System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting tourist attraction information; means for analyzing the collected information and extracting features and word-of-mouth information; means for translating the extracted information into a plurality of languages; means for storing the translated information in a database; means for providing the translated information in response to a search query from a user; and means for making a reservation for a facility based on the provided information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, interest in Japan's tourist spots among foreign tourists has been growing, but providing accurate local information in multiple languages ​​remains a challenge. Furthermore, there is a lack of systems that can efficiently collect tourist spot features and reviews and quickly and accurately translate them. There is also a need for a function that allows local users to easily obtain ratings and review information on popular spots in multiple languages ​​and smoothly complete the reservation process. The present invention aims to solve these problems. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for collecting tourist spot information, a means for analyzing the collected information and extracting features and reviews, a means for translating the extracted information into multiple languages, a means for storing the translated information in a database, a means for providing the translated information in response to a user's search query, and a means for making reservations at facilities based on the provided information. Specifically, a server collects tourist spot information via web scraping or an API, and analyzes and translates the information using generative AI. The system then provides multilingual information to the user's device in response to the search query, and completes the reservation process. In this way, a system is realized that allows foreign tourists to easily obtain information about popular local spots and smoothly proceed with reservations.

[0006] "Tourist spot information" is data that includes basic information, characteristics, reviews, word-of-mouth, etc. about tourist spots and famous places.

[0007] "Means of collection" refers to the technology and methods for automatically obtaining tourist spot information from the Internet.

[0008] "Means of analysis" refers to the algorithms and processes used to organize collected tourist spot information and extract features and reviews.

[0009] "Means of extraction" refers to techniques and methods for extracting important parts or key points from analyzed information.

[0010] "Translation means" refers to the techniques and methods used to translate extracted information into a different language.

[0011] "Means of storing in a database" refers to the technology and methods used to organize and store translated information so that it can be quickly retrieved when needed.

[0012] "Means for responding to search queries" refers to technologies and methods for providing relevant information based on a user's search request.

[0013] "Means of providing" refers to the technology or method for displaying information obtained in response to a search query on a user's device.

[0014] "Means for making a reservation" refers to the technology or method for actually making a reservation for the tourist spot selected by the user.

[0015] The term "system" refers to the entire computer-based configuration in which the above means work in conjunction with one another to achieve a series of processes. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a 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 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0034] The storage 32 stores a data generation model 58 and an 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 process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0037] This invention is a system that collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to easily make reservations for facilities based on that information. The specific program processing of this system is explained below in natural language, with specific examples also included.

[0038] Data collection and analysis

[0039] Subject: Server

[0040] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (such as name, address, and contact information) and user reviews. The collected data is saved in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[0041] Data Translation

[0042] Subject: Server

[0043] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[0044] Processing search queries and providing information

[0045] Subject: User device

[0046] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0047] Facility reservation

[0048] Subject: User device

[0049] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[0050] Specific examples

[0051] Example 1: Collecting and translating tourist spot information

[0052] Subject: Server

[0053] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[0054] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[0055] Translate the extracted information into English, Chinese, and Korean.

[0056] The translation results are stored in a database.

[0057] Example 2: User search and facility reservation

[0058] Subject: User device

[0059] When a user searches for "Sensoji Temple," the request is sent to the server.

[0060] The server searches the database and returns the relevant information to the user terminal.

[0061] The user terminal displays the returned information to the user.

[0062] The user clicks on the reservation button and a reservation request is sent to the server.

[0063] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0064] The user terminal displays the reservation confirmation information.

[0065] The above is a description of a specific embodiment for carrying out the present invention. This system allows foreign tourists to easily obtain information about tourist spots in Japan in multiple languages ​​and makes it possible to smoothly make reservations at facilities.

[0066] The processing flow will be explained below.

[0067] Step 1: Gather information

[0068] Subject: Server

[0069] The server launches a web scraping program and API client for collecting tourist information. Web scraping obtains information on tourist spots in Tokyo from tourism sites and tourism promotion sites. The API client obtains data using the APIs of map services and review sites. The collected information is temporarily saved in JSON format.

[0070] Step 2: Data structuring

[0071] Subject: Server

[0072] The server extracts the necessary basic information (such as name, address, and contact details) from the collected JSON data. It then classifies the data into different categories, such as facility information and review information, and converts it into a format that can be inserted into a database. This structured data is then stored in the database.

[0073] Step 3: Extracting features and reviews

[0074] Subject: Server

[0075] Generative AI is used to extract the characteristics and key reviews of each tourist spot from the stored data. The AI ​​model then uses text analysis techniques to identify and summarize positive and negative points from the reviews.

[0076] Step 4: Translate the information

[0077] Subject: Server

[0078] A translation module is invoked to translate the extracted features and reviews into different languages ​​such as English, Chinese, Korean, etc. The translated information is then stored in a database together with the original Japanese information.

[0079] Step 5: Receiving a user query

[0080] Subject: User device

[0081] A user inputs search keywords to search for tourist attractions, and a search request is sent to the server.

[0082] Step 6: Database Search

[0083] Subject: Server

[0084] The server queries the database based on the received search keywords and retrieves information about the relevant tourist spots, including basic information about the facilities, their features, and translated reviews.

[0085] Step 7: Returning search results

[0086] Subject: Server

[0087] The acquired tourist spot information is converted into a format to be sent back to the user's terminal, and the appropriate translation information is selected based on the user's language settings.

[0088] Step 8: Viewing search results

[0089] Subject: User device

[0090] The user terminal displays the tourist spot information sent from the server, including basic information about the facility, translated features, and reviews.

[0091] Step 9: Submit a booking request

[0092] Subject: User device

[0093] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[0094] Step 10: Reservation Processing

[0095] Subject: Server

[0096] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[0097] Step 11: View your booking confirmation

[0098] Subject: User device

[0099] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[0100] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[0101] Example 1

[0102] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0103] In recent years, the development of the tourism industry has created a demand for multilingual tourist information systems. However, existing systems struggle to effectively integrate the collection, analysis, and translation of tourist spot information, as well as the provision of information and reservation functions to users. Another challenge is improving the accuracy of information collected from multiple sources and provision in multiple languages. This makes it difficult for users to smoothly obtain the information they need, and the reservation process becomes tedious.

[0104] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0105] In this invention, the server includes means for collecting tourist spot information using web scraping and an application program interface, means for analyzing the collected information using a generative artificial intelligence model to extract features and reviews, and means for translating the extracted information into multiple languages ​​using a generative artificial intelligence model. This enables accurate collection, analysis, translation, and provision of tourist spot information in multiple languages. Furthermore, by providing appropriate information in response to search queries from user terminals, receiving facility reservation requests, and processing reservations in cooperation with a reservation management system, users can smoothly obtain information and easily proceed with the reservation process.

[0106] "Tourist attraction information" refers to detailed information such as basic information about places visited by tourists, addresses, contact information, opening hours, access methods, and user reviews.

[0107] "Web scraping" is a technique for automatically collecting data from websites using a program.

[0108] An "Application Program Interface (API)" is a means of providing definitions and protocols for different software applications to communicate with each other.

[0109] A "generative artificial intelligence model" refers to an artificial intelligence technology that uses natural language processing to analyze input data and generate information in a format that humans can understand.

[0110] "Means of collection" refers to the methods and tools used to collect tourist attraction information through web scraping and APIs.

[0111] "Means for analysis" refers to methods and tools for analyzing collected data using a generative artificial intelligence model and extracting its features and word-of-mouth information.

[0112] "Translation means" refers to the methods and tools for converting collected and analyzed information into different languages.

[0113] "Means of storing data in a database" refers to the systems and technologies used to organize and securely store processed information.

[0114] "Means for responding to search queries" refers to methods and tools for retrieving and providing appropriate data in response to a user's search request.

[0115] "Means for receiving facility reservation requests" refers to the methods and tools by which the server receives requests from users to reserve specific facilities.

[0116] "Means for linking with a reservation management system" refers to methods and tools for communicating with an external reservation management system, checking the reservation status of the facility, and confirming reservations.

[0117] This system collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to make reservations for facilities based on that information. Specific embodiments for carrying out the present invention are described below.

[0118] Data collection and analysis

[0119] Subject: Server

[0120] The server uses web scraping technology and application program interfaces (APIs) to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup and Scrapy libraries to retrieve data from the tourist attraction's official website, and also uses public tourist information APIs to obtain additional data. The collected information includes facility name, address, contact information, user reviews, etc., and is saved in JSON format.

[0121] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). During the analysis process, it identifies and structures the characteristics of tourist spots and important review information. For example, the analysis is performed using prompt sentences such as the following:

[0122] "Enter information about Sensoji Temple. Based on this information, we will extract the facility's features and important reviews."

[0123] Data Translation

[0124] Subject: Server

[0125] The extracted information is translated into multiple languages ​​using the translation function of a generative artificial intelligence model (e.g., DeepL Translation API or Google Translation API). Languages ​​to be translated include English, Chinese, and Korean. The translated information includes summaries of the property's features and reviews, and is stored in a database (e.g., PostgreSQL).

[0126] Processing search queries and providing information

[0127] Subject: User device

[0128] When a user searches for a tourist spot, they enter a search query from their device (PC, smartphone) and send it to the server. For example, if a user searches for "Sensoji Temple," the search query is sent to the server. The server searches the database, obtains information on matching tourist spots, and returns it to the user's device. The user's device displays the response received from the server to the user.

[0129] Facility reservation

[0130] Subject: User device

[0131] If the user checks the information about a tourist spot and decides to visit, they click the "Make a reservation" button on their user device. The user device then sends a reservation request to the server. The server then connects with the facility's reservation system (e.g., external reservation management API) to confirm whether the reservation can be made. Once the reservation is confirmed, the result is notified to the user device.

[0132] Specific examples

[0133] Example 1: Collecting and translating tourist spot information

[0134] Subject: Server

[0135] The server collects information about Tokyo's tourist spots through web scraping technology (BeautifulSoup) and a public API (tourist information API).

[0136] Using generative AI (GPT-4), we extract the characteristics and important reviews of Sensoji Temple.

[0137] The extracted information is translated into English, Chinese, and Korean using the DeepL translation API.

[0138] The translation results are stored in a PostgreSQL database.

[0139] Example 2: User search and facility reservation

[0140] Subject: User device

[0141] When a user searches for "Sensoji Temple," the request is sent from the device's web application to the server.

[0142] The server searches the database and returns the relevant information to the user terminal.

[0143] The user terminal displays the returned data on a user interface.

[0144] When the user clicks the "Book Now" button, a reservation request is sent to the server.

[0145] The server connects to an external reservation management API to confirm the reservation for Sensoji Temple.

[0146] The reservation result is notified to the user terminal, and the user receives reservation confirmation information.

[0147] The above is a detailed description of the embodiment of the present invention. This system allows users to obtain information about tourist spots in multiple languages ​​and easily make reservations at facilities.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1: Data collection

[0150] Subject: Server

[0151] The server uses web scraping technology and APIs to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup library to retrieve HTML data from the tourist attraction's official website, and the Scrapy library to extract information. It also uses tourist information APIs to obtain additional information such as facility name, address, contact information, and opening hours.

[0152] Input: URL of tourist destination, tourist information API endpoint

[0153] Output: JSON format tourist spot information data

[0154] Specific behavior:

[0155] Use BeautifulSoup to process "https: / / example.com / tourist-spot / asakusa" and extract the necessary information from the HTML data.

[0156] The acquired data is converted into JSON format and prepared for the next analysis process.

[0157] Step 2: Analyze the data

[0158] Subject: Server

[0159] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). Through this analysis process, tourist spot features and important reviews are identified and structured in JSON format.

[0160] Input: JSON format tourist spot information data

[0161] Output: Parsed data in JSON format (features and reviews)

[0162] Specific behavior:

[0163] A prompt is sent to the GPT-4 API saying, "Please extract the features of Sensoji Temple," and the features and reviews are extracted.

[0164] The analysis results are reconstructed into JSON format for the next translation process.

[0165] Step 3: Translate the data

[0166] Subject: Server

[0167] The server translates the parsed information into multiple languages ​​using the DeepL Translation API or Google Translation API. The translated information includes summaries of the property's features and reviews. This information is then stored in a database.

[0168] Input: Parsed data in JSON format

[0169] Output: Multilingual JSON format data

[0170] Specific behavior:

[0171] Translate the Japanese text "Sensoji Temple is a historic temple" into English, Chinese, and Korean using the DeepL Translation API.

[0172] The translation results are compiled in JSON format and each language version is saved in the database.

[0173] Step 4: Saving to the Database

[0174] Subject: Server

[0175] The server stores the translated information in a database by connecting to a PostgreSQL database and inserting the translated data using SQL statements.

[0176] Input: JSON format data translated into multiple languages

[0177] Output: Records in the database

[0178] Specific behavior:

[0179] Connect to the PostgreSQL database and execute the SQL statement "INSERT INTO tourist_spots (name, description_jp, description_en, description_cn, description_kr) VALUES (?, ?, ?, ?, ?)".

[0180] Step 5: Processing the search query

[0181] Subject: User device

[0182] To search for tourist attractions, a user inputs a search query from their device and sends it to the server, which searches the database to obtain matching tourist attraction information and returns it to the user device.

[0183] Input: The search query entered by the user (e.g., "Sensoji Temple")

[0184] Output: Tourist spot information as search results

[0185] Specific behavior:

[0186] A search query for "Sensoji Temple" is entered from the user's device and sent to the server.

[0187] The server searches the database and retrieves the relevant information for "Sensoji Temple"

[0188] Search results are returned to the user's device in JSON format

[0189] Step 6: Viewing information

[0190] Subject: User device

[0191] The user device analyzes the tourist spot information received from the server and displays it on the user interface. The displayed information includes the facility's features, contact information, access methods, reviews, etc.

[0192] Input: Tourist spot information received from the server (JSON format)

[0193] Output: What is displayed on the user interface

[0194] Specific behavior:

[0195] Parse the received JSON data and display it on the UI using React, Vue.js, etc.

[0196] For example, information such as "Name of facility: Sensoji Temple" and "Characteristics: Historic and full of attractions" will be displayed on the screen.

[0197] Step 7: Submit a facility reservation request

[0198] Subject: User device

[0199] If the user is satisfied with the displayed information, he clicks the reservation button to send a reservation request to the server.

[0200] Input: User's booking action (e.g., "Book Sensoji Temple")

[0201] Output: Booking request sent to server

[0202] Specific behavior:

[0203] User clicks the book button

[0204] The React frontend generates a JSON booking request and sends it to the server.

[0205] Step 8: Process facility reservations

[0206] Subject: Server

[0207] The server works in conjunction with an external reservation management system to check whether a reservation can be made, completes the reservation procedure, and notifies the user terminal of the reservation result.

[0208] Input: Reservation request from user (JSON format)

[0209] Output: Reservation result (success or failure)

[0210] Specific behavior:

[0211] The server communicates with an external reservation management API (e.g., Resy API) and attempts to reserve the facility.

[0212] If the reservation is confirmed, a message stating "Reservation completed" is generated and returned to the user's device in JSON format.

[0213] If the reservation fails, an error message will be returned along with the reason.

[0214] The above is the specific processing flow of this system. By combining the detailed operations and inputs / outputs at each step, a comprehensive tourist spot information and reservation system can be realized.

[0215] (Application example 1)

[0216] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] Conventional tourist information systems lack multilingual support, making them difficult for foreign tourists to use. In addition, they lack facility reservation and location-based recommendation functions, making it difficult for tourists to plan their trips efficiently.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0219] In this invention, the server includes means for collecting tourist attraction information, means for analyzing the collected information and extracting characteristics and rating information, means for translating the extracted information into multiple languages, means for storing the translated information in a data store, means for providing the translated information in response to a search query from a terminal, means for making facility reservations based on the provided information, and means for providing recommended tourist attraction information based on the user's location information. This allows foreign tourists to easily obtain tourist information in multiple languages ​​and efficiently make facility reservations. Furthermore, the recommendation function based on the user's location information allows for smoother travel planning.

[0220] "Tourist attraction information" refers to all information related to tourism, including basic information on tourist destinations, facilities, and famous places, as well as their locations, contact information, and reviews.

[0221] "Means of collection" refers to methods or devices for gathering the required information from the internet or other data sources, such as using web scraping or APIs.

[0222] "Means of analysis" refers to software or algorithms that analyze collected information and extract useful features and word-of-mouth information.

[0223] The "translation means" refers to a translation algorithm or engine that converts the collected and analyzed information into multiple languages.

[0224] A "data store" is a database or storage system for storing collected, analyzed, and translated information.

[0225] "Search query" means a question or request sent by a user through a terminal, which serves as the basis for the server to provide information.

[0226] "Recommended tourist attraction information" is information that the server indicates to the user suitable tourist attractions based on the user's location information and interests.

[0227] The system of the present invention provides tourist attraction information and facility reservations in multiple languages, and is composed of three elements: a server, a terminal, and a user. A specific embodiment of the system is described below.

[0228] Server Processing

[0229] 1. Data Collection:

[0230] The server uses web scraping and APIs to collect basic information about tourist attractions, including their locations, contact details, and ratings from the Internet. This information is stored in JSON format.

[0231] 2. Data Analysis:

[0232] The collected information is then analyzed by a generative AI model, which extracts tourist attraction features and important reviews, summarizing key points and presenting them in a user-friendly format.

[0233] 3. Multilingual Translation:

[0234] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities. The translated information includes summaries of tourist attractions' features and ratings. The translated data is then stored in a data store, ready to respond to future search queries.

[0235] 4. Recommendation function:

[0236] The server recommends suitable tourist spots to users based on their location information and past search history, allowing users to plan their trips efficiently.

[0237] Terminal handling

[0238] 1. Submit a search query:

[0239] When a user searches for a tourist attraction on their device, the search query is sent to the server, which searches the data store to retrieve the relevant tourist attraction information and returns it to the device.

[0240] 2. Information display:

[0241] The terminal displays the tourist attraction information obtained from the server in multiple languages ​​to the user, who can then select a tourist attraction based on the displayed information.

[0242] 3. Facility Reservation:

[0243] If the user is satisfied with the displayed information and would like to visit the tourist attraction, he or she clicks the "Book" button. This click sends a reservation request from the terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the terminal of the result. The terminal then displays reservation confirmation information to the user.

[0244] Hardware and software used

[0245] Hardware: Servers are computer systems with high-performance data processing capabilities. Devices include smartphones and tablets.

[0246] Software: BeautifulSoup and Selenium are used for web scraping. Generative AI models are used for data analysis and multilingual translation. External translation functions such as Google Translate API are also used. SQLite and MySQL are used for data stores.

[0247] Specific examples

[0248] Tourist attraction information collection and translation:

[0249] The server collects and analyzes information about tourist attractions in a city from the web. For example, it extracts the characteristics and important reviews of "Tourist Attraction A" and translates them into English, Chinese, and Korean. The results are stored in a data store.

[0250] User search and facility reservation:

[0251] When a user searches for "tourist attraction A" on a device, the request is sent to the server. The server searches for the relevant information and returns it to the device. When the user confirms the information and clicks the button to make a reservation for the facility, a reservation request is sent to the server. The server completes the reservation procedure and notifies the device of the results.

[0252] Prompt Sentence Examples

[0253] "Please provide tourist information and reviews in English, Chinese, and Korean about tourist attraction A."

[0254] "Translate the tourist information and reviews about sight B into English, Chinese, and Korean."

[0255] As described above, the system of the present invention provides multilingual tourist information and facilitates facility reservations. In addition, the recommendation function based on the user's location information allows users to plan their trips more efficiently.

[0256] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0257] Step 1:

[0258] The server collects tourist attraction information using web scraping and APIs. Specifically, it accesses the specified URL, analyzes the page content using BeautifulSoup and Selenium, and extracts the necessary information (name, address, contact information, reviews, etc.). The input is the URL, and the output is the collected tourist attraction information (in JSON format).

[0259] Step 2:

[0260] The server analyzes the collected tourist attraction information using a generative AI model. Specifically, it extracts and summarizes the tourist attraction's features and important review information. The input is the collected tourist attraction information (JSON format), and the output is the analyzed information (a summary of the features and review information).

[0261] Step 3:

[0262] The server translates the extracted information into multiple languages ​​using the translation function of the generative AI model. Specifically, it translates summaries of tourist attraction features and ratings into English, Chinese, and Korean. The input is the analyzed information, and the output is the information translated into multiple languages.

[0263] Step 4:

[0264] The server stores the translated information in a data store. Specifically, it stores the data in a database system such as SQLite or MySQL. The input is the translated information, and the output is stored in the database.

[0265] Step 5:

[0266] The device collects search queries from users and sends them to the server. Specifically, the user enters the name of a tourist attraction in the device's search bar and presses the search button. The input is the user's search query, and the output is a request sent to the server.

[0267] Step 6:

[0268] The server searches the database in response to the received search query to retrieve information on the relevant tourist attractions. Specifically, the process involves retrieving appropriate translation information from the database. The input is the user's search query, and the output is the retrieved tourist attraction information.

[0269] Step 7:

[0270] The server returns the acquired tourist attraction information to the terminal. Specifically, the process returns the information acquired from the database in JSON format. The input is the acquired tourist attraction information, and the output is the transmission of information to the terminal.

[0271] Step 8:

[0272] The terminal displays the tourist attraction information received from the server to the user. Specifically, this is a process of displaying tourist attraction information in multiple languages ​​on the terminal screen. The input is information from the server, and the output is the information displayed to the user.

[0273] Step 9:

[0274] When the user clicks the reservation button, the terminal sends a reservation request to the server. Specifically, the user indicates their intention to make a reservation by operating the reservation button on the screen. The input is the user's reservation instruction, and the output is the transmission of a reservation request to the server.

[0275] Step 10:

[0276] The server communicates with the facility's reservation system based on the received reservation request to confirm whether the reservation can be made. Specifically, this process works in conjunction with the reservation system API to carry out the reservation procedure. The input is the reservation request, and the output is the reservation confirmation result.

[0277] Step 11:

[0278] The server notifies the terminal of the reservation confirmation result. Specifically, if the reservation is successful, it sends detailed information to the terminal. The input is the reservation confirmation result, and the output is a notification to the terminal.

[0279] Step 12:

[0280] The terminal displays the reservation confirmation information received from the server to the user. Specifically, this process displays a message on the terminal screen indicating that the reservation was successful and provides detailed information. The input is the reservation confirmation information from the server, and the output is the display of the reservation confirmation information to the user.

[0281] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0282] This invention is a system that collects, analyzes, and translates tourist spot information and provides it to users in multiple languages, and also combines it with an emotion engine to recommend and book tourist spots based on the user's emotional state. The specific program processing of this system is explained below in natural language, with specific examples also included.

[0283] Data collection and analysis

[0284] Subject: Server

[0285] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (name, address, contact information, etc.) and user reviews. The collected data is temporarily stored in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[0286] Data Translation

[0287] Subject: Server

[0288] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[0289] Emotion recognition by emotion engine

[0290] Subject: User device

[0291] When a user searches for a tourist spot, the user terminal receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine recognizes that the user wants to relax.

[0292] Emotion-based information recommendation

[0293] Subject: Server

[0294] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[0295] Processing search queries and providing information

[0296] Subject: User device

[0297] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0298] Facility reservation

[0299] Subject: User device

[0300] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[0301] Specific examples

[0302] Example 1: Collecting and translating tourist spot information

[0303] Subject: Server

[0304] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[0305] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[0306] Translate the extracted information into English, Chinese, and Korean.

[0307] The translation results are stored in a database.

[0308] Example 2: User search and sentiment-based facility booking

[0309] Subject: User device

[0310] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax."

[0311] The server recommends tourist spots suitable for relaxation (e.g., hot springs or tranquil scenic spots) based on the recognized emotion data.

[0312] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[0313] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0314] The user terminal displays the reservation confirmation information.

[0315] The system of the present invention can significantly improve the user experience by recognizing the user's emotions and providing optimal tourist spot information based on those emotions. The above is a description of specific embodiments for carrying out the present invention.

[0316] The processing flow will be explained below.

[0317] Step 1: Gather information

[0318] Subject: Server

[0319] The server launches a web scraping program and API client for collecting tourist information. This allows it to obtain tourist spot information from tourism and promotional sites. The collected information includes basic facility information (name, address, contact information, etc.) and user reviews. The obtained data is temporarily saved in JSON format.

[0320] Step 2: Data structuring

[0321] Subject: Server

[0322] The server extracts the necessary basic information from the collected JSON data. Specifically, it extracts data such as facility name, address, contact information, opening hours, and fees. Next, it organizes the extracted data by tourist spot and converts it into a format that can be inserted into a database. The structured data is then saved in the database.

[0323] Step 3: Extracting features and reviews

[0324] Subject: Server

[0325] The server uses generative AI to extract the characteristics and important reviews of each tourist spot from the stored data. The generative AI then uses natural language processing technology to analyze the reviews and summarise the positive and negative points. The extracted characteristics and reviews are then passed on to the next processing step.

[0326] Step 4: Translate the information

[0327] Subject: Server

[0328] The extracted features and review information are translated into multiple languages. The server calls a generative AI translation module to translate the information into English, Chinese, Korean, etc. The translated information is then stored in a database along with the original Japanese information.

[0329] Step 5: Acquire and analyze emotion data

[0330] Subject: User device

[0331] When a user searches for a tourist spot, the user's device collects the user's input data and emotional information such as audio and video in real time. The emotion engine analyzes this collected data and recognizes the user's current emotional state. For example, the emotion "I want to relax" can be read from the user's facial expression.

[0332] Step 6: Emotion-based information recommendation

[0333] Subject: Server

[0334] Based on the emotion data recognized by the emotion engine, the server recommends the most suitable tourist spot information to the user. For example, if the user is recognized as wanting to "relax," the server will search the database for relaxing tourist spots such as tranquil landscapes and hot springs, and generate a recommendation list.

[0335] Step 7: Receiving and processing a search query

[0336] Subject: User device

[0337] A user enters keywords to search for tourist attractions. The user's search query is sent to a server, which also includes data about the user's current emotional state.

[0338] Step 8: Retrieving and returning search results

[0339] Subject: Server

[0340] The server queries the database based on the user's search query and emotion data to retrieve relevant tourist spot information. The retrieved information includes basic facility information, features, translated reviews, and recommendation reasons based on the user's emotion. The retrieved information is then organized and returned to the user's device.

[0341] Step 9: Viewing search results

[0342] Subject: User device

[0343] The user's device displays the tourist spot information sent from the server, including basic facility information, translated features, reviews, and emotion-based recommendations.

[0344] Step 10: Submit a booking request

[0345] Subject: User device

[0346] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[0347] Step 11: Reservation Processing

[0348] Subject: Server

[0349] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[0350] Step 12: View your booking confirmation

[0351] Subject: User device

[0352] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[0353] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[0354] Example 2

[0355] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0356] In recent years, with the development of the global tourism industry, there has been an increasing demand for tourist spot information accessible in multiple languages. However, there is a lack of systems that provide personalized information and reservation functions based on the user's emotional state, and there is a need to improve the user experience. Conventional systems have issues with language barriers and a lack of personalization functions when providing tourist spot information, making it difficult for users to select the optimal tourist spot that matches their emotional state. Therefore, a system that can efficiently recommend and reserve tourist spots based on the user's emotional state is needed.

[0357] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for saving the translated information in a database, means for analyzing data input by a user and recognizing an emotional state, means for recommending tourist spot information based on the recognized emotional state, means for providing translated information in response to a search query from a user, and means for making reservations for facilities based on the provided information. This makes it possible to provide tourist spot information and make reservations that are optimal for the user's emotional state.

[0358] "Tourist attraction information" refers to information such as the name, address, contact information, characteristics, and reviews of specific tourist spots and facilities.

[0359] "Means of collection" refers to web scraping tools and APIs used to obtain tourist spot information from the Internet.

[0360] The "analysis means" refers to generative AI models and text analysis tools that process the collected tourist spot information and extract features and important review information.

[0361] "Means for translating into multiple languages" refers to a machine translation API for translating collected and analyzed information into other languages.

[0362] "Means for storing in a database" refers to a storage system or database management system used to efficiently manage the analyzed and translated information.

[0363] The "means for analyzing user input data" refers to an emotion engine or text analysis tool that analyzes text input from a user and recognizes their emotional state.

[0364] The "means for recognizing emotional states" refers to generative AI models and sentiment analysis APIs for analyzing emotions from user text input.

[0365] The "means for providing translated information" refers to a search engine or display tool that retrieves and displays translated information in response to a user's search query.

[0366] "Means for recommending tourist spot information" refers to an algorithm or recommendation engine that selects and recommends the most appropriate tourist spot information based on the user's emotional state.

[0367] The "means of making facility reservations" refers to an online reservation system or API that works in conjunction with the tourist spot reservation system to execute and manage reservations.

[0368] The present invention provides a system for collecting, analyzing, and translating tourist spot information, and for recommending and reserving tourist spots based on the user's emotional state. The following describes in detail an embodiment of the system.

[0369] The system consists of a server, a user terminal, and multiple software modules. The server is the main component responsible for collecting, analyzing, translating, storing, and recommending tourist attraction information. The user terminal is a device used by users to access the system, such as a desktop computer, laptop, or smartphone.

[0370] Data collection

[0371] The server uses Python's Beautiful Soup and Scrapy libraries to collect information about tourist spots on the Internet through web scraping. It also calls tourist information APIs (such as the Google Places API) to obtain basic information about tourist facilities and user reviews. The collected data is temporarily stored in JSON format.

[0372] Data analysis

[0373] The collected JSON-formatted data is analyzed using a generative AI model (e.g., GPT-4). During this analysis process, the text data is preprocessed using Python's NLTK library to extract the characteristics of each tourist spot and important review information. This preprocessing step includes tokenization and stop word removal.

[0374] Data Translation

[0375] The resulting information is then translated into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL, ready to respond to future search queries.

[0376] User Input and Emotion Recognition

[0377] The user device provides a text input interface and captures the data entered in real time when the user searches for tourist attractions. This input data is analyzed using IBM Watson's sentiment analysis API to recognize the user's current emotional state. For example, if a user searches for "places to relax," this data is recognized as the emotional state of "wanting to relax."

[0378] information recommendation

[0379] The server then recommends the most suitable tourist spot information based on the user's emotional state. For example, if a user has an emotional state indicating a desire to relax, quiet scenery or hot springs will be recommended. This process is realized using a recommendation engine.

[0380] Processing search queries

[0381] When a user searches for a specific tourist spot name (for example, "Sensoji Temple"), the query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and returns it to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0382] Facility reservation

[0383] If the user is satisfied with the displayed information and would like to visit the tourist spot, he or she clicks the "Book" button. This sends a reservation request to the server. The server communicates with the facility's reservation system (e.g., AWS RDS) to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal displays reservation confirmation information.

[0384] Specific examples

[0385] Example 1: Collecting and translating tourist spot information

[0386] Example of server behavior:

[0387] The server collects information about tourist spots in Tokyo through web scraping (using Beautiful Soup) and an API (tourist information API).

[0388] Using GPT-4, we extract the characteristics and important reviews of Sensoji Temple.

[0389] The extracted information is translated into English, Chinese, and Korean using the Google Translate API.

[0390] The translation results are stored in a MySQL database.

[0391] Example 2: User search and sentiment-based facility booking

[0392] Example of user terminal behavior:

[0393] When a user searches for "places to relax," the input data is analyzed by an emotion engine (IBM Watson API), and the user's emotion is recognized as "I want to relax."

[0394] The server recommends tourist spots suitable for relaxation (e.g., hot springs, places with tranquil scenery) based on the recognized emotion data.

[0395] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[0396] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0397] The user terminal displays the reservation confirmation information.

[0398] By implementing the above steps, the system of the present invention can efficiently provide tourist spot information and make reservations that match the user's emotional state, thereby improving the user experience.

[0399] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0400] Step 1: Data collection

[0401] The server uses Python's Beautiful Soup and Scrapy libraries to collect tourist attraction information. It accesses tourist information websites and APIs (e.g., tourist information APIs) on the Internet to obtain tourist attraction names, addresses, contact information, and user reviews. This data is temporarily saved in JSON format.

[0402] Input: URL of tourist information site, API endpoint.

[0403] Output: Tourist spot information data in JSON format.

[0404] Specific operation: The server accesses "https: / / example.com / tourist-spots", extracts the tourist spot name, address, and contact information from the HTML using Beautiful Soup, and retrieves user reviews via the API. This data is temporarily stored in JSON format.

[0405] Step 2: Data analysis

[0406] The server analyzes the collected JSON-formatted data using a generative AI model (e.g., GPT-4). During the analysis process, the characteristics of each tourist spot and important review information are extracted. During this process, the NLTK library in Python is used to preprocess the text data (e.g., tokenize and remove stop words).

[0407] Input: Temporarily saved tourist spot information data in JSON format.

[0408] Output: Parsed feature information and important reviews.

[0409] How it works: The server loads the JSON data and uses NLTK to preprocess the text data, then uses a generative AI model (GPT-4) to extract tourist attraction features and important review information.

[0410] Step 3: Data Translation

[0411] The server translates the information obtained from the analysis into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL.

[0412] Input: Parsed feature information and important reviews.

[0413] Output: Tourist spot information translated into multiple languages.

[0414] Specific operation: The server sends the analysis results to the Google Translate API and translates them into English, Chinese, Korean, etc. The translation results are then stored in the database.

[0415] Step 4: Getting User Input and Emotion Recognition

[0416] When users search for tourist attractions, their devices capture text input in real time, which is then analyzed using IBM Watson's sentiment analysis API to recognize the user's emotional state.

[0417] Input: User's search query (e.g. "places to relax").

[0418] Output: The perceived emotional state of the user (e.g., "I want to relax").

[0419] Specific operation: The user device receives the input "place to relax" from the text input field, sends it to the IBM Watson API, and receives the sentiment analysis results.

[0420] Step 5: Information recommendation

[0421] The server recommends optimal tourist spot information based on the recognized emotional state, selects tourist spots suitable for the emotional state using a recommendation engine, and provides the recommended information to the user terminal.

[0422] Input: The user's perceived emotional state (e.g., "I want to relax").

[0423] Output: Recommendation information of tourist spots based on emotional state.

[0424] Specific operation: The server searches the database for tourist spots that match the emotional state of "wanting to relax" and sends the most appropriate information to the user's terminal.

[0425] Step 6: Processing the search query

[0426] When a user searches for a specific tourist spot name, the query is sent to the server, which searches the database to retrieve information about the relevant tourist spot and returns it to the user's device.

[0427] Input: User's search query (e.g. "Sensoji Temple").

[0428] Output: Detailed information about the tourist spot.

[0429] Specific operation: The user device sends the search query "Sensoji Temple" to the server. The server searches the database, obtains information about "Sensoji Temple," and sends it to the user device.

[0430] Step 7: Facility reservation

[0431] If the user is satisfied with the displayed information and clicks the "Reserve" button, a reservation request is sent to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible and notifies the user terminal of the result.

[0432] Input: The user's booking request.

[0433] Output: Confirmed booking information.

[0434] Specific operation: When the user clicks the reservation button, a reservation request is sent to the server. The server communicates with the reservation system to confirm whether the reservation can be made and notifies the user terminal of the result. The user terminal displays the reservation confirmation information.

[0435] The above are the specific processing steps of this system and the specific operations performed in each step.

[0436] (Application example 2)

[0437] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0438] In recent years, the amount of information on tourist spots has become enormous, making it difficult for users to find the tourist spots that suit them. There is also a demand for information provision tailored to user needs, such as multilingual support and facility reservations. However, conventional systems lack the functionality to recommend tourist spots based on the user's emotional state, limiting the user experience. Therefore, there is a need for a system that provides more personalized information and facilitates the reservation process.

[0439] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0440] In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for storing the translated information in a database, means for providing the translated information in response to a search query from a user, means for making facility reservations based on the provided information, and means for recognizing the user's emotional state and recommending tourist spots based on that emotion. This allows users to obtain tourist spot information in multiple languages ​​that matches their emotional state, enabling them to make facility reservations efficiently.

[0441] "Means for collecting tourist spot information" refers to a function that uses web scraping and APIs to collect data such as tourist spot names, addresses, contact information, photos, and reviews from the Internet.

[0442] "Means of analyzing collected information and extracting features and reviews" refers to a function that uses generative AI to analyze collected data on tourist spots and extract key features and important reviews from users.

[0443] "Means for translating extracted information into multiple languages" refers to a function that uses the translation function of generative AI to automatically translate extracted tourist spot information into multiple languages, such as English, Chinese, and Korean.

[0444] The "means for storing translated information in a database" is a function for storing translated tourist spot information in a database so that it can be used for later searching and display.

[0445] "Means for providing translated information in response to a search query from a user" is a function for searching a database for translated information in response to a query about a tourist spot searched by a user and providing it to the user.

[0446] "Means for making facility reservations based on the information provided" is a function that allows users to make reservations for facilities based on the tourist spot information they have viewed, and is a function that receives reservation requests and works in conjunction with the reservation system to complete the reservation.

[0447] "Means for recognizing the user's emotional state and recommending tourist spots based on that emotion" is a function that uses an emotion engine to recognize the user's emotional state from their input and actions, and automatically recommends tourist spots that match those emotions.

[0448] This invention is a system that collects and analyzes tourist spot information and provides it to users in multiple languages. Furthermore, by combining it with an emotion engine, it is possible to recommend and book tourist spots based on the user's emotional state. The hardware and software required to implement this invention are specifically described below.

[0449] Data collection and analysis

[0450] The server collects tourist attraction information using web scraping and APIs. The collected information includes the tourist attraction's name, address, contact information, photos, and user reviews. The collected data is temporarily stored in JSON format and then analyzed using a generative AI model. The analysis process extracts the characteristics of each tourist attraction and important review information.

[0451] Data Translation

[0452] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities, including English, Chinese, and Korean, and the translated information is stored in a database, ready to respond to future search queries.

[0453] Emotion recognition by emotion engine

[0454] When a user searches for a tourist spot, the device receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine analyzes this input and recognizes that the user wants to relax.

[0455] Emotion-based information recommendation

[0456] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[0457] Processing search queries and providing information

[0458] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0459] Facility reservation

[0460] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information.

[0461] Specific examples

[0462] Example 1: Collecting and translating tourist spot information

[0463] The server collects tourist information within the city through web scraping and APIs, extracts the characteristics and important reviews of "famous shrines" using a generative AI model, translates this into English, Chinese, and Korean, and stores it in a database.

[0464] Example 2: User search and sentiment-based facility booking

[0465] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax." Based on the recognized emotion data, the server recommends tourist spots suitable for relaxation (such as hot spring resorts or places with tranquil scenery). When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server, which cooperates with the facility's reservation system to complete the reservation, and then notifies the user's terminal of the results. The user's terminal displays reservation confirmation information.

[0466] Example prompt: "I am looking for a place to relax and unwind."

[0467] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0468] Step 1:

[0469] The server collects tourist attraction information using web scraping and APIs. As input, it requires the URL of the web page containing the tourist attraction and an API endpoint. As output, it obtains tourist attraction data in JSON format, including the name, address, contact information, photos, and reviews.

[0470] Step 2:

[0471] The server analyzes the collected tourist spot data and extracts features and important review information. A generative AI model is used for this analysis. The collected data in JSON format is required as input. The output is the extraction of tourist spot features and important review information. Data processing uses natural language processing technology to analyze the content of the reviews and pick out useful information.

[0472] Step 3:

[0473] The server translates the extracted information into multiple languages, using the translation function of the generative AI model. Features and reviews are required as input. The output is data translated into multiple languages, including English, Chinese, and Korean. Natural language processing is used to process the data and translate it into each language.

[0474] Step 4:

[0475] The server stores the translated information in a database. The input requires information translated in multiple languages. The output is the data stored in the database. The specific operation is a write operation to the database.

[0476] Step 5:

[0477] The device receives a search query from the user. The input requires the tourist spot name and conditions entered by the user. The output is the transmission of the search query to the server. The specific operation involves accepting input through the user interface and sending data to the server.

[0478] Step 6:

[0479] In response to a search query from a user, the server searches the database to retrieve information about the relevant tourist spot. The user's search query is required as input. Multilingual information about the relevant tourist spot is returned as output. Database query operations are performed as data operations.

[0480] Step 7:

[0481] The server sends the acquired information to the user's device. Tourist spot information acquired from the database is required as input. Data is sent to the user's device as output. Specifically, the data is sent via an HTTP response, etc.

[0482] Step 8:

[0483] The terminal receives the response from the server and displays the search results to the user. The tourist spot information sent from the server is required as input. The tourist spot information is displayed on the display screen as output. The specific operation is to update the user interface.

[0484] Step 9:

[0485] When the user checks the tourist attraction information and clicks the reservation button, the device uses an emotion engine to analyze the user's emotional state. The user's search content and input are required as input. The analyzed user's emotional state is obtained as output. An emotion analysis algorithm is applied to the data for calculation.

[0486] Step 10:

[0487] The server recommends optimal tourist spot information based on the emotional data recognized by the emotion engine. The analyzed emotional state and tourist spot data are required as input. The output is generated as recommended tourist spot information that matches the emotional state. Specifically, the server compares the emotional data with the tourist spot data to identify appropriate spots.

[0488] Step 11:

[0489] When the user checks the recommended tourist spot information and submits a reservation request, the terminal sends the reservation request to the server. The input requires the user's confirmation and the operation of the reservation button. The output is the sending of the reservation request to the server. The specific operation involves transmitting a signal from the user interface to the server.

[0490] Step 12:

[0491] The server receives the reservation request and verifies whether the reservation can be made by connecting with the facility's reservation system. The user's reservation request is required as input. The output is a result indicating whether the reservation can be made. The specific operation involves communication with the reservation system.

[0492] Step 13:

[0493] The server sends the reservation success / failure result to the terminal. The success / failure result from the reservation system is required as input. The result is notified to the user terminal as output. The specific operation is to send the data via an HTTP response.

[0494] Step 14:

[0495] The terminal receives the reservation availability result from the server and displays it to the user. The reservation availability result from the server is required as input. The reservation confirmation information is displayed on the user screen as output. The specific operation is to update the user interface.

[0496] These steps allow users to obtain tourist spot information that matches their emotional state and make reservations for facilities efficiently.

[0497] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0498] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0499] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0500] [Second embodiment]

[0501] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0502] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0503] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0504] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0505] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0506] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0507] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0508] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0509] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0510] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0511] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0512] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0513] This invention is a system that collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to easily make reservations for facilities based on that information. The specific program processing of this system is explained below in natural language, with specific examples also included.

[0514] Data collection and analysis

[0515] Subject: Server

[0516] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (such as name, address, and contact information) and user reviews. The collected data is saved in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[0517] Data Translation

[0518] Subject: Server

[0519] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[0520] Processing search queries and providing information

[0521] Subject: User device

[0522] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0523] Facility reservation

[0524] Subject: User device

[0525] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[0526] Specific examples

[0527] Example 1: Collecting and translating tourist spot information

[0528] Subject: Server

[0529] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[0530] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[0531] Translate the extracted information into English, Chinese, and Korean.

[0532] The translation results are stored in a database.

[0533] Example 2: User search and facility reservation

[0534] Subject: User device

[0535] When a user searches for "Sensoji Temple," the request is sent to the server.

[0536] The server searches the database and returns the relevant information to the user terminal.

[0537] The user terminal displays the returned information to the user.

[0538] The user clicks on the reservation button and a reservation request is sent to the server.

[0539] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0540] The user terminal displays the reservation confirmation information.

[0541] The above is a description of a specific embodiment for carrying out the present invention. This system allows foreign tourists to easily obtain information about tourist spots in Japan in multiple languages ​​and makes it possible to smoothly make reservations at facilities.

[0542] The processing flow will be explained below.

[0543] Step 1: Gather information

[0544] Subject: Server

[0545] The server launches a web scraping program and API client for collecting tourist information. Web scraping obtains information on tourist spots in Tokyo from tourism sites and tourism promotion sites. The API client obtains data using the APIs of map services and review sites. The collected information is temporarily saved in JSON format.

[0546] Step 2: Data structuring

[0547] Subject: Server

[0548] The server extracts the necessary basic information (such as name, address, and contact details) from the collected JSON data. It then classifies the data into different categories, such as facility information and review information, and converts it into a format that can be inserted into a database. This structured data is then stored in the database.

[0549] Step 3: Extracting features and reviews

[0550] Subject: Server

[0551] Generative AI is used to extract the characteristics and key reviews of each tourist spot from the stored data. The AI ​​model then uses text analysis techniques to identify and summarize positive and negative points from the reviews.

[0552] Step 4: Translate the information

[0553] Subject: Server

[0554] A translation module is invoked to translate the extracted features and reviews into different languages ​​such as English, Chinese, Korean, etc. The translated information is then stored in a database together with the original Japanese information.

[0555] Step 5: Receiving a user query

[0556] Subject: User device

[0557] A user inputs search keywords to search for tourist attractions, and a search request is sent to the server.

[0558] Step 6: Database Search

[0559] Subject: Server

[0560] The server queries the database based on the received search keywords and retrieves information about the relevant tourist spots, including basic information about the facilities, their features, and translated reviews.

[0561] Step 7: Returning search results

[0562] Subject: Server

[0563] The acquired tourist spot information is converted into a format to be sent back to the user's terminal, and the appropriate translation information is selected based on the user's language settings.

[0564] Step 8: Viewing search results

[0565] Subject: User device

[0566] The user terminal displays the tourist spot information sent from the server, including basic information about the facility, translated features, and reviews.

[0567] Step 9: Submit a booking request

[0568] Subject: User device

[0569] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[0570] Step 10: Reservation Processing

[0571] Subject: Server

[0572] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[0573] Step 11: View your booking confirmation

[0574] Subject: User device

[0575] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[0576] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[0577] Example 1

[0578] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0579] In recent years, the development of the tourism industry has created a demand for multilingual tourist information systems. However, existing systems struggle to effectively integrate the collection, analysis, and translation of tourist spot information, as well as the provision of information and reservation functions to users. Another challenge is improving the accuracy of information collected from multiple sources and provision in multiple languages. This makes it difficult for users to smoothly obtain the information they need, and the reservation process becomes tedious.

[0580] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0581] In this invention, the server includes means for collecting tourist spot information using web scraping and an application program interface, means for analyzing the collected information using a generative artificial intelligence model to extract features and reviews, and means for translating the extracted information into multiple languages ​​using a generative artificial intelligence model. This enables accurate collection, analysis, translation, and provision of tourist spot information in multiple languages. Furthermore, by providing appropriate information in response to search queries from user terminals, receiving facility reservation requests, and processing reservations in cooperation with a reservation management system, users can smoothly obtain information and easily proceed with the reservation process.

[0582] "Tourist attraction information" refers to detailed information such as basic information about places visited by tourists, addresses, contact information, opening hours, access methods, and user reviews.

[0583] "Web scraping" is a technique for automatically collecting data from websites using a program.

[0584] An "Application Program Interface (API)" is a means of providing definitions and protocols for different software applications to communicate with each other.

[0585] A "generative artificial intelligence model" refers to an artificial intelligence technology that uses natural language processing to analyze input data and generate information in a format that humans can understand.

[0586] "Means of collection" refers to the methods and tools used to collect tourist attraction information through web scraping and APIs.

[0587] "Means for analysis" refers to methods and tools for analyzing collected data using a generative artificial intelligence model and extracting its features and word-of-mouth information.

[0588] "Translation means" refers to the methods and tools for converting collected and analyzed information into different languages.

[0589] "Means of storing data in a database" refers to the systems and technologies used to organize and securely store processed information.

[0590] "Means for responding to search queries" refers to methods and tools for retrieving and providing appropriate data in response to a user's search request.

[0591] "Means for receiving facility reservation requests" refers to the methods and tools by which the server receives requests from users to reserve specific facilities.

[0592] "Means for linking with a reservation management system" refers to methods and tools for communicating with an external reservation management system, checking the reservation status of the facility, and confirming reservations.

[0593] This system collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to make reservations for facilities based on that information. Specific embodiments for carrying out the present invention are described below.

[0594] Data collection and analysis

[0595] Subject: Server

[0596] The server uses web scraping technology and application program interfaces (APIs) to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup and Scrapy libraries to retrieve data from the tourist attraction's official website, and also uses public tourist information APIs to obtain additional data. The collected information includes facility name, address, contact information, user reviews, etc., and is saved in JSON format.

[0597] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). During the analysis process, it identifies and structures the characteristics of tourist spots and important review information. For example, the analysis is performed using prompt sentences such as the following:

[0598] "Enter information about Sensoji Temple. Based on this information, we will extract the facility's features and important reviews."

[0599] Data Translation

[0600] Subject: Server

[0601] The extracted information is translated into multiple languages ​​using the translation function of a generative artificial intelligence model (e.g., DeepL Translation API or Google Translation API). Languages ​​to be translated include English, Chinese, and Korean. The translated information includes summaries of the property's features and reviews, and is stored in a database (e.g., PostgreSQL).

[0602] Processing search queries and providing information

[0603] Subject: User device

[0604] When a user searches for a tourist spot, they enter a search query from their device (PC, smartphone) and send it to the server. For example, if a user searches for "Sensoji Temple," the search query is sent to the server. The server searches the database, obtains information on matching tourist spots, and returns it to the user's device. The user's device displays the response received from the server to the user.

[0605] Facility reservation

[0606] Subject: User device

[0607] If the user checks the information about a tourist spot and decides to visit, they click the "Make a reservation" button on their user device. The user device then sends a reservation request to the server. The server then connects with the facility's reservation system (e.g., external reservation management API) to confirm whether the reservation can be made. Once the reservation is confirmed, the result is notified to the user device.

[0608] Specific examples

[0609] Example 1: Collecting and translating tourist spot information

[0610] Subject: Server

[0611] The server collects information about Tokyo's tourist spots through web scraping technology (BeautifulSoup) and a public API (tourist information API).

[0612] Using generative AI (GPT-4), we extract the characteristics and important reviews of Sensoji Temple.

[0613] The extracted information is translated into English, Chinese, and Korean using the DeepL translation API.

[0614] The translation results are stored in a PostgreSQL database.

[0615] Example 2: User search and facility reservation

[0616] Subject: User device

[0617] When a user searches for "Sensoji Temple," the request is sent from the device's web application to the server.

[0618] The server searches the database and returns the relevant information to the user terminal.

[0619] The user terminal displays the returned data on a user interface.

[0620] When the user clicks the "Book Now" button, a reservation request is sent to the server.

[0621] The server connects to an external reservation management API to confirm the reservation for Sensoji Temple.

[0622] The reservation result is notified to the user terminal, and the user receives reservation confirmation information.

[0623] The above is a detailed description of the embodiment of the present invention. This system allows users to obtain information about tourist spots in multiple languages ​​and easily make reservations at facilities.

[0624] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0625] Step 1: Data collection

[0626] Subject: Server

[0627] The server uses web scraping technology and APIs to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup library to retrieve HTML data from the tourist attraction's official website, and the Scrapy library to extract information. It also uses tourist information APIs to obtain additional information such as facility name, address, contact information, and opening hours.

[0628] Input: URL of tourist destination, tourist information API endpoint

[0629] Output: JSON format tourist spot information data

[0630] Specific behavior:

[0631] Use BeautifulSoup to process "https: / / example.com / tourist-spot / asakusa" and extract the necessary information from the HTML data.

[0632] The acquired data is converted into JSON format and prepared for the next analysis process.

[0633] Step 2: Analyze the data

[0634] Subject: Server

[0635] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). Through this analysis process, tourist spot features and important reviews are identified and structured in JSON format.

[0636] Input: JSON format tourist spot information data

[0637] Output: Parsed data in JSON format (features and reviews)

[0638] Specific behavior:

[0639] A prompt is sent to the GPT-4 API saying, "Please extract the features of Sensoji Temple," and the features and reviews are extracted.

[0640] The analysis results are reconstructed into JSON format for the next translation process.

[0641] Step 3: Translate the data

[0642] Subject: Server

[0643] The server translates the parsed information into multiple languages ​​using the DeepL Translation API or Google Translation API. The translated information includes summaries of the property's features and reviews. This information is then stored in a database.

[0644] Input: Parsed data in JSON format

[0645] Output: Multilingual JSON format data

[0646] Specific behavior:

[0647] Translate the Japanese text "Sensoji Temple is a historic temple" into English, Chinese, and Korean using the DeepL Translation API.

[0648] The translation results are compiled in JSON format and each language version is saved in the database.

[0649] Step 4: Saving to the Database

[0650] Subject: Server

[0651] The server stores the translated information in a database by connecting to a PostgreSQL database and inserting the translated data using SQL statements.

[0652] Input: JSON format data translated into multiple languages

[0653] Output: Records in the database

[0654] Specific behavior:

[0655] Connect to the PostgreSQL database and execute the SQL statement "INSERT INTO tourist_spots (name, description_jp, description_en, description_cn, description_kr) VALUES (?, ?, ?, ?, ?)".

[0656] Step 5: Processing the search query

[0657] Subject: User device

[0658] To search for tourist attractions, a user inputs a search query from their device and sends it to the server, which searches the database to obtain matching tourist attraction information and returns it to the user device.

[0659] Input: The search query entered by the user (e.g., "Sensoji Temple")

[0660] Output: Tourist spot information as search results

[0661] Specific behavior:

[0662] A search query for "Sensoji Temple" is entered from the user's device and sent to the server.

[0663] The server searches the database and retrieves the relevant information for "Sensoji Temple"

[0664] Search results are returned to the user's device in JSON format

[0665] Step 6: Viewing information

[0666] Subject: User device

[0667] The user device analyzes the tourist spot information received from the server and displays it on the user interface. The displayed information includes the facility's features, contact information, access methods, reviews, etc.

[0668] Input: Tourist spot information received from the server (JSON format)

[0669] Output: What is displayed on the user interface

[0670] Specific behavior:

[0671] Parse the received JSON data and display it on the UI using React, Vue.js, etc.

[0672] For example, information such as "Name of facility: Sensoji Temple" and "Characteristics: Historic and full of attractions" will be displayed on the screen.

[0673] Step 7: Submit a facility reservation request

[0674] Subject: User device

[0675] If the user is satisfied with the displayed information, he clicks the reservation button to send a reservation request to the server.

[0676] Input: User's booking action (e.g., "Book Sensoji Temple")

[0677] Output: Booking request sent to server

[0678] Specific behavior:

[0679] User clicks the book button

[0680] The React frontend generates a JSON booking request and sends it to the server.

[0681] Step 8: Process facility reservations

[0682] Subject: Server

[0683] The server works in conjunction with an external reservation management system to check whether a reservation can be made, completes the reservation procedure, and notifies the user terminal of the reservation result.

[0684] Input: Reservation request from user (JSON format)

[0685] Output: Reservation result (success or failure)

[0686] Specific behavior:

[0687] The server communicates with an external reservation management API (e.g., Resy API) and attempts to reserve the facility.

[0688] If the reservation is confirmed, a message stating "Reservation completed" is generated and returned to the user's device in JSON format.

[0689] If the reservation fails, an error message will be returned along with the reason.

[0690] The above is the specific processing flow of this system. By combining the detailed operations and inputs / outputs at each step, a comprehensive tourist spot information and reservation system can be realized.

[0691] (Application example 1)

[0692] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0693] Conventional tourist information systems lack multilingual support, making them difficult for foreign tourists to use. In addition, they lack facility reservation and location-based recommendation functions, making it difficult for tourists to plan their trips efficiently.

[0694] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0695] In this invention, the server includes means for collecting tourist attraction information, means for analyzing the collected information and extracting characteristics and rating information, means for translating the extracted information into multiple languages, means for storing the translated information in a data store, means for providing the translated information in response to a search query from a terminal, means for making facility reservations based on the provided information, and means for providing recommended tourist attraction information based on the user's location information. This allows foreign tourists to easily obtain tourist information in multiple languages ​​and efficiently make facility reservations. Furthermore, the recommendation function based on the user's location information allows for smoother travel planning.

[0696] "Tourist attraction information" refers to all information related to tourism, including basic information on tourist destinations, facilities, and famous places, as well as their locations, contact information, and reviews.

[0697] "Means of collection" refers to methods or devices for gathering the required information from the internet or other data sources, such as using web scraping or APIs.

[0698] "Means of analysis" refers to software or algorithms that analyze collected information and extract useful features and word-of-mouth information.

[0699] The "translation means" refers to a translation algorithm or engine that converts the collected and analyzed information into multiple languages.

[0700] A "data store" is a database or storage system for storing collected, analyzed, and translated information.

[0701] "Search query" means a question or request sent by a user through a terminal, which serves as the basis for the server to provide information.

[0702] "Recommended tourist attraction information" is information that the server indicates to the user suitable tourist attractions based on the user's location information and interests.

[0703] The system of the present invention provides tourist attraction information and facility reservations in multiple languages, and is composed of three elements: a server, a terminal, and a user. A specific embodiment of the system is described below.

[0704] Server Processing

[0705] 1. Data Collection:

[0706] The server uses web scraping and APIs to collect basic information about tourist attractions, including their locations, contact details, and ratings from the Internet. This information is stored in JSON format.

[0707] 2. Data Analysis:

[0708] The collected information is then analyzed by a generative AI model, which extracts tourist attraction features and important reviews, summarizing key points and presenting them in a user-friendly format.

[0709] 3. Multilingual Translation:

[0710] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities. The translated information includes summaries of tourist attractions' features and ratings. The translated data is then stored in a data store, ready to respond to future search queries.

[0711] 4. Recommendation function:

[0712] The server recommends suitable tourist spots to users based on their location information and past search history, allowing users to plan their trips efficiently.

[0713] Terminal handling

[0714] 1. Submit a search query:

[0715] When a user searches for a tourist attraction on their device, the search query is sent to the server, which searches the data store to retrieve the relevant tourist attraction information and returns it to the device.

[0716] 2. Information display:

[0717] The terminal displays the tourist attraction information obtained from the server in multiple languages ​​to the user, who can then select a tourist attraction based on the displayed information.

[0718] 3. Facility Reservation:

[0719] If the user is satisfied with the displayed information and would like to visit the tourist attraction, he or she clicks the "Book" button. This click sends a reservation request from the terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the terminal of the result. The terminal then displays reservation confirmation information to the user.

[0720] Hardware and software used

[0721] Hardware: Servers are computer systems with high-performance data processing capabilities. Devices include smartphones and tablets.

[0722] Software: BeautifulSoup and Selenium are used for web scraping. Generative AI models are used for data analysis and multilingual translation. External translation functions such as Google Translate API are also used. SQLite and MySQL are used for data stores.

[0723] Specific examples

[0724] Tourist attraction information collection and translation:

[0725] The server collects and analyzes information about tourist attractions in a city from the web. For example, it extracts the characteristics and important reviews of "Tourist Attraction A" and translates them into English, Chinese, and Korean. The results are stored in a data store.

[0726] User search and facility reservation:

[0727] When a user searches for "tourist attraction A" on a device, the request is sent to the server. The server searches for the relevant information and returns it to the device. When the user confirms the information and clicks the button to make a reservation for the facility, a reservation request is sent to the server. The server completes the reservation procedure and notifies the device of the results.

[0728] Prompt Sentence Examples

[0729] "Please provide tourist information and reviews in English, Chinese, and Korean about tourist attraction A."

[0730] "Translate the tourist information and reviews about sight B into English, Chinese, and Korean."

[0731] As described above, the system of the present invention provides multilingual tourist information and facilitates facility reservations. In addition, the recommendation function based on the user's location information allows users to plan their trips more efficiently.

[0732] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0733] Step 1:

[0734] The server collects tourist attraction information using web scraping and APIs. Specifically, it accesses the specified URL, analyzes the page content using BeautifulSoup and Selenium, and extracts the necessary information (name, address, contact information, reviews, etc.). The input is the URL, and the output is the collected tourist attraction information (in JSON format).

[0735] Step 2:

[0736] The server analyzes the collected tourist attraction information using a generative AI model. Specifically, it extracts and summarizes the tourist attraction's features and important review information. The input is the collected tourist attraction information (JSON format), and the output is the analyzed information (a summary of the features and review information).

[0737] Step 3:

[0738] The server translates the extracted information into multiple languages ​​using the translation function of the generative AI model. Specifically, it translates summaries of tourist attraction features and ratings into English, Chinese, and Korean. The input is the analyzed information, and the output is the information translated into multiple languages.

[0739] Step 4:

[0740] The server stores the translated information in a data store. Specifically, it stores the data in a database system such as SQLite or MySQL. The input is the translated information, and the output is stored in the database.

[0741] Step 5:

[0742] The device collects search queries from users and sends them to the server. Specifically, the user enters the name of a tourist attraction in the device's search bar and presses the search button. The input is the user's search query, and the output is a request sent to the server.

[0743] Step 6:

[0744] The server searches the database in response to the received search query to retrieve information on the relevant tourist attractions. Specifically, the process involves retrieving appropriate translation information from the database. The input is the user's search query, and the output is the retrieved tourist attraction information.

[0745] Step 7:

[0746] The server returns the acquired tourist attraction information to the terminal. Specifically, the process returns the information acquired from the database in JSON format. The input is the acquired tourist attraction information, and the output is the transmission of information to the terminal.

[0747] Step 8:

[0748] The terminal displays the tourist attraction information received from the server to the user. Specifically, this is a process of displaying tourist attraction information in multiple languages ​​on the terminal screen. The input is information from the server, and the output is the information displayed to the user.

[0749] Step 9:

[0750] When the user clicks the reservation button, the terminal sends a reservation request to the server. Specifically, the user indicates their intention to make a reservation by operating the reservation button on the screen. The input is the user's reservation instruction, and the output is the transmission of a reservation request to the server.

[0751] Step 10:

[0752] The server communicates with the facility's reservation system based on the received reservation request to confirm whether the reservation can be made. Specifically, this process works in conjunction with the reservation system API to carry out the reservation procedure. The input is the reservation request, and the output is the reservation confirmation result.

[0753] Step 11:

[0754] The server notifies the terminal of the reservation confirmation result. Specifically, if the reservation is successful, it sends detailed information to the terminal. The input is the reservation confirmation result, and the output is a notification to the terminal.

[0755] Step 12:

[0756] The terminal displays the reservation confirmation information received from the server to the user. Specifically, this process displays a message on the terminal screen indicating that the reservation was successful and provides detailed information. The input is the reservation confirmation information from the server, and the output is the display of the reservation confirmation information to the user.

[0757] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0758] This invention is a system that collects, analyzes, and translates tourist spot information and provides it to users in multiple languages, and also combines it with an emotion engine to recommend and book tourist spots based on the user's emotional state. The specific program processing of this system is explained below in natural language, with specific examples also included.

[0759] Data collection and analysis

[0760] Subject: Server

[0761] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (name, address, contact information, etc.) and user reviews. The collected data is temporarily stored in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[0762] Data Translation

[0763] Subject: Server

[0764] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[0765] Emotion recognition by emotion engine

[0766] Subject: User device

[0767] When a user searches for a tourist spot, the user terminal receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine recognizes that the user wants to relax.

[0768] Emotion-based information recommendation

[0769] Subject: Server

[0770] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[0771] Processing search queries and providing information

[0772] Subject: User device

[0773] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0774] Facility reservation

[0775] Subject: User device

[0776] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[0777] Specific examples

[0778] Example 1: Collecting and translating tourist spot information

[0779] Subject: Server

[0780] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[0781] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[0782] Translate the extracted information into English, Chinese, and Korean.

[0783] The translation results are stored in a database.

[0784] Example 2: User search and sentiment-based facility booking

[0785] Subject: User device

[0786] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax."

[0787] The server recommends tourist spots suitable for relaxation (e.g., hot springs or tranquil scenic spots) based on the recognized emotion data.

[0788] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[0789] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0790] The user terminal displays the reservation confirmation information.

[0791] The system of the present invention can significantly improve the user experience by recognizing the user's emotions and providing optimal tourist spot information based on those emotions. The above is a description of specific embodiments for carrying out the present invention.

[0792] The processing flow will be explained below.

[0793] Step 1: Gather information

[0794] Subject: Server

[0795] The server launches a web scraping program and API client for collecting tourist information. This allows it to obtain tourist spot information from tourism and promotional sites. The collected information includes basic facility information (name, address, contact information, etc.) and user reviews. The obtained data is temporarily saved in JSON format.

[0796] Step 2: Data structuring

[0797] Subject: Server

[0798] The server extracts the necessary basic information from the collected JSON data. Specifically, it extracts data such as facility name, address, contact information, opening hours, and fees. Next, it organizes the extracted data by tourist spot and converts it into a format that can be inserted into a database. The structured data is then saved in the database.

[0799] Step 3: Extracting features and reviews

[0800] Subject: Server

[0801] The server uses generative AI to extract the characteristics and important reviews of each tourist spot from the stored data. The generative AI then uses natural language processing technology to analyze the reviews and summarise the positive and negative points. The extracted characteristics and reviews are then passed on to the next processing step.

[0802] Step 4: Translate the information

[0803] Subject: Server

[0804] The extracted features and review information are translated into multiple languages. The server calls a generative AI translation module to translate the information into English, Chinese, Korean, etc. The translated information is then stored in a database along with the original Japanese information.

[0805] Step 5: Acquire and analyze emotion data

[0806] Subject: User device

[0807] When a user searches for a tourist spot, the user's device collects the user's input data and emotional information such as audio and video in real time. The emotion engine analyzes this collected data and recognizes the user's current emotional state. For example, the emotion "I want to relax" can be read from the user's facial expression.

[0808] Step 6: Emotion-based information recommendation

[0809] Subject: Server

[0810] Based on the emotion data recognized by the emotion engine, the server recommends the most suitable tourist spot information to the user. For example, if the user is recognized as wanting to "relax," the server will search the database for relaxing tourist spots such as tranquil landscapes and hot springs, and generate a recommendation list.

[0811] Step 7: Receiving and processing a search query

[0812] Subject: User device

[0813] A user enters keywords to search for tourist attractions. The user's search query is sent to a server, which also includes data about the user's current emotional state.

[0814] Step 8: Retrieving and returning search results

[0815] Subject: Server

[0816] The server queries the database based on the user's search query and emotion data to retrieve relevant tourist spot information. The retrieved information includes basic facility information, features, translated reviews, and recommendation reasons based on the user's emotion. The retrieved information is then organized and returned to the user's device.

[0817] Step 9: Viewing search results

[0818] Subject: User device

[0819] The user's device displays the tourist spot information sent from the server, including basic facility information, translated features, reviews, and emotion-based recommendations.

[0820] Step 10: Submit a booking request

[0821] Subject: User device

[0822] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[0823] Step 11: Reservation Processing

[0824] Subject: Server

[0825] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[0826] Step 12: View your booking confirmation

[0827] Subject: User device

[0828] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[0829] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[0830] Example 2

[0831] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0832] In recent years, with the development of the global tourism industry, there has been an increasing demand for tourist spot information accessible in multiple languages. However, there is a lack of systems that provide personalized information and reservation functions based on the user's emotional state, and there is a need to improve the user experience. Conventional systems have issues with language barriers and a lack of personalization functions when providing tourist spot information, making it difficult for users to select the optimal tourist spot that matches their emotional state. Therefore, a system that can efficiently recommend and reserve tourist spots based on the user's emotional state is needed.

[0833] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for saving the translated information in a database, means for analyzing data input by a user and recognizing an emotional state, means for recommending tourist spot information based on the recognized emotional state, means for providing translated information in response to a search query from a user, and means for making reservations for facilities based on the provided information. This makes it possible to provide tourist spot information and make reservations that are optimal for the user's emotional state.

[0834] "Tourist attraction information" refers to information such as the name, address, contact information, characteristics, and reviews of specific tourist spots and facilities.

[0835] "Means of collection" refers to web scraping tools and APIs used to obtain tourist spot information from the Internet.

[0836] The "analysis means" refers to generative AI models and text analysis tools that process the collected tourist spot information and extract features and important review information.

[0837] "Means for translating into multiple languages" refers to a machine translation API for translating collected and analyzed information into other languages.

[0838] "Means for storing in a database" refers to a storage system or database management system used to efficiently manage the analyzed and translated information.

[0839] The "means for analyzing user input data" refers to an emotion engine or text analysis tool that analyzes text input from a user and recognizes their emotional state.

[0840] The "means for recognizing emotional states" refers to generative AI models and sentiment analysis APIs for analyzing emotions from user text input.

[0841] The "means for providing translated information" refers to a search engine or display tool that retrieves and displays translated information in response to a user's search query.

[0842] "Means for recommending tourist spot information" refers to an algorithm or recommendation engine that selects and recommends the most appropriate tourist spot information based on the user's emotional state.

[0843] The "means of making facility reservations" refers to an online reservation system or API that works in conjunction with the tourist spot reservation system to execute and manage reservations.

[0844] The present invention provides a system for collecting, analyzing, and translating tourist spot information, and for recommending and reserving tourist spots based on the user's emotional state. The following describes in detail an embodiment of the system.

[0845] The system consists of a server, a user terminal, and multiple software modules. The server is the main component responsible for collecting, analyzing, translating, storing, and recommending tourist attraction information. The user terminal is a device used by users to access the system, such as a desktop computer, laptop, or smartphone.

[0846] Data collection

[0847] The server uses Python's Beautiful Soup and Scrapy libraries to collect information about tourist spots on the Internet through web scraping. It also calls tourist information APIs (such as the Google Places API) to obtain basic information about tourist facilities and user reviews. The collected data is temporarily stored in JSON format.

[0848] Data analysis

[0849] The collected JSON-formatted data is analyzed using a generative AI model (e.g., GPT-4). During this analysis process, the text data is preprocessed using Python's NLTK library to extract the characteristics of each tourist spot and important review information. This preprocessing step includes tokenization and stop word removal.

[0850] Data Translation

[0851] The resulting information is then translated into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL, ready to respond to future search queries.

[0852] User Input and Emotion Recognition

[0853] The user device provides a text input interface and captures the data entered in real time when the user searches for tourist attractions. This input data is analyzed using IBM Watson's sentiment analysis API to recognize the user's current emotional state. For example, if a user searches for "places to relax," this data is recognized as the emotional state of "wanting to relax."

[0854] information recommendation

[0855] The server then recommends the most suitable tourist spot information based on the user's emotional state. For example, if a user has an emotional state indicating a desire to relax, quiet scenery or hot springs will be recommended. This process is realized using a recommendation engine.

[0856] Processing search queries

[0857] When a user searches for a specific tourist spot name (for example, "Sensoji Temple"), the query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and returns it to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0858] Facility reservation

[0859] If the user is satisfied with the displayed information and would like to visit the tourist spot, he or she clicks the "Book" button. This sends a reservation request to the server. The server communicates with the facility's reservation system (e.g., AWS RDS) to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal displays reservation confirmation information.

[0860] Specific examples

[0861] Example 1: Collecting and translating tourist spot information

[0862] Example of server behavior:

[0863] The server collects information about tourist spots in Tokyo through web scraping (using Beautiful Soup) and an API (tourist information API).

[0864] Using GPT-4, we extract the characteristics and important reviews of Sensoji Temple.

[0865] The extracted information is translated into English, Chinese, and Korean using the Google Translate API.

[0866] The translation results are stored in a MySQL database.

[0867] Example 2: User search and sentiment-based facility booking

[0868] Example of user terminal behavior:

[0869] When a user searches for "places to relax," the input data is analyzed by an emotion engine (IBM Watson API), and the user's emotion is recognized as "I want to relax."

[0870] The server recommends tourist spots suitable for relaxation (e.g., hot springs, places with tranquil scenery) based on the recognized emotion data.

[0871] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[0872] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[0873] The user terminal displays the reservation confirmation information.

[0874] By implementing the above steps, the system of the present invention can efficiently provide tourist spot information and make reservations that match the user's emotional state, thereby improving the user experience.

[0875] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0876] Step 1: Data collection

[0877] The server uses Python's Beautiful Soup and Scrapy libraries to collect tourist attraction information. It accesses tourist information websites and APIs (e.g., tourist information APIs) on the Internet to obtain tourist attraction names, addresses, contact information, and user reviews. This data is temporarily saved in JSON format.

[0878] Input: URL of tourist information site, API endpoint.

[0879] Output: Tourist spot information data in JSON format.

[0880] Specific operation: The server accesses "https: / / example.com / tourist-spots", extracts the tourist spot name, address, and contact information from the HTML using Beautiful Soup, and retrieves user reviews via the API. This data is temporarily stored in JSON format.

[0881] Step 2: Data analysis

[0882] The server analyzes the collected JSON-formatted data using a generative AI model (e.g., GPT-4). During the analysis process, the characteristics of each tourist spot and important review information are extracted. During this process, the NLTK library in Python is used to preprocess the text data (e.g., tokenize and remove stop words).

[0883] Input: Temporarily saved tourist spot information data in JSON format.

[0884] Output: Parsed feature information and important reviews.

[0885] How it works: The server loads the JSON data and uses NLTK to preprocess the text data, then uses a generative AI model (GPT-4) to extract tourist attraction features and important review information.

[0886] Step 3: Data Translation

[0887] The server translates the information obtained from the analysis into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL.

[0888] Input: Parsed feature information and important reviews.

[0889] Output: Tourist spot information translated into multiple languages.

[0890] Specific operation: The server sends the analysis results to the Google Translate API and translates them into English, Chinese, Korean, etc. The translation results are then stored in the database.

[0891] Step 4: Getting User Input and Emotion Recognition

[0892] When users search for tourist attractions, their devices capture text input in real time, which is then analyzed using IBM Watson's sentiment analysis API to recognize the user's emotional state.

[0893] Input: User's search query (e.g. "places to relax").

[0894] Output: The perceived emotional state of the user (e.g., "I want to relax").

[0895] Specific operation: The user device receives the input "place to relax" from the text input field, sends it to the IBM Watson API, and receives the sentiment analysis results.

[0896] Step 5: Information recommendation

[0897] The server recommends optimal tourist spot information based on the recognized emotional state, selects tourist spots suitable for the emotional state using a recommendation engine, and provides the recommended information to the user terminal.

[0898] Input: The user's perceived emotional state (e.g., "I want to relax").

[0899] Output: Recommendation information of tourist spots based on emotional state.

[0900] Specific operation: The server searches the database for tourist spots that match the emotional state of "wanting to relax" and sends the most appropriate information to the user's terminal.

[0901] Step 6: Processing the search query

[0902] When a user searches for a specific tourist spot name, the query is sent to the server, which searches the database to retrieve information about the relevant tourist spot and returns it to the user's device.

[0903] Input: User's search query (e.g. "Sensoji Temple").

[0904] Output: Detailed information about the tourist spot.

[0905] Specific operation: The user device sends the search query "Sensoji Temple" to the server. The server searches the database, obtains information about "Sensoji Temple," and sends it to the user device.

[0906] Step 7: Facility reservation

[0907] If the user is satisfied with the displayed information and clicks the "Reserve" button, a reservation request is sent to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible and notifies the user terminal of the result.

[0908] Input: The user's booking request.

[0909] Output: Confirmed booking information.

[0910] Specific operation: When the user clicks the reservation button, a reservation request is sent to the server. The server communicates with the reservation system to confirm whether the reservation can be made and notifies the user terminal of the result. The user terminal displays the reservation confirmation information.

[0911] The above are the specific processing steps of this system and the specific operations performed in each step.

[0912] (Application example 2)

[0913] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0914] In recent years, the amount of information on tourist spots has become enormous, making it difficult for users to find the tourist spots that suit them. There is also a demand for information provision tailored to user needs, such as multilingual support and facility reservations. However, conventional systems lack the functionality to recommend tourist spots based on the user's emotional state, limiting the user experience. Therefore, there is a need for a system that provides more personalized information and facilitates the reservation process.

[0915] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0916] In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for storing the translated information in a database, means for providing the translated information in response to a search query from a user, means for making facility reservations based on the provided information, and means for recognizing the user's emotional state and recommending tourist spots based on that emotion. This allows users to obtain tourist spot information in multiple languages ​​that matches their emotional state, enabling them to make facility reservations efficiently.

[0917] "Means for collecting tourist spot information" refers to a function that uses web scraping and APIs to collect data such as tourist spot names, addresses, contact information, photos, and reviews from the Internet.

[0918] "Means of analyzing collected information and extracting features and reviews" refers to a function that uses generative AI to analyze collected data on tourist spots and extract key features and important reviews from users.

[0919] "Means for translating extracted information into multiple languages" refers to a function that uses the translation function of generative AI to automatically translate extracted tourist spot information into multiple languages, such as English, Chinese, and Korean.

[0920] The "means for storing translated information in a database" is a function for storing translated tourist spot information in a database so that it can be used for later searching and display.

[0921] "Means for providing translated information in response to a search query from a user" is a function for searching a database for translated information in response to a query about a tourist spot searched by a user and providing it to the user.

[0922] "Means for making facility reservations based on the information provided" is a function that allows users to make reservations for facilities based on the tourist spot information they have viewed, and is a function that receives reservation requests and works in conjunction with the reservation system to complete the reservation.

[0923] "Means for recognizing the user's emotional state and recommending tourist spots based on that emotion" is a function that uses an emotion engine to recognize the user's emotional state from their input and actions, and automatically recommends tourist spots that match those emotions.

[0924] This invention is a system that collects and analyzes tourist spot information and provides it to users in multiple languages. Furthermore, by combining it with an emotion engine, it is possible to recommend and book tourist spots based on the user's emotional state. The hardware and software required to implement this invention are specifically described below.

[0925] Data collection and analysis

[0926] The server collects tourist attraction information using web scraping and APIs. The collected information includes the tourist attraction's name, address, contact information, photos, and user reviews. The collected data is temporarily stored in JSON format and then analyzed using a generative AI model. The analysis process extracts the characteristics of each tourist attraction and important review information.

[0927] Data Translation

[0928] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities, including English, Chinese, and Korean, and the translated information is stored in a database, ready to respond to future search queries.

[0929] Emotion recognition by emotion engine

[0930] When a user searches for a tourist spot, the device receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine analyzes this input and recognizes that the user wants to relax.

[0931] Emotion-based information recommendation

[0932] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[0933] Processing search queries and providing information

[0934] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0935] Facility reservation

[0936] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information.

[0937] Specific examples

[0938] Example 1: Collecting and translating tourist spot information

[0939] The server collects tourist information within the city through web scraping and APIs, extracts the characteristics and important reviews of "famous shrines" using a generative AI model, translates this into English, Chinese, and Korean, and stores it in a database.

[0940] Example 2: User search and sentiment-based facility booking

[0941] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax." Based on the recognized emotion data, the server recommends tourist spots suitable for relaxation (such as hot spring resorts or places with tranquil scenery). When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server, which cooperates with the facility's reservation system to complete the reservation, and then notifies the user's terminal of the results. The user's terminal displays reservation confirmation information.

[0942] Example prompt: "I am looking for a place to relax and unwind."

[0943] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0944] Step 1:

[0945] The server collects tourist attraction information using web scraping and APIs. As input, it requires the URL of the web page containing the tourist attraction and an API endpoint. As output, it obtains tourist attraction data in JSON format, including the name, address, contact information, photos, and reviews.

[0946] Step 2:

[0947] The server analyzes the collected tourist spot data and extracts features and important review information. A generative AI model is used for this analysis. The collected data in JSON format is required as input. The output is the extraction of tourist spot features and important review information. Data processing uses natural language processing technology to analyze the content of the reviews and pick out useful information.

[0948] Step 3:

[0949] The server translates the extracted information into multiple languages, using the translation function of the generative AI model. Features and reviews are required as input. The output is data translated into multiple languages, including English, Chinese, and Korean. Natural language processing is used to process the data and translate it into each language.

[0950] Step 4:

[0951] The server stores the translated information in a database. The input requires information translated in multiple languages. The output is the data stored in the database. The specific operation is a write operation to the database.

[0952] Step 5:

[0953] The device receives a search query from the user. The input requires the tourist spot name and conditions entered by the user. The output is the transmission of the search query to the server. The specific operation involves accepting input through the user interface and sending data to the server.

[0954] Step 6:

[0955] In response to a search query from a user, the server searches the database to retrieve information about the relevant tourist spot. The user's search query is required as input. Multilingual information about the relevant tourist spot is returned as output. Database query operations are performed as data operations.

[0956] Step 7:

[0957] The server sends the acquired information to the user's device. Tourist spot information acquired from the database is required as input. Data is sent to the user's device as output. Specifically, the data is sent via an HTTP response, etc.

[0958] Step 8:

[0959] The terminal receives the response from the server and displays the search results to the user. The tourist spot information sent from the server is required as input. The tourist spot information is displayed on the display screen as output. The specific operation is to update the user interface.

[0960] Step 9:

[0961] When the user checks the tourist attraction information and clicks the reservation button, the device uses an emotion engine to analyze the user's emotional state. The user's search content and input are required as input. The analyzed user's emotional state is obtained as output. An emotion analysis algorithm is applied to the data for calculation.

[0962] Step 10:

[0963] The server recommends optimal tourist spot information based on the emotional data recognized by the emotion engine. The analyzed emotional state and tourist spot data are required as input. The output is generated as recommended tourist spot information that matches the emotional state. Specifically, the server compares the emotional data with the tourist spot data to identify appropriate spots.

[0964] Step 11:

[0965] When the user checks the recommended tourist spot information and submits a reservation request, the terminal sends the reservation request to the server. The input requires the user's confirmation and the operation of the reservation button. The output is the sending of the reservation request to the server. The specific operation involves transmitting a signal from the user interface to the server.

[0966] Step 12:

[0967] The server receives the reservation request and verifies whether the reservation can be made by connecting with the facility's reservation system. The user's reservation request is required as input. The output is a result indicating whether the reservation can be made. The specific operation involves communication with the reservation system.

[0968] Step 13:

[0969] The server sends the reservation success / failure result to the terminal. The success / failure result from the reservation system is required as input. The result is notified to the user terminal as output. The specific operation is to send the data via an HTTP response.

[0970] Step 14:

[0971] The terminal receives the reservation availability result from the server and displays it to the user. The reservation availability result from the server is required as input. The reservation confirmation information is displayed on the user screen as output. The specific operation is to update the user interface.

[0972] These steps allow users to obtain tourist spot information that matches their emotional state and make reservations for facilities efficiently.

[0973] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0974] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0975] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0976] [Third embodiment]

[0977] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0978] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0979] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0980] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0981] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0982] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0983] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0984] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0985] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0986] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0987] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0988] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0989] This invention is a system that collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to easily make reservations for facilities based on that information. The specific program processing of this system is explained below in natural language, with specific examples also included.

[0990] Data collection and analysis

[0991] Subject: Server

[0992] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (such as name, address, and contact information) and user reviews. The collected data is saved in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[0993] Data Translation

[0994] Subject: Server

[0995] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[0996] Processing search queries and providing information

[0997] Subject: User device

[0998] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[0999] Facility reservation

[1000] Subject: User device

[1001] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[1002] Specific examples

[1003] Example 1: Collecting and translating tourist spot information

[1004] Subject: Server

[1005] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[1006] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[1007] Translate the extracted information into English, Chinese, and Korean.

[1008] The translation results are stored in a database.

[1009] Example 2: User search and facility reservation

[1010] Subject: User device

[1011] When a user searches for "Sensoji Temple," the request is sent to the server.

[1012] The server searches the database and returns the relevant information to the user terminal.

[1013] The user terminal displays the returned information to the user.

[1014] The user clicks on the reservation button and a reservation request is sent to the server.

[1015] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1016] The user terminal displays the reservation confirmation information.

[1017] The above is a description of a specific embodiment for carrying out the present invention. This system allows foreign tourists to easily obtain information about tourist spots in Japan in multiple languages ​​and makes it possible to smoothly make reservations at facilities.

[1018] The processing flow will be explained below.

[1019] Step 1: Gather information

[1020] Subject: Server

[1021] The server launches a web scraping program and API client for collecting tourist information. Web scraping obtains information on tourist spots in Tokyo from tourism sites and tourism promotion sites. The API client obtains data using the APIs of map services and review sites. The collected information is temporarily saved in JSON format.

[1022] Step 2: Data structuring

[1023] Subject: Server

[1024] The server extracts the necessary basic information (such as name, address, and contact details) from the collected JSON data. It then classifies the data into different categories, such as facility information and review information, and converts it into a format that can be inserted into a database. This structured data is then stored in the database.

[1025] Step 3: Extracting features and reviews

[1026] Subject: Server

[1027] Generative AI is used to extract the characteristics and key reviews of each tourist spot from the stored data. The AI ​​model then uses text analysis techniques to identify and summarize positive and negative points from the reviews.

[1028] Step 4: Translate the information

[1029] Subject: Server

[1030] A translation module is invoked to translate the extracted features and reviews into different languages ​​such as English, Chinese, Korean, etc. The translated information is then stored in a database together with the original Japanese information.

[1031] Step 5: Receiving a user query

[1032] Subject: User device

[1033] A user inputs search keywords to search for tourist attractions, and a search request is sent to the server.

[1034] Step 6: Database Search

[1035] Subject: Server

[1036] The server queries the database based on the received search keywords and retrieves information about the relevant tourist spots, including basic information about the facilities, their features, and translated reviews.

[1037] Step 7: Returning search results

[1038] Subject: Server

[1039] The acquired tourist spot information is converted into a format to be sent back to the user's terminal, and the appropriate translation information is selected based on the user's language settings.

[1040] Step 8: Viewing search results

[1041] Subject: User device

[1042] The user terminal displays the tourist spot information sent from the server, including basic information about the facility, translated features, and reviews.

[1043] Step 9: Submit a booking request

[1044] Subject: User device

[1045] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[1046] Step 10: Reservation Processing

[1047] Subject: Server

[1048] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[1049] Step 11: View your booking confirmation

[1050] Subject: User device

[1051] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[1052] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[1053] Example 1

[1054] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1055] In recent years, the development of the tourism industry has created a demand for multilingual tourist information systems. However, existing systems struggle to effectively integrate the collection, analysis, and translation of tourist spot information, as well as the provision of information and reservation functions to users. Another challenge is improving the accuracy of information collected from multiple sources and provision in multiple languages. This makes it difficult for users to smoothly obtain the information they need, and the reservation process becomes tedious.

[1056] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1057] In this invention, the server includes means for collecting tourist spot information using web scraping and an application program interface, means for analyzing the collected information using a generative artificial intelligence model to extract features and reviews, and means for translating the extracted information into multiple languages ​​using a generative artificial intelligence model. This enables accurate collection, analysis, translation, and provision of tourist spot information in multiple languages. Furthermore, by providing appropriate information in response to search queries from user terminals, receiving facility reservation requests, and processing reservations in cooperation with a reservation management system, users can smoothly obtain information and easily proceed with the reservation process.

[1058] "Tourist attraction information" refers to detailed information such as basic information about places visited by tourists, addresses, contact information, opening hours, access methods, and user reviews.

[1059] "Web scraping" is a technique for automatically collecting data from websites using a program.

[1060] An "Application Program Interface (API)" is a means of providing definitions and protocols for different software applications to communicate with each other.

[1061] A "generative artificial intelligence model" refers to an artificial intelligence technology that uses natural language processing to analyze input data and generate information in a format that humans can understand.

[1062] "Means of collection" refers to the methods and tools used to collect tourist attraction information through web scraping and APIs.

[1063] "Means for analysis" refers to methods and tools for analyzing collected data using a generative artificial intelligence model and extracting its features and word-of-mouth information.

[1064] "Translation means" refers to the methods and tools for converting collected and analyzed information into different languages.

[1065] "Means of storing data in a database" refers to the systems and technologies used to organize and securely store processed information.

[1066] "Means for responding to search queries" refers to methods and tools for retrieving and providing appropriate data in response to a user's search request.

[1067] "Means for receiving facility reservation requests" refers to the methods and tools by which the server receives requests from users to reserve specific facilities.

[1068] "Means for linking with a reservation management system" refers to methods and tools for communicating with an external reservation management system, checking the reservation status of the facility, and confirming reservations.

[1069] This system collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to make reservations for facilities based on that information. Specific embodiments for carrying out the present invention are described below.

[1070] Data collection and analysis

[1071] Subject: Server

[1072] The server uses web scraping technology and application program interfaces (APIs) to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup and Scrapy libraries to retrieve data from the tourist attraction's official website, and also uses public tourist information APIs to obtain additional data. The collected information includes facility name, address, contact information, user reviews, etc., and is saved in JSON format.

[1073] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). During the analysis process, it identifies and structures the characteristics of tourist spots and important review information. For example, the analysis is performed using prompt sentences such as the following:

[1074] "Enter information about Sensoji Temple. Based on this information, we will extract the facility's features and important reviews."

[1075] Data Translation

[1076] Subject: Server

[1077] The extracted information is translated into multiple languages ​​using the translation function of a generative artificial intelligence model (e.g., DeepL Translation API or Google Translation API). Languages ​​to be translated include English, Chinese, and Korean. The translated information includes summaries of the property's features and reviews, and is stored in a database (e.g., PostgreSQL).

[1078] Processing search queries and providing information

[1079] Subject: User device

[1080] When a user searches for a tourist spot, they enter a search query from their device (PC, smartphone) and send it to the server. For example, if a user searches for "Sensoji Temple," the search query is sent to the server. The server searches the database, obtains information on matching tourist spots, and returns it to the user's device. The user's device displays the response received from the server to the user.

[1081] Facility reservation

[1082] Subject: User device

[1083] If the user checks the information about a tourist spot and decides to visit, they click the "Make a reservation" button on their user device. The user device then sends a reservation request to the server. The server then connects with the facility's reservation system (e.g., external reservation management API) to confirm whether the reservation can be made. Once the reservation is confirmed, the result is notified to the user device.

[1084] Specific examples

[1085] Example 1: Collecting and translating tourist spot information

[1086] Subject: Server

[1087] The server collects information about Tokyo's tourist spots through web scraping technology (BeautifulSoup) and a public API (tourist information API).

[1088] Using generative AI (GPT-4), we extract the characteristics and important reviews of Sensoji Temple.

[1089] The extracted information is translated into English, Chinese, and Korean using the DeepL translation API.

[1090] The translation results are stored in a PostgreSQL database.

[1091] Example 2: User search and facility reservation

[1092] Subject: User device

[1093] When a user searches for "Sensoji Temple," the request is sent from the device's web application to the server.

[1094] The server searches the database and returns the relevant information to the user terminal.

[1095] The user terminal displays the returned data on a user interface.

[1096] When the user clicks the "Book Now" button, a reservation request is sent to the server.

[1097] The server connects to an external reservation management API to confirm the reservation for Sensoji Temple.

[1098] The reservation result is notified to the user terminal, and the user receives reservation confirmation information.

[1099] The above is a detailed description of the embodiment of the present invention. This system allows users to obtain information about tourist spots in multiple languages ​​and easily make reservations at facilities.

[1100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1101] Step 1: Data collection

[1102] Subject: Server

[1103] The server uses web scraping technology and APIs to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup library to retrieve HTML data from the tourist attraction's official website, and the Scrapy library to extract information. It also uses tourist information APIs to obtain additional information such as facility name, address, contact information, and opening hours.

[1104] Input: URL of tourist destination, tourist information API endpoint

[1105] Output: JSON format tourist spot information data

[1106] Specific behavior:

[1107] Use BeautifulSoup to process "https: / / example.com / tourist-spot / asakusa" and extract the necessary information from the HTML data.

[1108] The acquired data is converted into JSON format and prepared for the next analysis process.

[1109] Step 2: Analyze the data

[1110] Subject: Server

[1111] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). Through this analysis process, tourist spot features and important reviews are identified and structured in JSON format.

[1112] Input: JSON format tourist spot information data

[1113] Output: Parsed data in JSON format (features and reviews)

[1114] Specific behavior:

[1115] A prompt is sent to the GPT-4 API saying, "Please extract the features of Sensoji Temple," and the features and reviews are extracted.

[1116] The analysis results are reconstructed into JSON format for the next translation process.

[1117] Step 3: Translate the data

[1118] Subject: Server

[1119] The server translates the parsed information into multiple languages ​​using the DeepL Translation API or Google Translation API. The translated information includes summaries of the property's features and reviews. This information is then stored in a database.

[1120] Input: Parsed data in JSON format

[1121] Output: Multilingual JSON format data

[1122] Specific behavior:

[1123] Translate the Japanese text "Sensoji Temple is a historic temple" into English, Chinese, and Korean using the DeepL Translation API.

[1124] The translation results are compiled in JSON format and each language version is saved in the database.

[1125] Step 4: Saving to the Database

[1126] Subject: Server

[1127] The server stores the translated information in a database by connecting to a PostgreSQL database and inserting the translated data using SQL statements.

[1128] Input: JSON format data translated into multiple languages

[1129] Output: Records in the database

[1130] Specific behavior:

[1131] Connect to the PostgreSQL database and execute the SQL statement "INSERT INTO tourist_spots (name, description_jp, description_en, description_cn, description_kr) VALUES (?, ?, ?, ?, ?)".

[1132] Step 5: Processing the search query

[1133] Subject: User device

[1134] To search for tourist attractions, a user inputs a search query from their device and sends it to the server, which searches the database to obtain matching tourist attraction information and returns it to the user device.

[1135] Input: The search query entered by the user (e.g., "Sensoji Temple")

[1136] Output: Tourist spot information as search results

[1137] Specific behavior:

[1138] A search query for "Sensoji Temple" is entered from the user's device and sent to the server.

[1139] The server searches the database and retrieves the relevant information for "Sensoji Temple"

[1140] Search results are returned to the user's device in JSON format

[1141] Step 6: Viewing information

[1142] Subject: User device

[1143] The user device analyzes the tourist spot information received from the server and displays it on the user interface. The displayed information includes the facility's features, contact information, access methods, reviews, etc.

[1144] Input: Tourist spot information received from the server (JSON format)

[1145] Output: What is displayed on the user interface

[1146] Specific behavior:

[1147] Parse the received JSON data and display it on the UI using React, Vue.js, etc.

[1148] For example, information such as "Name of facility: Sensoji Temple" and "Characteristics: Historic and full of attractions" will be displayed on the screen.

[1149] Step 7: Submit a facility reservation request

[1150] Subject: User device

[1151] If the user is satisfied with the displayed information, he clicks the reservation button to send a reservation request to the server.

[1152] Input: User's booking action (e.g., "Book Sensoji Temple")

[1153] Output: Booking request sent to server

[1154] Specific behavior:

[1155] User clicks the book button

[1156] The React frontend generates a JSON booking request and sends it to the server.

[1157] Step 8: Process facility reservations

[1158] Subject: Server

[1159] The server works in conjunction with an external reservation management system to check whether a reservation can be made, completes the reservation procedure, and notifies the user terminal of the reservation result.

[1160] Input: Reservation request from user (JSON format)

[1161] Output: Reservation result (success or failure)

[1162] Specific behavior:

[1163] The server communicates with an external reservation management API (e.g., Resy API) and attempts to reserve the facility.

[1164] If the reservation is confirmed, a message stating "Reservation completed" is generated and returned to the user's device in JSON format.

[1165] If the reservation fails, an error message will be returned along with the reason.

[1166] The above is the specific processing flow of this system. By combining the detailed operations and inputs / outputs at each step, a comprehensive tourist spot information and reservation system can be realized.

[1167] (Application example 1)

[1168] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1169] Conventional tourist information systems lack multilingual support, making them difficult for foreign tourists to use. In addition, they lack facility reservation and location-based recommendation functions, making it difficult for tourists to plan their trips efficiently.

[1170] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1171] In this invention, the server includes means for collecting tourist attraction information, means for analyzing the collected information and extracting characteristics and rating information, means for translating the extracted information into multiple languages, means for storing the translated information in a data store, means for providing the translated information in response to a search query from a terminal, means for making facility reservations based on the provided information, and means for providing recommended tourist attraction information based on the user's location information. This allows foreign tourists to easily obtain tourist information in multiple languages ​​and efficiently make facility reservations. Furthermore, the recommendation function based on the user's location information allows for smoother travel planning.

[1172] "Tourist attraction information" refers to all information related to tourism, including basic information on tourist destinations, facilities, and famous places, as well as their locations, contact information, and reviews.

[1173] "Means of collection" refers to methods or devices for gathering the required information from the internet or other data sources, such as using web scraping or APIs.

[1174] "Means of analysis" refers to software or algorithms that analyze collected information and extract useful features and word-of-mouth information.

[1175] The "translation means" refers to a translation algorithm or engine that converts the collected and analyzed information into multiple languages.

[1176] A "data store" is a database or storage system for storing collected, analyzed, and translated information.

[1177] "Search query" means a question or request sent by a user through a terminal, which serves as the basis for the server to provide information.

[1178] "Recommended tourist attraction information" is information that the server indicates to the user suitable tourist attractions based on the user's location information and interests.

[1179] The system of the present invention provides tourist attraction information and facility reservations in multiple languages, and is composed of three elements: a server, a terminal, and a user. A specific embodiment of the system is described below.

[1180] Server Processing

[1181] 1. Data Collection:

[1182] The server uses web scraping and APIs to collect basic information about tourist attractions, including their locations, contact details, and ratings from the Internet. This information is stored in JSON format.

[1183] 2. Data Analysis:

[1184] The collected information is then analyzed by a generative AI model, which extracts tourist attraction features and important reviews, summarizing key points and presenting them in a user-friendly format.

[1185] 3. Multilingual Translation:

[1186] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities. The translated information includes summaries of tourist attractions' features and ratings. The translated data is then stored in a data store, ready to respond to future search queries.

[1187] 4. Recommendation function:

[1188] The server recommends suitable tourist spots to users based on their location information and past search history, allowing users to plan their trips efficiently.

[1189] Terminal handling

[1190] 1. Submit a search query:

[1191] When a user searches for a tourist attraction on their device, the search query is sent to the server, which searches the data store to retrieve the relevant tourist attraction information and returns it to the device.

[1192] 2. Information display:

[1193] The terminal displays the tourist attraction information obtained from the server in multiple languages ​​to the user, who can then select a tourist attraction based on the displayed information.

[1194] 3. Facility Reservation:

[1195] If the user is satisfied with the displayed information and would like to visit the tourist attraction, he or she clicks the "Book" button. This click sends a reservation request from the terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the terminal of the result. The terminal then displays reservation confirmation information to the user.

[1196] Hardware and software used

[1197] Hardware: Servers are computer systems with high-performance data processing capabilities. Devices include smartphones and tablets.

[1198] Software: BeautifulSoup and Selenium are used for web scraping. Generative AI models are used for data analysis and multilingual translation. External translation functions such as Google Translate API are also used. SQLite and MySQL are used for data stores.

[1199] Specific examples

[1200] Tourist attraction information collection and translation:

[1201] The server collects and analyzes information about tourist attractions in a city from the web. For example, it extracts the characteristics and important reviews of "Tourist Attraction A" and translates them into English, Chinese, and Korean. The results are stored in a data store.

[1202] User search and facility reservation:

[1203] When a user searches for "tourist attraction A" on a device, the request is sent to the server. The server searches for the relevant information and returns it to the device. When the user confirms the information and clicks the button to make a reservation for the facility, a reservation request is sent to the server. The server completes the reservation procedure and notifies the device of the results.

[1204] Prompt Sentence Examples

[1205] "Please provide tourist information and reviews in English, Chinese, and Korean about tourist attraction A."

[1206] "Translate the tourist information and reviews about sight B into English, Chinese, and Korean."

[1207] As described above, the system of the present invention provides multilingual tourist information and facilitates facility reservations. In addition, the recommendation function based on the user's location information allows users to plan their trips more efficiently.

[1208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1209] Step 1:

[1210] The server collects tourist attraction information using web scraping and APIs. Specifically, it accesses the specified URL, analyzes the page content using BeautifulSoup and Selenium, and extracts the necessary information (name, address, contact information, reviews, etc.). The input is the URL, and the output is the collected tourist attraction information (in JSON format).

[1211] Step 2:

[1212] The server analyzes the collected tourist attraction information using a generative AI model. Specifically, it extracts and summarizes the tourist attraction's features and important review information. The input is the collected tourist attraction information (JSON format), and the output is the analyzed information (a summary of the features and review information).

[1213] Step 3:

[1214] The server translates the extracted information into multiple languages ​​using the translation function of the generative AI model. Specifically, it translates summaries of tourist attraction features and ratings into English, Chinese, and Korean. The input is the analyzed information, and the output is the information translated into multiple languages.

[1215] Step 4:

[1216] The server stores the translated information in a data store. Specifically, it stores the data in a database system such as SQLite or MySQL. The input is the translated information, and the output is stored in the database.

[1217] Step 5:

[1218] The device collects search queries from users and sends them to the server. Specifically, the user enters the name of a tourist attraction in the device's search bar and presses the search button. The input is the user's search query, and the output is a request sent to the server.

[1219] Step 6:

[1220] The server searches the database in response to the received search query to retrieve information on the relevant tourist attractions. Specifically, the process involves retrieving appropriate translation information from the database. The input is the user's search query, and the output is the retrieved tourist attraction information.

[1221] Step 7:

[1222] The server returns the acquired tourist attraction information to the terminal. Specifically, the process returns the information acquired from the database in JSON format. The input is the acquired tourist attraction information, and the output is the transmission of information to the terminal.

[1223] Step 8:

[1224] The terminal displays the tourist attraction information received from the server to the user. Specifically, this is a process of displaying tourist attraction information in multiple languages ​​on the terminal screen. The input is information from the server, and the output is the information displayed to the user.

[1225] Step 9:

[1226] When the user clicks the reservation button, the terminal sends a reservation request to the server. Specifically, the user indicates their intention to make a reservation by operating the reservation button on the screen. The input is the user's reservation instruction, and the output is the transmission of a reservation request to the server.

[1227] Step 10:

[1228] The server communicates with the facility's reservation system based on the received reservation request to confirm whether the reservation can be made. Specifically, this process works in conjunction with the reservation system API to carry out the reservation procedure. The input is the reservation request, and the output is the reservation confirmation result.

[1229] Step 11:

[1230] The server notifies the terminal of the reservation confirmation result. Specifically, if the reservation is successful, it sends detailed information to the terminal. The input is the reservation confirmation result, and the output is a notification to the terminal.

[1231] Step 12:

[1232] The terminal displays the reservation confirmation information received from the server to the user. Specifically, this process displays a message on the terminal screen indicating that the reservation was successful and provides detailed information. The input is the reservation confirmation information from the server, and the output is the display of the reservation confirmation information to the user.

[1233] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1234] This invention is a system that collects, analyzes, and translates tourist spot information and provides it to users in multiple languages, and also combines it with an emotion engine to recommend and book tourist spots based on the user's emotional state. The specific program processing of this system is explained below in natural language, with specific examples also included.

[1235] Data collection and analysis

[1236] Subject: Server

[1237] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (name, address, contact information, etc.) and user reviews. The collected data is temporarily stored in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[1238] Data Translation

[1239] Subject: Server

[1240] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[1241] Emotion recognition by emotion engine

[1242] Subject: User device

[1243] When a user searches for a tourist spot, the user terminal receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine recognizes that the user wants to relax.

[1244] Emotion-based information recommendation

[1245] Subject: Server

[1246] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[1247] Processing search queries and providing information

[1248] Subject: User device

[1249] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1250] Facility reservation

[1251] Subject: User device

[1252] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[1253] Specific examples

[1254] Example 1: Collecting and translating tourist spot information

[1255] Subject: Server

[1256] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[1257] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[1258] Translate the extracted information into English, Chinese, and Korean.

[1259] The translation results are stored in a database.

[1260] Example 2: User search and sentiment-based facility booking

[1261] Subject: User device

[1262] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax."

[1263] The server recommends tourist spots suitable for relaxation (e.g., hot springs or tranquil scenic spots) based on the recognized emotion data.

[1264] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[1265] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1266] The user terminal displays the reservation confirmation information.

[1267] The system of the present invention can significantly improve the user experience by recognizing the user's emotions and providing optimal tourist spot information based on those emotions. The above is a description of specific embodiments for carrying out the present invention.

[1268] The processing flow will be explained below.

[1269] Step 1: Gather information

[1270] Subject: Server

[1271] The server launches a web scraping program and API client for collecting tourist information. This allows it to obtain tourist spot information from tourism and promotional sites. The collected information includes basic facility information (name, address, contact information, etc.) and user reviews. The obtained data is temporarily saved in JSON format.

[1272] Step 2: Data structuring

[1273] Subject: Server

[1274] The server extracts the necessary basic information from the collected JSON data. Specifically, it extracts data such as facility name, address, contact information, opening hours, and fees. Next, it organizes the extracted data by tourist spot and converts it into a format that can be inserted into a database. The structured data is then saved in the database.

[1275] Step 3: Extracting features and reviews

[1276] Subject: Server

[1277] The server uses generative AI to extract the characteristics and important reviews of each tourist spot from the stored data. The generative AI then uses natural language processing technology to analyze the reviews and summarise the positive and negative points. The extracted characteristics and reviews are then passed on to the next processing step.

[1278] Step 4: Translate the information

[1279] Subject: Server

[1280] The extracted features and review information are translated into multiple languages. The server calls a generative AI translation module to translate the information into English, Chinese, Korean, etc. The translated information is then stored in a database along with the original Japanese information.

[1281] Step 5: Acquire and analyze emotion data

[1282] Subject: User device

[1283] When a user searches for a tourist spot, the user's device collects the user's input data and emotional information such as audio and video in real time. The emotion engine analyzes this collected data and recognizes the user's current emotional state. For example, the emotion "I want to relax" can be read from the user's facial expression.

[1284] Step 6: Emotion-based information recommendation

[1285] Subject: Server

[1286] Based on the emotion data recognized by the emotion engine, the server recommends the most suitable tourist spot information to the user. For example, if the user is recognized as wanting to "relax," the server will search the database for relaxing tourist spots such as tranquil landscapes and hot springs, and generate a recommendation list.

[1287] Step 7: Receiving and processing a search query

[1288] Subject: User device

[1289] A user enters keywords to search for tourist attractions. The user's search query is sent to a server, which also includes data about the user's current emotional state.

[1290] Step 8: Retrieving and returning search results

[1291] Subject: Server

[1292] The server queries the database based on the user's search query and emotion data to retrieve relevant tourist spot information. The retrieved information includes basic facility information, features, translated reviews, and recommendation reasons based on the user's emotion. The retrieved information is then organized and returned to the user's device.

[1293] Step 9: Viewing search results

[1294] Subject: User device

[1295] The user's device displays the tourist spot information sent from the server, including basic facility information, translated features, reviews, and emotion-based recommendations.

[1296] Step 10: Submit a booking request

[1297] Subject: User device

[1298] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[1299] Step 11: Reservation Processing

[1300] Subject: Server

[1301] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[1302] Step 12: View your booking confirmation

[1303] Subject: User device

[1304] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[1305] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[1306] Example 2

[1307] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1308] In recent years, with the development of the global tourism industry, there has been an increasing demand for tourist spot information accessible in multiple languages. However, there is a lack of systems that provide personalized information and reservation functions based on the user's emotional state, and there is a need to improve the user experience. Conventional systems have issues with language barriers and a lack of personalization functions when providing tourist spot information, making it difficult for users to select the optimal tourist spot that matches their emotional state. Therefore, a system that can efficiently recommend and reserve tourist spots based on the user's emotional state is needed.

[1309] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for saving the translated information in a database, means for analyzing data input by a user and recognizing an emotional state, means for recommending tourist spot information based on the recognized emotional state, means for providing translated information in response to a search query from a user, and means for making reservations for facilities based on the provided information. This makes it possible to provide tourist spot information and make reservations that are optimal for the user's emotional state.

[1310] "Tourist attraction information" refers to information such as the name, address, contact information, characteristics, and reviews of specific tourist spots and facilities.

[1311] "Means of collection" refers to web scraping tools and APIs used to obtain tourist spot information from the Internet.

[1312] The "analysis means" refers to generative AI models and text analysis tools that process the collected tourist spot information and extract features and important review information.

[1313] "Means for translating into multiple languages" refers to a machine translation API for translating collected and analyzed information into other languages.

[1314] "Means for storing in a database" refers to a storage system or database management system used to efficiently manage the analyzed and translated information.

[1315] The "means for analyzing user input data" refers to an emotion engine or text analysis tool that analyzes text input from a user and recognizes their emotional state.

[1316] The "means for recognizing emotional states" refers to generative AI models and sentiment analysis APIs for analyzing emotions from user text input.

[1317] The "means for providing translated information" refers to a search engine or display tool that retrieves and displays translated information in response to a user's search query.

[1318] "Means for recommending tourist spot information" refers to an algorithm or recommendation engine that selects and recommends the most appropriate tourist spot information based on the user's emotional state.

[1319] The "means of making facility reservations" refers to an online reservation system or API that works in conjunction with the tourist spot reservation system to execute and manage reservations.

[1320] The present invention provides a system for collecting, analyzing, and translating tourist spot information, and for recommending and reserving tourist spots based on the user's emotional state. The following describes in detail an embodiment of the system.

[1321] The system consists of a server, a user terminal, and multiple software modules. The server is the main component responsible for collecting, analyzing, translating, storing, and recommending tourist attraction information. The user terminal is a device used by users to access the system, such as a desktop computer, laptop, or smartphone.

[1322] Data collection

[1323] The server uses Python's Beautiful Soup and Scrapy libraries to collect information about tourist spots on the Internet through web scraping. It also calls tourist information APIs (such as the Google Places API) to obtain basic information about tourist facilities and user reviews. The collected data is temporarily stored in JSON format.

[1324] Data analysis

[1325] The collected JSON-formatted data is analyzed using a generative AI model (e.g., GPT-4). During this analysis process, the text data is preprocessed using Python's NLTK library to extract the characteristics of each tourist spot and important review information. This preprocessing step includes tokenization and stop word removal.

[1326] Data Translation

[1327] The resulting information is then translated into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL, ready to respond to future search queries.

[1328] User Input and Emotion Recognition

[1329] The user device provides a text input interface and captures the data entered in real time when the user searches for tourist attractions. This input data is analyzed using IBM Watson's sentiment analysis API to recognize the user's current emotional state. For example, if a user searches for "places to relax," this data is recognized as the emotional state of "wanting to relax."

[1330] information recommendation

[1331] The server then recommends the most suitable tourist spot information based on the user's emotional state. For example, if a user has an emotional state indicating a desire to relax, quiet scenery or hot springs will be recommended. This process is realized using a recommendation engine.

[1332] Processing search queries

[1333] When a user searches for a specific tourist spot name (for example, "Sensoji Temple"), the query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and returns it to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1334] Facility reservation

[1335] If the user is satisfied with the displayed information and would like to visit the tourist spot, he or she clicks the "Book" button. This sends a reservation request to the server. The server communicates with the facility's reservation system (e.g., AWS RDS) to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal displays reservation confirmation information.

[1336] Specific examples

[1337] Example 1: Collecting and translating tourist spot information

[1338] Example of server behavior:

[1339] The server collects information about tourist spots in Tokyo through web scraping (using Beautiful Soup) and an API (tourist information API).

[1340] Using GPT-4, we extract the characteristics and important reviews of Sensoji Temple.

[1341] The extracted information is translated into English, Chinese, and Korean using the Google Translate API.

[1342] The translation results are stored in a MySQL database.

[1343] Example 2: User search and sentiment-based facility booking

[1344] Example of user terminal behavior:

[1345] When a user searches for "places to relax," the input data is analyzed by an emotion engine (IBM Watson API), and the user's emotion is recognized as "I want to relax."

[1346] The server recommends tourist spots suitable for relaxation (e.g., hot springs, places with tranquil scenery) based on the recognized emotion data.

[1347] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[1348] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1349] The user terminal displays the reservation confirmation information.

[1350] By implementing the above steps, the system of the present invention can efficiently provide tourist spot information and make reservations that match the user's emotional state, thereby improving the user experience.

[1351] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1352] Step 1: Data collection

[1353] The server uses Python's Beautiful Soup and Scrapy libraries to collect tourist attraction information. It accesses tourist information websites and APIs (e.g., tourist information APIs) on the Internet to obtain tourist attraction names, addresses, contact information, and user reviews. This data is temporarily saved in JSON format.

[1354] Input: URL of tourist information site, API endpoint.

[1355] Output: Tourist spot information data in JSON format.

[1356] Specific operation: The server accesses "https: / / example.com / tourist-spots", extracts the tourist spot name, address, and contact information from the HTML using Beautiful Soup, and retrieves user reviews via the API. This data is temporarily stored in JSON format.

[1357] Step 2: Data analysis

[1358] The server analyzes the collected JSON-formatted data using a generative AI model (e.g., GPT-4). During the analysis process, the characteristics of each tourist spot and important review information are extracted. During this process, the NLTK library in Python is used to preprocess the text data (e.g., tokenize and remove stop words).

[1359] Input: Temporarily saved tourist spot information data in JSON format.

[1360] Output: Parsed feature information and important reviews.

[1361] How it works: The server loads the JSON data and uses NLTK to preprocess the text data, then uses a generative AI model (GPT-4) to extract tourist attraction features and important review information.

[1362] Step 3: Data Translation

[1363] The server translates the information obtained from the analysis into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL.

[1364] Input: Parsed feature information and important reviews.

[1365] Output: Tourist spot information translated into multiple languages.

[1366] Specific operation: The server sends the analysis results to the Google Translate API and translates them into English, Chinese, Korean, etc. The translation results are then stored in the database.

[1367] Step 4: Getting User Input and Emotion Recognition

[1368] When users search for tourist attractions, their devices capture text input in real time, which is then analyzed using IBM Watson's sentiment analysis API to recognize the user's emotional state.

[1369] Input: User's search query (e.g. "places to relax").

[1370] Output: The perceived emotional state of the user (e.g., "I want to relax").

[1371] Specific operation: The user device receives the input "place to relax" from the text input field, sends it to the IBM Watson API, and receives the sentiment analysis results.

[1372] Step 5: Information recommendation

[1373] The server recommends optimal tourist spot information based on the recognized emotional state, selects tourist spots suitable for the emotional state using a recommendation engine, and provides the recommended information to the user terminal.

[1374] Input: The user's perceived emotional state (e.g., "I want to relax").

[1375] Output: Recommendation information of tourist spots based on emotional state.

[1376] Specific operation: The server searches the database for tourist spots that match the emotional state of "wanting to relax" and sends the most appropriate information to the user's terminal.

[1377] Step 6: Processing the search query

[1378] When a user searches for a specific tourist spot name, the query is sent to the server, which searches the database to retrieve information about the relevant tourist spot and returns it to the user's device.

[1379] Input: User's search query (e.g. "Sensoji Temple").

[1380] Output: Detailed information about the tourist spot.

[1381] Specific operation: The user device sends the search query "Sensoji Temple" to the server. The server searches the database, obtains information about "Sensoji Temple," and sends it to the user device.

[1382] Step 7: Facility reservation

[1383] If the user is satisfied with the displayed information and clicks the "Reserve" button, a reservation request is sent to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible and notifies the user terminal of the result.

[1384] Input: The user's booking request.

[1385] Output: Confirmed booking information.

[1386] Specific operation: When the user clicks the reservation button, a reservation request is sent to the server. The server communicates with the reservation system to confirm whether the reservation can be made and notifies the user terminal of the result. The user terminal displays the reservation confirmation information.

[1387] The above are the specific processing steps of this system and the specific operations performed in each step.

[1388] (Application example 2)

[1389] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1390] In recent years, the amount of information on tourist spots has become enormous, making it difficult for users to find the tourist spots that suit them. There is also a demand for information provision tailored to user needs, such as multilingual support and facility reservations. However, conventional systems lack the functionality to recommend tourist spots based on the user's emotional state, limiting the user experience. Therefore, there is a need for a system that provides more personalized information and facilitates the reservation process.

[1391] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1392] In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for storing the translated information in a database, means for providing the translated information in response to a search query from a user, means for making facility reservations based on the provided information, and means for recognizing the user's emotional state and recommending tourist spots based on that emotion. This allows users to obtain tourist spot information in multiple languages ​​that matches their emotional state, enabling them to make facility reservations efficiently.

[1393] "Means for collecting tourist spot information" refers to a function that uses web scraping and APIs to collect data such as tourist spot names, addresses, contact information, photos, and reviews from the Internet.

[1394] "Means of analyzing collected information and extracting features and reviews" refers to a function that uses generative AI to analyze collected data on tourist spots and extract key features and important reviews from users.

[1395] "Means for translating extracted information into multiple languages" refers to a function that uses the translation function of generative AI to automatically translate extracted tourist spot information into multiple languages, such as English, Chinese, and Korean.

[1396] The "means for storing translated information in a database" is a function for storing translated tourist spot information in a database so that it can be used for later searching and display.

[1397] "Means for providing translated information in response to a search query from a user" is a function for searching a database for translated information in response to a query about a tourist spot searched by a user and providing it to the user.

[1398] "Means for making facility reservations based on the information provided" is a function that allows users to make reservations for facilities based on the tourist spot information they have viewed, and is a function that receives reservation requests and works in conjunction with the reservation system to complete the reservation.

[1399] "Means for recognizing the user's emotional state and recommending tourist spots based on that emotion" is a function that uses an emotion engine to recognize the user's emotional state from their input and actions, and automatically recommends tourist spots that match those emotions.

[1400] This invention is a system that collects and analyzes tourist spot information and provides it to users in multiple languages. Furthermore, by combining it with an emotion engine, it is possible to recommend and book tourist spots based on the user's emotional state. The hardware and software required to implement this invention are specifically described below.

[1401] Data collection and analysis

[1402] The server collects tourist attraction information using web scraping and APIs. The collected information includes the tourist attraction's name, address, contact information, photos, and user reviews. The collected data is temporarily stored in JSON format and then analyzed using a generative AI model. The analysis process extracts the characteristics of each tourist attraction and important review information.

[1403] Data Translation

[1404] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities, including English, Chinese, and Korean, and the translated information is stored in a database, ready to respond to future search queries.

[1405] Emotion recognition by emotion engine

[1406] When a user searches for a tourist spot, the device receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine analyzes this input and recognizes that the user wants to relax.

[1407] Emotion-based information recommendation

[1408] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[1409] Processing search queries and providing information

[1410] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1411] Facility reservation

[1412] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information.

[1413] Specific examples

[1414] Example 1: Collecting and translating tourist spot information

[1415] The server collects tourist information within the city through web scraping and APIs, extracts the characteristics and important reviews of "famous shrines" using a generative AI model, translates this into English, Chinese, and Korean, and stores it in a database.

[1416] Example 2: User search and sentiment-based facility booking

[1417] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax." Based on the recognized emotion data, the server recommends tourist spots suitable for relaxation (such as hot spring resorts or places with tranquil scenery). When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server, which cooperates with the facility's reservation system to complete the reservation, and then notifies the user's terminal of the results. The user's terminal displays reservation confirmation information.

[1418] Example prompt: "I am looking for a place to relax and unwind."

[1419] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1420] Step 1:

[1421] The server collects tourist attraction information using web scraping and APIs. As input, it requires the URL of the web page containing the tourist attraction and an API endpoint. As output, it obtains tourist attraction data in JSON format, including the name, address, contact information, photos, and reviews.

[1422] Step 2:

[1423] The server analyzes the collected tourist spot data and extracts features and important review information. A generative AI model is used for this analysis. The collected data in JSON format is required as input. The output is the extraction of tourist spot features and important review information. Data processing uses natural language processing technology to analyze the content of the reviews and pick out useful information.

[1424] Step 3:

[1425] The server translates the extracted information into multiple languages, using the translation function of the generative AI model. Features and reviews are required as input. The output is data translated into multiple languages, including English, Chinese, and Korean. Natural language processing is used to process the data and translate it into each language.

[1426] Step 4:

[1427] The server stores the translated information in a database. The input requires information translated in multiple languages. The output is the data stored in the database. The specific operation is a write operation to the database.

[1428] Step 5:

[1429] The device receives a search query from the user. The input requires the tourist spot name and conditions entered by the user. The output is the transmission of the search query to the server. The specific operation involves accepting input through the user interface and sending data to the server.

[1430] Step 6:

[1431] In response to a search query from a user, the server searches the database to retrieve information about the relevant tourist spot. The user's search query is required as input. Multilingual information about the relevant tourist spot is returned as output. Database query operations are performed as data operations.

[1432] Step 7:

[1433] The server sends the acquired information to the user's device. Tourist spot information acquired from the database is required as input. Data is sent to the user's device as output. Specifically, the data is sent via an HTTP response, etc.

[1434] Step 8:

[1435] The terminal receives the response from the server and displays the search results to the user. The tourist spot information sent from the server is required as input. The tourist spot information is displayed on the display screen as output. The specific operation is to update the user interface.

[1436] Step 9:

[1437] When the user checks the tourist attraction information and clicks the reservation button, the device uses an emotion engine to analyze the user's emotional state. The user's search content and input are required as input. The analyzed user's emotional state is obtained as output. An emotion analysis algorithm is applied to the data for calculation.

[1438] Step 10:

[1439] The server recommends optimal tourist spot information based on the emotional data recognized by the emotion engine. The analyzed emotional state and tourist spot data are required as input. The output is generated as recommended tourist spot information that matches the emotional state. Specifically, the server compares the emotional data with the tourist spot data to identify appropriate spots.

[1440] Step 11:

[1441] When the user checks the recommended tourist spot information and submits a reservation request, the terminal sends the reservation request to the server. The input requires the user's confirmation and the operation of the reservation button. The output is the sending of the reservation request to the server. The specific operation involves transmitting a signal from the user interface to the server.

[1442] Step 12:

[1443] The server receives the reservation request and verifies whether the reservation can be made by connecting with the facility's reservation system. The user's reservation request is required as input. The output is a result indicating whether the reservation can be made. The specific operation involves communication with the reservation system.

[1444] Step 13:

[1445] The server sends the reservation success / failure result to the terminal. The success / failure result from the reservation system is required as input. The result is notified to the user terminal as output. The specific operation is to send the data via an HTTP response.

[1446] Step 14:

[1447] The terminal receives the reservation availability result from the server and displays it to the user. The reservation availability result from the server is required as input. The reservation confirmation information is displayed on the user screen as output. The specific operation is to update the user interface.

[1448] These steps allow users to obtain tourist spot information that matches their emotional state and make reservations for facilities efficiently.

[1449] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1450] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1451] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1452] [Fourth embodiment]

[1453] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1454] 7, a 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.

[1455] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1456] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1457] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1458] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1459] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1460] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1461] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1462] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1463] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1464] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1465] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1466] This invention is a system that collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to easily make reservations for facilities based on that information. The specific program processing of this system is explained below in natural language, with specific examples also included.

[1467] Data collection and analysis

[1468] Subject: Server

[1469] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (such as name, address, and contact information) and user reviews. The collected data is saved in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[1470] Data Translation

[1471] Subject: Server

[1472] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[1473] Processing search queries and providing information

[1474] Subject: User device

[1475] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1476] Facility reservation

[1477] Subject: User device

[1478] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[1479] Specific examples

[1480] Example 1: Collecting and translating tourist spot information

[1481] Subject: Server

[1482] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[1483] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[1484] Translate the extracted information into English, Chinese, and Korean.

[1485] The translation results are stored in a database.

[1486] Example 2: User search and facility reservation

[1487] Subject: User device

[1488] When a user searches for "Sensoji Temple," the request is sent to the server.

[1489] The server searches the database and returns the relevant information to the user terminal.

[1490] The user terminal displays the returned information to the user.

[1491] The user clicks on the reservation button and a reservation request is sent to the server.

[1492] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1493] The user terminal displays the reservation confirmation information.

[1494] The above is a description of a specific embodiment for carrying out the present invention. This system allows foreign tourists to easily obtain information about tourist spots in Japan in multiple languages ​​and makes it possible to smoothly make reservations at facilities.

[1495] The processing flow will be explained below.

[1496] Step 1: Gather information

[1497] Subject: Server

[1498] The server launches a web scraping program and API client for collecting tourist information. Web scraping obtains information on tourist spots in Tokyo from tourism sites and tourism promotion sites. The API client obtains data using the APIs of map services and review sites. The collected information is temporarily saved in JSON format.

[1499] Step 2: Data structuring

[1500] Subject: Server

[1501] The server extracts the necessary basic information (such as name, address, and contact details) from the collected JSON data. It then classifies the data into different categories, such as facility information and review information, and converts it into a format that can be inserted into a database. This structured data is then stored in the database.

[1502] Step 3: Extracting features and reviews

[1503] Subject: Server

[1504] Generative AI is used to extract the characteristics and key reviews of each tourist spot from the stored data. The AI ​​model then uses text analysis techniques to identify and summarize positive and negative points from the reviews.

[1505] Step 4: Translate the information

[1506] Subject: Server

[1507] A translation module is invoked to translate the extracted features and reviews into different languages ​​such as English, Chinese, Korean, etc. The translated information is then stored in a database together with the original Japanese information.

[1508] Step 5: Receiving a user query

[1509] Subject: User device

[1510] A user inputs search keywords to search for tourist attractions, and a search request is sent to the server.

[1511] Step 6: Database Search

[1512] Subject: Server

[1513] The server queries the database based on the received search keywords and retrieves information about the relevant tourist spots, including basic information about the facilities, their features, and translated reviews.

[1514] Step 7: Returning search results

[1515] Subject: Server

[1516] The acquired tourist spot information is converted into a format to be sent back to the user's terminal, and the appropriate translation information is selected based on the user's language settings.

[1517] Step 8: Viewing search results

[1518] Subject: User device

[1519] The user terminal displays the tourist spot information sent from the server, including basic information about the facility, translated features, and reviews.

[1520] Step 9: Submit a booking request

[1521] Subject: User device

[1522] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[1523] Step 10: Reservation Processing

[1524] Subject: Server

[1525] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[1526] Step 11: View your booking confirmation

[1527] Subject: User device

[1528] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[1529] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[1530] Example 1

[1531] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1532] In recent years, the development of the tourism industry has created a demand for multilingual tourist information systems. However, existing systems struggle to effectively integrate the collection, analysis, and translation of tourist spot information, as well as the provision of information and reservation functions to users. Another challenge is improving the accuracy of information collected from multiple sources and provision in multiple languages. This makes it difficult for users to smoothly obtain the information they need, and the reservation process becomes tedious.

[1533] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1534] In this invention, the server includes means for collecting tourist spot information using web scraping and an application program interface, means for analyzing the collected information using a generative artificial intelligence model to extract features and reviews, and means for translating the extracted information into multiple languages ​​using a generative artificial intelligence model. This enables accurate collection, analysis, translation, and provision of tourist spot information in multiple languages. Furthermore, by providing appropriate information in response to search queries from user terminals, receiving facility reservation requests, and processing reservations in cooperation with a reservation management system, users can smoothly obtain information and easily proceed with the reservation process.

[1535] "Tourist attraction information" refers to detailed information such as basic information about places visited by tourists, addresses, contact information, opening hours, access methods, and user reviews.

[1536] "Web scraping" is a technique for automatically collecting data from websites using a program.

[1537] An "Application Program Interface (API)" is a means of providing definitions and protocols for different software applications to communicate with each other.

[1538] A "generative artificial intelligence model" refers to an artificial intelligence technology that uses natural language processing to analyze input data and generate information in a format that humans can understand.

[1539] "Means of collection" refers to the methods and tools used to collect tourist attraction information through web scraping and APIs.

[1540] "Means for analysis" refers to methods and tools for analyzing collected data using a generative artificial intelligence model and extracting its features and word-of-mouth information.

[1541] "Translation means" refers to the methods and tools for converting collected and analyzed information into different languages.

[1542] "Means of storing data in a database" refers to the systems and technologies used to organize and securely store processed information.

[1543] "Means for responding to search queries" refers to methods and tools for retrieving and providing appropriate data in response to a user's search request.

[1544] "Means for receiving facility reservation requests" refers to the methods and tools by which the server receives requests from users to reserve specific facilities.

[1545] "Means for linking with a reservation management system" refers to methods and tools for communicating with an external reservation management system, checking the reservation status of the facility, and confirming reservations.

[1546] This system collects, analyzes, and translates tourist spot information, provides it to users in multiple languages, and allows users to make reservations for facilities based on that information. Specific embodiments for carrying out the present invention are described below.

[1547] Data collection and analysis

[1548] Subject: Server

[1549] The server uses web scraping technology and application program interfaces (APIs) to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup and Scrapy libraries to retrieve data from the tourist attraction's official website, and also uses public tourist information APIs to obtain additional data. The collected information includes facility name, address, contact information, user reviews, etc., and is saved in JSON format.

[1550] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). During the analysis process, it identifies and structures the characteristics of tourist spots and important review information. For example, the analysis is performed using prompt sentences such as the following:

[1551] "Enter information about Sensoji Temple. Based on this information, we will extract the facility's features and important reviews."

[1552] Data Translation

[1553] Subject: Server

[1554] The extracted information is translated into multiple languages ​​using the translation function of a generative artificial intelligence model (e.g., DeepL Translation API or Google Translation API). Languages ​​to be translated include English, Chinese, and Korean. The translated information includes summaries of the property's features and reviews, and is stored in a database (e.g., PostgreSQL).

[1555] Processing search queries and providing information

[1556] Subject: User device

[1557] When a user searches for a tourist spot, they enter a search query from their device (PC, smartphone) and send it to the server. For example, if a user searches for "Sensoji Temple," the search query is sent to the server. The server searches the database, obtains information on matching tourist spots, and returns it to the user's device. The user's device displays the response received from the server to the user.

[1558] Facility reservation

[1559] Subject: User device

[1560] If the user checks the information about a tourist spot and decides to visit, they click the "Make a reservation" button on their user device. The user device then sends a reservation request to the server. The server then connects with the facility's reservation system (e.g., external reservation management API) to confirm whether the reservation can be made. Once the reservation is confirmed, the result is notified to the user device.

[1561] Specific examples

[1562] Example 1: Collecting and translating tourist spot information

[1563] Subject: Server

[1564] The server collects information about Tokyo's tourist spots through web scraping technology (BeautifulSoup) and a public API (tourist information API).

[1565] Using generative AI (GPT-4), we extract the characteristics and important reviews of Sensoji Temple.

[1566] The extracted information is translated into English, Chinese, and Korean using the DeepL translation API.

[1567] The translation results are stored in a PostgreSQL database.

[1568] Example 2: User search and facility reservation

[1569] Subject: User device

[1570] When a user searches for "Sensoji Temple," the request is sent from the device's web application to the server.

[1571] The server searches the database and returns the relevant information to the user terminal.

[1572] The user terminal displays the returned data on a user interface.

[1573] When the user clicks the "Book Now" button, a reservation request is sent to the server.

[1574] The server connects to an external reservation management API to confirm the reservation for Sensoji Temple.

[1575] The reservation result is notified to the user terminal, and the user receives reservation confirmation information.

[1576] The above is a detailed description of the embodiment of the present invention. This system allows users to obtain information about tourist spots in multiple languages ​​and easily make reservations at facilities.

[1577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1578] Step 1: Data collection

[1579] Subject: Server

[1580] The server uses web scraping technology and APIs to collect tourist attraction information. Specifically, it uses Python's BeautifulSoup library to retrieve HTML data from the tourist attraction's official website, and the Scrapy library to extract information. It also uses tourist information APIs to obtain additional information such as facility name, address, contact information, and opening hours.

[1581] Input: URL of tourist destination, tourist information API endpoint

[1582] Output: JSON format tourist spot information data

[1583] Specific behavior:

[1584] Use BeautifulSoup to process "https: / / example.com / tourist-spot / asakusa" and extract the necessary information from the HTML data.

[1585] The acquired data is converted into JSON format and prepared for the next analysis process.

[1586] Step 2: Analyze the data

[1587] Subject: Server

[1588] The server analyzes the collected data using a generative artificial intelligence model (e.g., OpenAI's GPT-4). Through this analysis process, tourist spot features and important reviews are identified and structured in JSON format.

[1589] Input: JSON format tourist spot information data

[1590] Output: Parsed data in JSON format (features and reviews)

[1591] Specific behavior:

[1592] A prompt is sent to the GPT-4 API saying, "Please extract the features of Sensoji Temple," and the features and reviews are extracted.

[1593] The analysis results are reconstructed into JSON format for the next translation process.

[1594] Step 3: Translate the data

[1595] Subject: Server

[1596] The server translates the parsed information into multiple languages ​​using the DeepL Translation API or Google Translation API. The translated information includes summaries of the property's features and reviews. This information is then stored in a database.

[1597] Input: Parsed data in JSON format

[1598] Output: Multilingual JSON format data

[1599] Specific behavior:

[1600] Translate the Japanese text "Sensoji Temple is a historic temple" into English, Chinese, and Korean using the DeepL Translation API.

[1601] The translation results are compiled in JSON format and each language version is saved in the database.

[1602] Step 4: Saving to the Database

[1603] Subject: Server

[1604] The server stores the translated information in a database by connecting to a PostgreSQL database and inserting the translated data using SQL statements.

[1605] Input: JSON format data translated into multiple languages

[1606] Output: Records in the database

[1607] Specific behavior:

[1608] Connect to the PostgreSQL database and execute the SQL statement "INSERT INTO tourist_spots (name, description_jp, description_en, description_cn, description_kr) VALUES (?, ?, ?, ?, ?)".

[1609] Step 5: Processing the search query

[1610] Subject: User device

[1611] To search for tourist attractions, a user inputs a search query from their device and sends it to the server, which searches the database to obtain matching tourist attraction information and returns it to the user device.

[1612] Input: The search query entered by the user (e.g., "Sensoji Temple")

[1613] Output: Tourist spot information as search results

[1614] Specific behavior:

[1615] A search query for "Sensoji Temple" is entered from the user's device and sent to the server.

[1616] The server searches the database and retrieves the relevant information for "Sensoji Temple"

[1617] Search results are returned to the user's device in JSON format

[1618] Step 6: Viewing information

[1619] Subject: User device

[1620] The user device analyzes the tourist spot information received from the server and displays it on the user interface. The displayed information includes the facility's features, contact information, access methods, reviews, etc.

[1621] Input: Tourist spot information received from the server (JSON format)

[1622] Output: What is displayed on the user interface

[1623] Specific behavior:

[1624] Parse the received JSON data and display it on the UI using React, Vue.js, etc.

[1625] For example, information such as "Name of facility: Sensoji Temple" and "Characteristics: Historic and full of attractions" will be displayed on the screen.

[1626] Step 7: Submit a facility reservation request

[1627] Subject: User device

[1628] If the user is satisfied with the displayed information, he clicks the reservation button to send a reservation request to the server.

[1629] Input: User's booking action (e.g., "Book Sensoji Temple")

[1630] Output: Booking request sent to server

[1631] Specific behavior:

[1632] User clicks the book button

[1633] The React frontend generates a JSON booking request and sends it to the server.

[1634] Step 8: Process facility reservations

[1635] Subject: Server

[1636] The server works in conjunction with an external reservation management system to check whether a reservation can be made, completes the reservation procedure, and notifies the user terminal of the reservation result.

[1637] Input: Reservation request from user (JSON format)

[1638] Output: Reservation result (success or failure)

[1639] Specific behavior:

[1640] The server communicates with an external reservation management API (e.g., Resy API) and attempts to reserve the facility.

[1641] If the reservation is confirmed, a message stating "Reservation completed" is generated and returned to the user's device in JSON format.

[1642] If the reservation fails, an error message will be returned along with the reason.

[1643] The above is the specific processing flow of this system. By combining the detailed operations and inputs / outputs at each step, a comprehensive tourist spot information and reservation system can be realized.

[1644] (Application example 1)

[1645] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1646] Conventional tourist information systems lack multilingual support, making them difficult for foreign tourists to use. In addition, they lack facility reservation and location-based recommendation functions, making it difficult for tourists to plan their trips efficiently.

[1647] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1648] In this invention, the server includes means for collecting tourist attraction information, means for analyzing the collected information and extracting characteristics and rating information, means for translating the extracted information into multiple languages, means for storing the translated information in a data store, means for providing the translated information in response to a search query from a terminal, means for making facility reservations based on the provided information, and means for providing recommended tourist attraction information based on the user's location information. This allows foreign tourists to easily obtain tourist information in multiple languages ​​and efficiently make facility reservations. Furthermore, the recommendation function based on the user's location information allows for smoother travel planning.

[1649] "Tourist attraction information" refers to all information related to tourism, including basic information on tourist destinations, facilities, and famous places, as well as their locations, contact information, and reviews.

[1650] "Means of collection" refers to methods or devices for gathering the required information from the internet or other data sources, such as using web scraping or APIs.

[1651] "Means of analysis" refers to software or algorithms that analyze collected information and extract useful features and word-of-mouth information.

[1652] The "translation means" refers to a translation algorithm or engine that converts the collected and analyzed information into multiple languages.

[1653] A "data store" is a database or storage system for storing collected, analyzed, and translated information.

[1654] "Search query" means a question or request sent by a user through a terminal, which serves as the basis for the server to provide information.

[1655] "Recommended tourist attraction information" is information that the server indicates to the user suitable tourist attractions based on the user's location information and interests.

[1656] The system of the present invention provides tourist attraction information and facility reservations in multiple languages, and is composed of three elements: a server, a terminal, and a user. A specific embodiment of the system is described below.

[1657] Server Processing

[1658] 1. Data Collection:

[1659] The server uses web scraping and APIs to collect basic information about tourist attractions, including their locations, contact details, and ratings from the Internet. This information is stored in JSON format.

[1660] 2. Data Analysis:

[1661] The collected information is then analyzed by a generative AI model, which extracts tourist attraction features and important reviews, summarizing key points and presenting them in a user-friendly format.

[1662] 3. Multilingual Translation:

[1663] The extracted information is then translated into multiple languages ​​using the generative AI model's translation capabilities. The translated information includes summaries of tourist attractions' features and ratings. The translated data is then stored in a data store, ready to respond to future search queries.

[1664] 4. Recommendation function:

[1665] The server recommends suitable tourist spots to users based on their location information and past search history, allowing users to plan their trips efficiently.

[1666] Terminal handling

[1667] 1. Submit a search query:

[1668] When a user searches for a tourist attraction on their device, the search query is sent to the server, which searches the data store to retrieve the relevant tourist attraction information and returns it to the device.

[1669] 2. Information display:

[1670] The terminal displays the tourist attraction information obtained from the server in multiple languages ​​to the user, who can then select a tourist attraction based on the displayed information.

[1671] 3. Facility Reservation:

[1672] If the user is satisfied with the displayed information and would like to visit the tourist attraction, he or she clicks the "Book" button. This click sends a reservation request from the terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the terminal of the result. The terminal then displays reservation confirmation information to the user.

[1673] Hardware and software used

[1674] Hardware: Servers are computer systems with high-performance data processing capabilities. Devices include smartphones and tablets.

[1675] Software: BeautifulSoup and Selenium are used for web scraping. Generative AI models are used for data analysis and multilingual translation. External translation functions such as Google Translate API are also used. SQLite and MySQL are used for data stores.

[1676] Specific examples

[1677] Tourist attraction information collection and translation:

[1678] The server collects and analyzes information about tourist attractions in a city from the web. For example, it extracts the characteristics and important reviews of "Tourist Attraction A" and translates them into English, Chinese, and Korean. The results are stored in a data store.

[1679] User search and facility reservation:

[1680] When a user searches for "tourist attraction A" on a device, the request is sent to the server. The server searches for the relevant information and returns it to the device. When the user confirms the information and clicks the button to make a reservation for the facility, a reservation request is sent to the server. The server completes the reservation procedure and notifies the device of the results.

[1681] Prompt Sentence Examples

[1682] "Please provide tourist information and reviews in English, Chinese, and Korean about tourist attraction A."

[1683] "Translate the tourist information and reviews about sight B into English, Chinese, and Korean."

[1684] As described above, the system of the present invention provides multilingual tourist information and facilitates facility reservations. In addition, the recommendation function based on the user's location information allows users to plan their trips more efficiently.

[1685] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1686] Step 1:

[1687] The server collects tourist attraction information using web scraping and APIs. Specifically, it accesses the specified URL, analyzes the page content using BeautifulSoup and Selenium, and extracts the necessary information (name, address, contact information, reviews, etc.). The input is the URL, and the output is the collected tourist attraction information (in JSON format).

[1688] Step 2:

[1689] The server analyzes the collected tourist attraction information using a generative AI model. Specifically, it extracts and summarizes the tourist attraction's features and important review information. The input is the collected tourist attraction information (JSON format), and the output is the analyzed information (a summary of the features and review information).

[1690] Step 3:

[1691] The server translates the extracted information into multiple languages ​​using the translation function of the generative AI model. Specifically, it translates summaries of tourist attraction features and ratings into English, Chinese, and Korean. The input is the analyzed information, and the output is the information translated into multiple languages.

[1692] Step 4:

[1693] The server stores the translated information in a data store. Specifically, it stores the data in a database system such as SQLite or MySQL. The input is the translated information, and the output is stored in the database.

[1694] Step 5:

[1695] The device collects search queries from users and sends them to the server. Specifically, the user enters the name of a tourist attraction in the device's search bar and presses the search button. The input is the user's search query, and the output is a request sent to the server.

[1696] Step 6:

[1697] The server searches the database in response to the received search query to retrieve information on the relevant tourist attractions. Specifically, the process involves retrieving appropriate translation information from the database. The input is the user's search query, and the output is the retrieved tourist attraction information.

[1698] Step 7:

[1699] The server returns the acquired tourist attraction information to the terminal. Specifically, the process returns the information acquired from the database in JSON format. The input is the acquired tourist attraction information, and the output is the transmission of information to the terminal.

[1700] Step 8:

[1701] The terminal displays the tourist attraction information received from the server to the user. Specifically, this is a process of displaying tourist attraction information in multiple languages ​​on the terminal screen. The input is information from the server, and the output is the information displayed to the user.

[1702] Step 9:

[1703] When the user clicks the reservation button, the terminal sends a reservation request to the server. Specifically, the user indicates their intention to make a reservation by operating the reservation button on the screen. The input is the user's reservation instruction, and the output is the transmission of a reservation request to the server.

[1704] Step 10:

[1705] The server communicates with the facility's reservation system based on the received reservation request to confirm whether the reservation can be made. Specifically, this process works in conjunction with the reservation system API to carry out the reservation procedure. The input is the reservation request, and the output is the reservation confirmation result.

[1706] Step 11:

[1707] The server notifies the terminal of the reservation confirmation result. Specifically, if the reservation is successful, it sends detailed information to the terminal. The input is the reservation confirmation result, and the output is a notification to the terminal.

[1708] Step 12:

[1709] The terminal displays the reservation confirmation information received from the server to the user. Specifically, this process displays a message on the terminal screen indicating that the reservation was successful and provides detailed information. The input is the reservation confirmation information from the server, and the output is the display of the reservation confirmation information to the user.

[1710] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1711] This invention is a system that collects, analyzes, and translates tourist spot information and provides it to users in multiple languages, and also combines it with an emotion engine to recommend and book tourist spots based on the user's emotional state. The specific program processing of this system is explained below in natural language, with specific examples also included.

[1712] Data collection and analysis

[1713] Subject: Server

[1714] The server collects tourist spot information using web scraping and APIs. This information includes basic facility information (name, address, contact information, etc.) and user reviews. The collected data is temporarily stored in JSON format and prepared for analysis. The server then analyzes the collected data using generative AI. This analysis process extracts the characteristics of each tourist spot and important review information.

[1715] Data Translation

[1716] Subject: Server

[1717] The extracted information is then translated into multiple languages ​​(e.g., English, Chinese, and Korean) using generative AI translation capabilities. The translated information includes summaries of the property's features and reviews. The translated data is then stored in a database, ready to respond to future search queries.

[1718] Emotion recognition by emotion engine

[1719] Subject: User device

[1720] When a user searches for a tourist spot, the user terminal receives the user's input data in real time. The emotion engine analyzes this input data and recognizes the user's current emotional state. For example, if a user searches for "places to relax," the emotion engine recognizes that the user wants to relax.

[1721] Emotion-based information recommendation

[1722] Subject: Server

[1723] Based on the emotional data recognized by the emotion engine, the server recommends tourist spot information that is most suitable for the user. For example, if the user has the emotion "I want to relax," the server will recommend relaxing tourist spots such as tranquil landscapes and hot springs. This allows the user to easily obtain tourist spot information that matches their emotional state.

[1724] Processing search queries and providing information

[1725] Subject: User device

[1726] When a user searches for a tourist spot (for example, "Sensoji Temple") on their device, the search query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and sends it back to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1727] Facility reservation

[1728] Subject: User device

[1729] If the user is satisfied with the displayed information and would like to visit the tourist spot, they click the "Book" button. This sends a reservation request from the user terminal to the server. The server communicates with the facility's reservation system to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal then displays reservation confirmation information to the user.

[1730] Specific examples

[1731] Example 1: Collecting and translating tourist spot information

[1732] Subject: Server

[1733] The server collects information about tourist spots in Tokyo through web scraping and APIs.

[1734] Generative AI is used to extract the characteristics and important reviews of Sensoji Temple.

[1735] Translate the extracted information into English, Chinese, and Korean.

[1736] The translation results are stored in a database.

[1737] Example 2: User search and sentiment-based facility booking

[1738] Subject: User device

[1739] When a user searches for "places to relax," the input data is analyzed by the emotion engine, and the user's emotion is recognized as "I want to relax."

[1740] The server recommends tourist spots suitable for relaxation (e.g., hot springs or tranquil scenic spots) based on the recognized emotion data.

[1741] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[1742] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1743] The user terminal displays the reservation confirmation information.

[1744] The system of the present invention can significantly improve the user experience by recognizing the user's emotions and providing optimal tourist spot information based on those emotions. The above is a description of specific embodiments for carrying out the present invention.

[1745] The processing flow will be explained below.

[1746] Step 1: Gather information

[1747] Subject: Server

[1748] The server launches a web scraping program and API client for collecting tourist information. This allows it to obtain tourist spot information from tourism and promotional sites. The collected information includes basic facility information (name, address, contact information, etc.) and user reviews. The obtained data is temporarily saved in JSON format.

[1749] Step 2: Data structuring

[1750] Subject: Server

[1751] The server extracts the necessary basic information from the collected JSON data. Specifically, it extracts data such as facility name, address, contact information, opening hours, and fees. Next, it organizes the extracted data by tourist spot and converts it into a format that can be inserted into a database. The structured data is then saved in the database.

[1752] Step 3: Extracting features and reviews

[1753] Subject: Server

[1754] The server uses generative AI to extract the characteristics and important reviews of each tourist spot from the stored data. The generative AI then uses natural language processing technology to analyze the reviews and summarise the positive and negative points. The extracted characteristics and reviews are then passed on to the next processing step.

[1755] Step 4: Translate the information

[1756] Subject: Server

[1757] The extracted features and review information are translated into multiple languages. The server calls a generative AI translation module to translate the information into English, Chinese, Korean, etc. The translated information is then stored in a database along with the original Japanese information.

[1758] Step 5: Acquire and analyze emotion data

[1759] Subject: User device

[1760] When a user searches for a tourist spot, the user's device collects the user's input data and emotional information such as audio and video in real time. The emotion engine analyzes this collected data and recognizes the user's current emotional state. For example, the emotion "I want to relax" can be read from the user's facial expression.

[1761] Step 6: Emotion-based information recommendation

[1762] Subject: Server

[1763] Based on the emotion data recognized by the emotion engine, the server recommends the most suitable tourist spot information to the user. For example, if the user is recognized as wanting to "relax," the server will search the database for relaxing tourist spots such as tranquil landscapes and hot springs, and generate a recommendation list.

[1764] Step 7: Receiving and processing a search query

[1765] Subject: User device

[1766] A user enters keywords to search for tourist attractions. The user's search query is sent to a server, which also includes data about the user's current emotional state.

[1767] Step 8: Retrieving and returning search results

[1768] Subject: Server

[1769] The server queries the database based on the user's search query and emotion data to retrieve relevant tourist spot information. The retrieved information includes basic facility information, features, translated reviews, and recommendation reasons based on the user's emotion. The retrieved information is then organized and returned to the user's device.

[1770] Step 9: Viewing search results

[1771] Subject: User device

[1772] The user's device displays the tourist spot information sent from the server, including basic facility information, translated features, reviews, and emotion-based recommendations.

[1773] Step 10: Submit a booking request

[1774] Subject: User device

[1775] When a user clicks the "Book Now" button on the facility details page, a reservation request is sent to the server, including the user's contact information and the desired reservation date and time.

[1776] Step 11: Reservation Processing

[1777] Subject: Server

[1778] The server connects to the reservation system of the specified facility to check whether the reservation is possible. If the reservation is possible, the server confirms the reservation and saves the reservation information in the database. The server then returns the reservation result to the user's terminal.

[1779] Step 12: View your booking confirmation

[1780] Subject: User device

[1781] The user terminal displays the reservation confirmation information received from the server, allowing the user to confirm that the reservation has been completed successfully.

[1782] The above is a specific processing flow in the system of the present invention. The operations performed by the server, terminal, and user at each step have been explained in detail.

[1783] Example 2

[1784] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1785] In recent years, with the development of the global tourism industry, there has been an increasing demand for tourist spot information accessible in multiple languages. However, there is a lack of systems that provide personalized information and reservation functions based on the user's emotional state, and there is a need to improve the user experience. Conventional systems have issues with language barriers and a lack of personalization functions when providing tourist spot information, making it difficult for users to select the optimal tourist spot that matches their emotional state. Therefore, a system that can efficiently recommend and reserve tourist spots based on the user's emotional state is needed.

[1786] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot information, means for analyzing the collected information and extracting features and word-of-mouth information, means for translating the extracted information into multiple languages, means for saving the translated information in a database, means for analyzing data input by a user and recognizing an emotional state, means for recommending tourist spot information based on the recognized emotional state, means for providing translated information in response to a search query from a user, and means for making reservations for facilities based on the provided information. This makes it possible to provide tourist spot information and make reservations that are optimal for the user's emotional state.

[1787] "Tourist attraction information" refers to information such as the name, address, contact information, characteristics, and reviews of specific tourist spots and facilities.

[1788] "Means of collection" refers to web scraping tools and APIs used to obtain tourist spot information from the Internet.

[1789] The "analysis means" refers to generative AI models and text analysis tools that process the collected tourist spot information and extract features and important review information.

[1790] "Means for translating into multiple languages" refers to a machine translation API for translating collected and analyzed information into other languages.

[1791] "Means for storing in a database" refers to a storage system or database management system used to efficiently manage the analyzed and translated information.

[1792] The "means for analyzing user input data" refers to an emotion engine or text analysis tool that analyzes text input from a user and recognizes their emotional state.

[1793] The "means for recognizing emotional states" refers to generative AI models and sentiment analysis APIs for analyzing emotions from user text input.

[1794] The "means for providing translated information" refers to a search engine or display tool that retrieves and displays translated information in response to a user's search query.

[1795] "Means for recommending tourist spot information" refers to an algorithm or recommendation engine that selects and recommends the most appropriate tourist spot information based on the user's emotional state.

[1796] The "means of making facility reservations" refers to an online reservation system or API that works in conjunction with the tourist spot reservation system to execute and manage reservations.

[1797] The present invention provides a system for collecting, analyzing, and translating tourist spot information, and for recommending and reserving tourist spots based on the user's emotional state. The following describes in detail an embodiment of the system.

[1798] The system consists of a server, a user terminal, and multiple software modules. The server is the main component responsible for collecting, analyzing, translating, storing, and recommending tourist attraction information. The user terminal is a device used by users to access the system, such as a desktop computer, laptop, or smartphone.

[1799] Data collection

[1800] The server uses Python's Beautiful Soup and Scrapy libraries to collect information about tourist spots on the Internet through web scraping. It also calls tourist information APIs (such as the Google Places API) to obtain basic information about tourist facilities and user reviews. The collected data is temporarily stored in JSON format.

[1801] Data analysis

[1802] The collected JSON-formatted data is analyzed using a generative AI model (e.g., GPT-4). During this analysis process, the text data is preprocessed using Python's NLTK library to extract the characteristics of each tourist spot and important review information. This preprocessing step includes tokenization and stop word removal.

[1803] Data Translation

[1804] The resulting information is then translated into multiple languages ​​using the Google Translate API or DeepL API, and the translated data is stored in a database such as MySQL, ready to respond to future search queries.

[1805] User Input and Emotion Recognition

[1806] The user device provides a text input interface and captures the data entered in real time when the user searches for tourist attractions. This input data is analyzed using IBM Watson's sentiment analysis API to recognize the user's current emotional state. For example, if a user searches for "places to relax," this data is recognized as the emotional state of "wanting to relax."

[1807] information recommendation

[1808] The server then recommends the most suitable tourist spot information based on the user's emotional state. For example, if a user has an emotional state indicating a desire to relax, quiet scenery or hot springs will be recommended. This process is realized using a recommendation engine.

[1809] Processing search queries

[1810] When a user searches for a specific tourist spot name (for example, "Sensoji Temple"), the query is sent to the server. The server searches the database, obtains information about the relevant tourist spot (features and reviews in multiple languages), and returns it to the user's device. The user's device receives the response from the server and displays it to the user as a search result.

[1811] Facility reservation

[1812] If the user is satisfied with the displayed information and would like to visit the tourist spot, he or she clicks the "Book" button. This sends a reservation request to the server. The server communicates with the facility's reservation system (e.g., AWS RDS) to confirm whether the reservation is possible. If the reservation is possible, the server completes the reservation procedure and notifies the user terminal of the result. The user terminal displays reservation confirmation information.

[1813] Specific examples

[1814] Example 1: Collecting and translating tourist spot information

[1815] Example of server behavior:

[1816] The server collects information about tourist spots in Tokyo through web scraping (using Beautiful Soup) and an API (tourist information API).

[1817] Using GPT-4, we extract the characteristics and important reviews of Sensoji Temple.

[1818] The extracted information is translated into English, Chinese, and Korean using the Google Translate API.

[1819] The translation results are stored in a MySQL database.

[1820] Example 2: User search and sentiment-based facility booking

[1821] Example of user terminal behavior:

[1822] When a user searches for "places to relax," the input data is analyzed by an emotion engine (IBM Watson API), and the user's emotion is recognized as "I want to relax."

[1823] The server recommends tourist spots suitable for relaxation (e.g., hot springs, places with tranquil scenery) based on the recognized emotion data.

[1824] When the user checks the details of the recommended tourist spot and clicks the reservation button, a reservation request is sent to the server.

[1825] The server completes the reservation in cooperation with the facility's reservation system and notifies the user terminal of the result.

[1826] The user terminal displays the reservation confirmation information.

[1827] By implementing the above steps, the system of the present invention can efficiently provide tourist spot information and make reservations that match the user's emotional state, thereby improving the user experience.

[1828] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1829] Step 1: Data collection

[1830] The server uses Python's Beautiful Soup and Scrapy libraries to collect tourist attraction information. It accesses tourist information websites and APIs (e.g., tourist information APIs) on the Internet to obtain tourist attraction names, addresses, contact information, and user reviews. This data is temporarily saved in JSON format.

[1831] Input: URL of tourist i...

Claims

1. A means of collecting tourist spot information; A means of analyzing the collected information and extracting characteristics and word-of-mouth information; means for translating the extracted information into multiple languages; a means for storing the translated information in a database; means for providing translated information in response to a search query from a user; a means for making facility reservations based on the information provided; and A system including:

2. 10. The system of claim 1, further comprising means for retrieving appropriate tourist spot information based on the search query and displaying it on the user terminal.

3. 10. The system of claim 1, further comprising means for receiving a reservation request by a user and coordinating with a reservation system to complete the reservation.

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