice, "I'm planning a weekend trip with a close friend. Do you have any recommendations?", the system will operate as follows:

[1166] The user's device converts the audio to text and sends that text data to the server.

[1167] The server processes the received text data using a natural language processing model to analyze the user's intent. For example, it might identify "recommended travel destinations to visit with close friends on the weekend."

[1168] The server executes relevant queries against the SQLite database to retrieve appropriate travel destination information.

[1169] Based on the information it retrieves, the server generates a response saying, "Tokyo is highly recommended. You can enjoy sightseeing and shopping, and there's plenty of delicious food."

[1170] The server sends the generated response to the user's terminal, and the user's terminal displays its contents to the user.

[1171] This system allows users to efficiently and conveniently plan their trips while on the go and obtain necessary information in real time. Possible prompts include phrases like, "I'd like to travel with friends this weekend; what are some recommended destinations?"

[1172] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1173] Step 1:

[1174] Users make travel-related inquiries by voice. Specifically, they use the infotainment system of an autonomous vehicle to voice prompts such as, "I'm planning a weekend trip with a close friend. Do you have any recommendations?" The input is the user's voice.

[1175] Step 2:

[1176] The device receives voice input and converts it to text. Specifically, it uses its voice recognition system to analyze the voice data and generate text data. The output is the user's inquiry in text format.

[1177] Step 3:

[1178] The terminal sends text data to the server. Specifically, it uses its communication module to send text data to the server's API endpoint. The input is the user's query in text format, and the output is a notification to the server that the transmission is complete.

[1179] Step 4:

[1180] The server receives text data and analyzes it using a natural language processing (NLP) model. Specifically, it uses Python scripts and the transformers library on the server to identify the user's intent. For example, it might identify "recommended travel destinations to go to with close friends on the weekend." The input is the user's inquiry in text format, and the output is the analyzed user intent.

[1181] Step 5:

[1182] The server executes queries against the database based on the user's intent. Specifically, it executes SQL queries related to an SQLite database to retrieve information about travel destinations, accommodations, activities, places to visit, and optimal routes. The input is the user's intent, and the output is the database search results.

[1183] Step 6:

[1184] The server generates a response to provide to the user based on the database search results. Specifically, it creates a response message based on the retrieved information, for example, "Tokyo is recommended. You can enjoy sightseeing and shopping, and there are many delicious restaurants." The input is the database search results, and the output is the generated response message.

[1185] Step 7:

[1186] The server sends the generated response message to the terminal. Specifically, it uses the server's communication module to send the response message to the terminal. The input is the generated response message, and the output is a notification to the terminal that the transmission is complete.

[1187] Step 8:

[1188] The terminal displays the response received from the server to the user. Specifically, it uses the terminal's display or speaker to present the response message to the user. The input is the response message from the server, and the output is the information presented to the user.

[1189] 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.

[1190] This invention provides a system that enables users to efficiently plan their trips. Specifically, it proposes a system that receives and analyzes travel-related inquiries from users to identify their intentions and provide appropriate information. Furthermore, by combining this with an emotion engine, it offers suggestions and responses based on the user's emotions. This system can provide users with a more personalized experience.

[1191] System Configuration

[1192] This system consists of the following main components:

[1193] 1. User terminal

[1194] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[1195] The user terminal has the function to send the inquiry details to the server.

[1196] 2. Server

[1197] The server plays a central role in receiving user inquiries and analyzing their content.

[1198] The server uses natural language processing techniques to analyze the query and identify the user's intent.

[1199] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[1200] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[1201] The server generates a response to provide to the user based on the information it has obtained.

[1202] The server sends the generated response to the user's terminal.

[1203] 3. Database

[1204] The database stores detailed information about travel destinations, accommodations, and activities.

[1205] The server queries the database to retrieve the necessary information.

[1206] 4. Emotional Engine

[1207] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[1208] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[1209] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[1210] System operation

[1211] Examples of user inquiries

[1212] The user enters an inquiry saying, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[1213] Server Processing

[1214] Reception: The server receives a query from the user's terminal.

[1215] Analysis: The server analyzes the received query using natural language processing techniques to identify the user's intent and emotions. In this case, the keyword "stressed" leads to the conclusion that the user is seeking relaxation.

[1216] Emotion Recognition: The emotion engine recognizes the user's emotion as "stress."

[1217] Information retrieval: The server queries the database to find information on relaxing travel destinations, accommodations, and activities.

[1218] Response Generation: Based on the information the server has acquired, it uses an emotion engine to generate a response to provide to the user. In this case, it would generate a response such as, "Okinawa resorts are highly recommended. They offer relaxing beachfront environments and excellent spas. There are many resort hotels that provide a relaxing atmosphere."

[1219] Sending: The server sends the generated response to the user's terminal.

[1220] Display on the user's terminal

[1221] The user's terminal receives the response sent from the server and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[1222] Specific example

[1223] For example, if a user asks, "I'm tired and would like to take a vacation. Are there any places where I can relax?", the server will use an emotion engine to analyze the emotional keywords "relax" and "vacation" and suggest relaxing travel destinations. In this case, it would generate and provide a response such as, "I recommend a resort in Bali. It has beautiful beaches and abundant spa services, where you can refresh both your mind and body."

[1224] The system of the present invention can efficiently perform these processes to propose the optimal travel plan for the user. Furthermore, by combining it with an emotion engine, it is possible to provide personalized services that are attentive to the user's emotions.

[1225] The following describes the processing flow.

[1226] Step 1:

[1227] The user types their inquiry on their device and presses the send button. For example, they might enter a message like, "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[1228] Step 2:

[1229] The terminal receives the user's inquiry and forms an API request to send to the server.

[1230] Step 3:

[1231] The device sends the API request it has formed to the server. This request includes the user's inquiry and user ID.

[1232] Step 4:

[1233] The server receives API requests from terminals and parses their contents. Specifically, it parses the data received in JSON format to obtain the query details and user ID.

[1234] Step 5:

[1235] The server analyzes the received inquiry using natural language processing technology to identify the user's intent. In this case, keywords such as "I'm stressed" and "a relaxing travel destination" are analyzed.

[1236] Step 6:

[1237] The server uses an emotion engine to recognize the user's emotions from the content of their inquiry. For example, it might recognize from the keyword "stress" that the user is seeking relaxation.

[1238] Step 7:

[1239] The server queries the database based on the user's intentions and emotions. For example, it might search for information on relaxing travel destinations, accommodations, and activities.

[1240] Step 8:

[1241] The database receives queries from the server and returns the relevant information. This information includes the name of the travel destination, accommodation details, and recommended activities.

[1242] Step 9:

[1243] The server generates a response to provide to the user based on information retrieved from the database. An emotion engine is used to adjust the tone and content of the response. For example, it might create a response like, "I recommend Okinawa resorts. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[1244] Step 10:

[1245] The server sends the generated response to the user's terminal. The response is sent to the terminal in JSON format.

[1246] Step 11:

[1247] The terminal receives a response from the server, analyzes it, and displays it to the user. The user can then proceed with their travel plan based on the suggested information.

[1248] Step 12:

[1249] By reviewing the information provided and asking further questions as needed, users can create a more detailed travel plan. Through this series of interactions, users can create the optimal travel plan.

[1250] (Example 2)

[1251] 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".

[1252] Conventional travel planning support systems typically provide generic responses to user inquiries, rarely offering personalized suggestions tailored to the user's emotions or specific needs. This made it difficult for users to obtain information about travel destinations that suited their feelings and circumstances, often leading to stress. Furthermore, generating responses that consider user emotions requires advanced technology, which was challenging for conventional systems. Therefore, there is a need for a travel planning support system capable of providing information that resonates with the user's emotions.

[1253] 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.

[1254] In this invention, the server includes means for receiving travel-related inquiries from users; means for analyzing the content of the user's inquiry and identifying the user's intentions and emotions; means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intentions and emotions; means for generating a response to provide the user with the obtained information using an emotion engine; and means for sending the generated response to the user. This makes it possible to provide personalized travel information that is attentive to the user's emotions.

[1255] A "user" refers to an individual or legal entity that uses the system to make travel-related inquiries.

[1256] "Travel-related inquiries" refer to questions or requests from users seeking information about accommodations, destinations, activities, etc., through the system.

[1257] A "server" refers to a central computing resource that receives and analyzes user inquiries, retrieves necessary information, and generates and sends responses.

[1258] "Natural language processing" refers to the techniques used by computers to understand and analyze human language, and specifically includes processes such as text tokenization, semantic analysis, and tagging.

[1259] An "emotion engine" refers to a technology that analyzes the emotions behind a user's inquiry and generates an appropriate response based on that analysis.

[1260] A "database" refers to a collection of stored data that contains information about travel destinations, accommodations, and activities, which a server uses to query and retrieve that information.

[1261] A "query" refers to a statement of inquiry executed to retrieve specific information from a database.

[1262] "Response" refers to the information that a server generates and provides to a user in response to a user's inquiry.

[1263] "Personalized suggestions" refer to specific travel information and advice tailored to the individual needs and feelings of the user.

[1264] This invention is a system that enables users to efficiently plan their travels. Specifically, it receives and analyzes user inquiries to identify the user's intentions and emotions, and then provides appropriate information. By combining this system with an emotion engine, it can offer suggestions and responses based on the user's emotions, providing a more personalized experience.

[1265] System Configuration

[1266] This system consists of the following main components:

[1267] 1. User terminal

[1268] This refers to the device that users use to access a system and enter inquiries. This includes smartphones, tablets, and personal computers.

[1269] The user terminal has the function to send the inquiry details to the server.

[1270] 2. Server

[1271] The server plays a central role in receiving user inquiries and analyzing their content.

[1272] The server uses natural language processing techniques to analyze the query content and identify the user's intent and sentiment.

[1273] Furthermore, by incorporating an emotion engine, it can recognize emotions from user inquiries and adjust appropriate suggestions accordingly.

[1274] The server retrieves appropriate information from the database based on the user's intentions and emotions.

[1275] The server generates a response to provide to the user based on the information it has obtained.

[1276] The server sends the generated response to the user's terminal.

[1277] 3. Database

[1278] The database stores detailed information about travel destinations, accommodations, and activities.

[1279] The server queries the database to retrieve the necessary information.

[1280] 4. Emotional Engine

[1281] The emotion engine is a means of recognizing a user's emotions from the content of their inquiry.

[1282] Based on the server's analysis, it uses user emotion data to generate human-like responses.

[1283] The emotion engine adjusts the tone and expression of responses to provide optimal suggestions tailored to the user's emotions.

[1284] The technologies used

[1285] Natural language processing technology:

[1286] The server uses natural language processing technologies such as Google's BERT and OpenAI's GPT-4 to analyze user inquiries.

[1287] Database technology:

[1288] The server uses database management systems such as MySQL and MongoDB to store travel-related information and retrieve it by executing queries.

[1289] Emotion analysis technology:

[1290] The server uses Affective Computing Lab's emotion analysis engine and other tools to analyze the user's emotions and generate responses based on that analysis.

[1291] Specific example

[1292] Examples of inquiries

[1293] User: "I've been feeling stressed lately, so could you recommend some relaxing travel destinations?"

[1294] The server will perform the following steps:

[1295] 1. The server receives a query from the user's terminal.

[1296] 2. The server uses an NLP model (e.g., BERT or GPT-4) to analyze the query.

[1297] 3. The server identifies the user's intentions and emotions from the analysis. For example, it can understand the user's intention to relax from the phrase "I'm stressed."

[1298] 4. The emotion engine recognizes the user's emotions as "stress."

[1299] 5. The server queries the database to retrieve information about suitable travel destinations.

[1300] 6. Based on the information it has acquired, the server uses an emotion engine to generate a response to provide to the user. For example, it might create a response such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and plenty of spas. There are many resort hotels that provide a relaxing atmosphere."

[1301] 7. The server sends the generated response to the user's terminal.

[1302] 8. The user terminal displays the received response to the user.

[1303] Example of a prompt

[1304] "I'm tired and would like to take a vacation. Are there any places where I can relax?"

[1305] "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[1306] With the above configuration, it becomes possible to efficiently propose travel plans that are tailored to the user's emotions.

[1307] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1308] Step 1:

[1309] User: The user accesses the system using a terminal and enters travel-related inquiries. For example, they might enter a specific prompt such as, "I've been feeling stressed lately, so please recommend some relaxing travel destinations."

[1310] Terminal: Sends the entered query to the server. At this time, the terminal generates an HTTP request and sends data containing the query content to the server. The input is the user's text message, and the output is an HTTP request addressed to the server.

[1311] Step 2:

[1312] Server: The server receives HTTP requests sent from terminals. It converts the received data into a parseable format (e.g., JSON) and passes it to its internal system. The input is an HTTP request from a terminal, and the output is parseable data.

[1313] Step 3:

[1314] Server: The server uses natural language processing (NLP) techniques to analyze the query content. Specifically, it uses generative AI models (e.g., BERT or GPT-4) to tokenize, semantically analyze, and tag the text. The input is the user's query text, and the output is the analyzed text data.

[1315] Step 4:

[1316] Server: The server identifies the user's intentions and emotions based on the analysis results of the NLP model. It uses an emotion engine to extract emotions and intentions such as "stress" and "want to relax." The input is the analyzed text data, and the output is user intention and emotion information.

[1317] Step 5:

[1318] Server: The server queries the database to retrieve information on relaxing travel destinations, accommodations, and activities. The database contains detailed information about travel destinations, accommodations, and activities. The input is user intent and sentiment information, and the output is the retrieved travel-related information.

[1319] Step 6:

[1320] Server: Based on the information it retrieves, the server uses an emotion engine to generate responses to provide to the user. Specifically, it might create responses such as, "I recommend resorts in Okinawa. They offer relaxing beachfront environments and excellent spas." The input is information retrieved from the database, and the output is the generated response message.

[1321] Step 7:

[1322] Server: Sends the generated response message to the user's terminal as an HTTP response. The input is the generated response message, and the output is the HTTP response sent to the terminal.

[1323] Step 8:

[1324] Terminal: The user terminal receives HTTP responses from the server and displays them on the screen. The user can then proceed with their travel plan based on the displayed suggestions. Input is the HTTP response from the server, and output is the response message displayed to the user.

[1325] (Application Example 2)

[1326] 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".

[1327] Conventional travel planning systems can provide basic information in response to user inquiries, but they have difficulty providing personalized suggestions that reflect the user's emotions and specific intentions. Furthermore, in-store customer service has limited detailed information provision regarding travel, making it difficult to improve customer satisfaction. This invention aims to solve these problems and provide a system that offers optimal travel suggestions based on the user's emotions, thereby improving in-store service.

[1328] 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. In this invention, the server includes means for receiving travel inquiries from users, means for analyzing the content of the user's inquiry and identifying the user's intent, means for obtaining information on travel destinations, accommodations, and activities from a database based on the user's intent, means for generating a response to provide to the user based on the obtained information, means for transmitting the generated response to the user, means including an emotion recognition engine that recognizes emotions and adjusts the tone and expression of the response based on those emotions, and means for being installed in a customer support robot at a physical store. This makes it possible to provide personalized travel suggestions that are attentive to the user's emotions, and is expected to improve services at physical stores.

[1329] A "user terminal" is a device used by a user to access the system and enter inquiries, and includes smartphones, tablet devices, personal computers, etc.

[1330] A "server" is a central system that receives user inquiries, analyzes their content, identifies the user's intent, and provides appropriate information using an emotion recognition engine.

[1331] "Natural language processing" is a technology that analyzes user inquiries and identifies the user's intent, involving the analysis and interpretation of meaning of text data.

[1332] A "database" is a storage device that stores detailed information about travel destinations, accommodations, and activities, and provides the necessary information in response to queries from a server.

[1333] An "emotion recognition engine" is a system that recognizes emotions from the content of a user's inquiry and adjusts the tone and expression of the response, providing the most suitable suggestions based on the user's emotions.

[1334] A "customer support robot" is a robot designed to handle customer interactions in physical stores and has functions such as suggesting travel plans and providing customer service.

[1335] This invention is a system to be installed in a customer support robot designed to improve customer service in physical stores. The system consists of a user terminal, a server, a database, an emotion recognition engine, and a customer support robot for use in physical stores.

[1336] First, the user terminal is a device that customers use to access the system and enter travel-related inquiries. The inquiries entered from the user terminal are sent to the server.

[1337] The server receives inquiries from user terminals, analyzes them using natural language processing, and identifies the user's intent. The analysis uses the natural language processing library "transformers." This technology allows for the specific identification of what the user is requesting.

[1338] Next, the server uses an emotion recognition engine to recognize the user's emotions from the content of their inquiry. Here, an emotion analysis model is used to understand the user's emotional state. This step enables the server to provide optimal suggestions tailored to the user's emotions.

[1339] Based on the analyzed intentions and emotions, the server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities. The database contains detailed information on domestic and international travel destinations.

[1340] Based on the information acquired by the server, a response is generated to be provided to the user. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response to achieve a human-like dialogue that is attentive to the user's emotions.

[1341] Finally, the generated response is delivered to the user via a user terminal or a customer support robot in a physical store. This customer support robot provides detailed travel suggestions and advanced service to customers in the store.

[1342] For example, if a user asks, "I've been feeling stressed lately, so could you recommend a relaxing travel destination?", the server analyzes the user's request using keywords like "relax" and "stress." The emotion recognition engine then recognizes the user's emotional state as "stressed" and generates a response such as, "I recommend a resort in Okinawa. It has a relaxing beach environment and plenty of spas," which is then provided to the user.

[1343] Other examples of prompt statements include the following:

[1344] "I'm thinking about a road trip, but what would you recommend as a destination?"

[1345] "What hotels would you recommend for business travel?"

[1346] "What activities can we enjoy on a family trip?"

[1347] This system will enable personalized travel suggestions based on user emotions, which is expected to improve in-store services.

[1348] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1349] Step 1:

[1350] The system receives inquiries from user devices. Users use smartphones, tablets, etc., to input travel-related questions and send them to the server. The input is the user's inquiry, and the output is the inquiry data received by the server.

[1351] Step 2:

[1352] The server analyzes the received query. It uses natural language processing techniques to analyze the query content and identify the user's intent. Specifically, it uses the natural language processing library "transformers" to analyze text data. The input is the received query data, and the output is the analyzed user intent data.

[1353] Step 3:

[1354] The server uses an emotion recognition engine to recognize the user's emotions. The query is input into an emotion analysis model to identify the user's emotional state. The input is the analyzed user intent data, and the output is the user's emotion data.

[1355] Step 4:

[1356] The server executes database queries to retrieve information on suitable travel destinations, accommodations, and activities based on the user's intent and sentiment. It issues queries to the database and searches for the necessary information. The input is user intent data and sentiment data, and the output is the retrieved travel information.

[1357] Step 5:

[1358] The server generates a response to provide to the user based on the acquired information. During this response generation process, an emotion recognition engine adjusts the tone and expression of the response. The input is the acquired travel information, and the output is response data that corresponds to the emotion.

[1359] Step 6:

[1360] The server sends the generated response data to the user terminal or a customer support robot in a physical store. The user terminal or robot displays this response and provides it to the user. The input is emotion-sensitive response data, and the output is the displayed response information.

[1361] Step 7: The user decides on an action based on the suggestions. The travel plan is advanced based on the information provided by the user terminal or customer support robot. The input is the displayed response information, and the output is the user's next action.

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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.

[1368] 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.

[1369] 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.

[1370] 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."

[1371] 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.

[1372] 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.

[1373] 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.

[1374] 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.

[1375] 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.

[1376] 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.

[1377] 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.

[1378] 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.

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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.

[1383] The following is further disclosed regarding the embodiments described above.

[1384] (Claim 1)

[1385] A means of receiving travel-related inquiries from users,

[1386] A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent,

[1387] Based on the user's intent, a means for obtaining information about travel destinations, accommodations, and activities from a database,

[1388] A means for generating a response to be provided to the user based on the acquired information,

[1389] Means for sending the generated response to the user,

[1390] A system that includes this.

[1391] (Claim 2)

[1392] The system according to claim 1, characterized in that the means for identifying the user's intent involves analyzing the content of the inquiry using natural language processing.

[1393] (Claim 3)

[1394] The system according to claim 1, characterized in that the means for obtaining the aforementioned travel destinations, accommodations, and activities is to retrieve the information by executing a database query.

[1395] "Example 1"

[1396] (Claim 1)

[1397] A means of receiving travel-related inquiries from users,

[1398] A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent,

[1399] Based on the user's intent, a means for obtaining information about travel destinations, accommodations, and activities from a database,

[1400] A means for generating a response to be provided to the user based on the acquired information,

[1401] Means for sending the generated response to the user,

[1402] The display means on the user terminal,

[1403] A system that includes this.

[1404] (Claim 2)

[1405] The system according to claim 1, characterized in that the means for identifying the user's intent involves analyzing the content of the inquiry using a generative AI model employing natural language processing technology.

[1406] (Claim 3)

[1407] The system according to claim 1, characterized in that the means for obtaining the aforementioned travel destinations, accommodations, and activities is to retrieve information by executing queries against a database.

[1408] "Application Example 1"

[1409] (Claim 1)

[1410] A means of receiving travel-related inquiries from users,

[1411] A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent,

[1412] Based on the user's intent, a means of obtaining information about travel destinations, accommodations, and activities, as well as places to stop during travel and optimal routes, from a database,

[1413] A means for generating a response to be provided to the user based on the acquired information,

[1414] Means for sending the generated response to the user,

[1415] A system that includes this.

[1416] (Claim 2)

[1417] The system according to claim 1, characterized in that the means for identifying the user's intent involves analyzing the content of the inquiry using natural language processing.

[1418] (Claim 3)

[1419] The system according to claim 1, characterized in that the means for obtaining information about the aforementioned travel destination, accommodation, and activities, as well as places to stop by and the best route, is to retrieve information by executing a database query.

[1420] "Example 2 of combining an emotion engine"

[1421] (Claim 1)

[1422] A means of receiving travel-related inquiries from users,

[1423] A means of analyzing the content of the user's inquiry and identifying the user's intent and emotions,

[1424] A means for obtaining information about travel destinations, accommodations, and activities from a database based on the user's intentions and emotions,

[1425] Means for generating a response to provide the user with the acquired information using an emotion engine,

[1426] Means for sending the generated response to the user,

[1427] A system that includes this.

[1428] (Claim 2)

[1429] The system according to claim 1, characterized in that the means for identifying the user's intent and emotions involves analyzing the content of the inquiry using natural language processing and sentiment analysis.

[1430] (Claim 3)

[1431] The system according to claim 1, characterized in that the means for obtaining the aforementioned travel destinations, accommodations, and activities is to retrieve the information by executing a database query.

[1432] "Application example 2 when combining with an emotional engine"

[1433] (Claim 1)

[1434] A means of receiving travel-related inquiries from users,

[1435] A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent,

[1436] Based on the user's intent, a means for obtaining information about travel destinations, accommodations, and activities from a database,

[1437] A means for generating a response to be provided to the user based on the acquired information,

[1438] Means for sending the generated response to the user,

[1439] Means including an emotion recognition engine that recognizes an emotion and adjusts the tone and expression of the response based on that emotion,

[1440] Methods for installing on customer support robots in physical stores,

[1441] A system that includes this.

[1442] (Claim 2)

[1443] The system according to claim 1, characterized in that the means for identifying the user's intent involves analyzing the content of the inquiry using natural language processing.

[1444] (Claim 3)

[1445] The system according to claim 1, characterized in that the means for obtaining the aforementioned travel destinations, accommodations, and activities is to retrieve the information by executing a database query. [Explanation of Symbols]

[1446] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving travel-related inquiries from users, A means of analyzing the content of the inquiry from the aforementioned user and identifying the user's intent, Based on the user's intent, a means for obtaining information about travel destinations, accommodations, and activities from a database, A means for generating a response to be provided to the user based on the acquired information, Means for sending the generated response to the user, A system that includes this.

2. The system according to claim 1, characterized in that the means for identifying the user's intent is to analyze the content of the inquiry using natural language processing.

3. The system according to claim 1, characterized in that the means for obtaining the aforementioned travel destinations, accommodations, and activities is to retrieve the information by executing a database query.

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