system

Abstract

To provide a system that provides reliable ratings and efficient reservation procedures. [Solution] A system including: means for collecting evaluation information from various evaluation sites and social media; means for saving the collected evaluation information in a database; means for providing an interface for inputting the user's hobbies, preferences, schedule, and budget; means for searching the database for matching evaluation information based on the input information and generating a travel plan; means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; means for completing the reservation in cooperation with each application site based on the reservation information; means for collecting feedback from the user after the trip or meal; means for saving the collected feedback in a database and using it to propose plans for the next time and thereafter; and means for evaluating the contribution of companies participating in the platform and distributing income.

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] When planning a trip or meal, users must gather information from multiple review sites and social media, which can lead to confusion due to the different ratings and prices. Another problem is that using multiple platforms can make the reservation process complicated. Furthermore, each platform has different relative rating criteria, making it difficult to make reliable comparisons. [Means for solving the problem]

[0005] The present invention provides a means for collecting review information from various review sites and social media and converting it into a unified format. The unified format review information is stored in a database. It also provides an interface for inputting the user's hobbies, preferences, schedule, and budget, and includes a means for searching the database for matching review information based on the input information to generate a travel plan. The generated travel plan is presented to the user, and the system also includes a means for collecting reservation information for the selected plan. It also includes a means for notifying the user of reservation confirmation information when the travel plan reservation is completed. It also includes a means for collecting feedback from users after travel or dining, storing it in a database, and using it to propose future plans. Finally, the system includes a means for evaluating the contribution of platform participants and distributing revenue, thereby realizing a system that provides reliable reviews and an efficient reservation process.

[0006] A "rating site" is a website where users post ratings and comments about travel destinations, restaurants, etc.

[0007] "Social media" refers to online platforms that enable users to share information and interact.

[0008] "Rating information" refers to data such as ratings and comments posted on rating sites and social media, poster information, and posting date and time.

[0009] A "unified format" refers to a data format that converts different evaluation scales and data formats into a consistent format.

[0010] "Database" means a digital storage system for storing and managing collected evaluation information.

[0011] "Interface" refers to the front-end portion of software that provides the screens and elements through which a user can input information.

[0012] An "algorithm" is a defined set of steps or procedures for solving a particular problem.

[0013] "Feedback" refers to the ratings and impressions users provide after a trip or meal.

[0014] "Platform Participating Companies" refers to companies that provide data and services to this system.

[0015] "Contribution level" refers to the value of a company calculated based on evaluations such as word-of-mouth information and reservation history provided by each company to the system. [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] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan trips and meals. This system is made up of the following functions: server, terminal, and user.

[0038] 1. Collecting and converting evaluation information

[0039] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, posting date and time, etc.

[0040] The server centrally manages the collected evaluation information and converts it into a unified format. For example, it converts different evaluation scales such as 5-point and 10-point ratings into a 10-point rating. It also stores each evaluation information in a database.

[0041] 2. Providing a user interface

[0042] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, itinerary, and hobbies and preferences.

[0043] Users input search criteria through the device interface, such as the purpose of their trip, the area they want to visit, their budget, and the duration of their trip.

[0044] 3. Analyzing user data and generating travel plans

[0045] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[0046] The server then generates a travel plan that best suits the user based on the search results. This plan includes hotels, restaurants, and tourist attractions based on the user's preferences and budget. Each plan is accompanied by reviews and comments, making it easy for the user to understand.

[0047] Examples:

[0048] When a user enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server generates a plan that matches these conditions and suggests a travel plan that includes highly rated hotels and restaurants.

[0049] 4. Reservation Procedure

[0050] If the user checks the proposed plan and wishes to make a reservation, they enter the necessary information on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0051] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0052] 5. Gathering feedback and improving the system

[0053] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0054] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0055] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[0056] ---

[0057] This system makes travel and dining planning efficient and fair, providing users with reliable information with minimal effort, simplifying the overall booking process, and enabling continuous improvement through feedback.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] Subject: Server

[0061] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0062] Step 2:

[0063] Subject: Server

[0064] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[0065] Step 3:

[0066] Subject: Server

[0067] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0068] Step 4:

[0069] Subject: Terminal

[0070] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences.

[0071] Step 5:

[0072] Subject: User

[0073] The user enters the travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the device interface and clicks the "Submit" button.

[0074] Step 6:

[0075] Subject: Terminal

[0076] The terminal sends the information entered by the user to the server in a data format such as JSON.

[0077] Step 7:

[0078] Subject: Server

[0079] The server searches the database based on the received user conditions and retrieves matching evaluation information.

[0080] Step 8:

[0081] Subject: Server

[0082] The server generates a personalized itinerary for the user based on the search results, including hotels, dining options, and attractions, all with ratings and reviews.

[0083] Step 9:

[0084] Subject: Server

[0085] The server sends the generated travel plan to the terminal in JSON format or similar.

[0086] Step 10:

[0087] Subject: Terminal

[0088] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[0089] Step 11:

[0090] Subject: User

[0091] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the terminal.

[0092] Step 12:

[0093] Subject: Terminal

[0094] The terminal sends the reservation information entered by the user to the server in JSON format or similar.

[0095] Step 13:

[0096] Subject: Server

[0097] The server connects the received reservation information through the API of each application site and executes the reservation.

[0098] Step 14:

[0099] Subject: Server

[0100] When the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0101] Step 15:

[0102] Subject: Server

[0103] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[0104] Step 16:

[0105] Subject: User

[0106] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[0107] Step 17:

[0108] Subject: Server

[0109] The server stores the received feedback information in a database and uses it for subsequent plan generation.

[0110] Step 18:

[0111] Subject: Server

[0112] The server evaluates the contribution of each participating company based on reviews and booking history, and prepares revenue distribution data.

[0113] Example 1

[0114] 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."

[0115] Traditional travel and dining planning requires users to individually research multiple online review sites and social media, which can often be inefficient. Furthermore, the lack of a unified rating scale across different review sites makes it difficult to make proper comparisons. Furthermore, there are few systems that automatically generate optimal travel plans tailored to a user's specific needs and budget, and the booking process can be complicated and time-consuming. As a result, users often end up with unsatisfactory plans despite the significant effort required.

[0116] 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.

[0117] In this invention, the server includes: means for collecting review information from various review sites and social media; means for converting the collected review information into a unified format; means for saving the unified format review information in a database; means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget; means for searching the database for matching review information based on the input information and generating a travel plan; means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; means for completing the reservation by connecting with each application site based on the reservation information; means for collecting feedback from the user after the trip or meal; means for saving the collected feedback in a database and using it for future plan proposals; means for evaluating the contribution of platform participants and distributing revenue; means for using an API and web scraping to collect review information; and means for using a generative AI model to generate prompts based on the user's input information when generating a travel plan. This allows users to obtain efficient and accurate travel plans based on reliable information with little effort.

[0118] "Rating information" refers to data such as user ratings and comments, poster information, and posting date and time.

[0119] A "unified format" is a format that converts different evaluation scales into a common standard.

[0120] A "database" is a digital storage system for storing and managing evaluation information, feedback information, and the like.

[0121] An "interface" is a user interaction tool that allows users to input information such as hobbies, preferences, schedules, and budgets.

[0122] A "travel plan" is a plan including accommodations, places to eat, and tourist attractions that is generated based on information input by the user.

[0123] A "generative AI model" is an artificial intelligence algorithm that generates optimal travel plans based on user input information.

[0124] A "prompt sentence" is input text given to a generative AI model to guide the AI's response.

[0125] "Reservation Information" means the details required to reserve the travel plan selected by the User.

[0126] "Feedback" refers to ratings and comments provided by users after their travel or dining experiences.

[0127] "Contribution level" is an evaluation based on word-of-mouth information and number of reservations provided by companies participating in the platform.

[0128] "Web scraping" is a technique for automatically collecting data from web pages.

[0129] An "API" is an interface for exchanging functions and data between different software systems.

[0130] This invention is a system that collects and centrally manages word-of-mouth information from various rating sites and social media to help users efficiently plan trips and meals. This system is made up of a server, terminals, and user functions.

[0131] 1. Collecting and converting evaluation information

[0132] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. Specifically, it uses libraries such as Python's BeautifulSoup or Selenium to obtain data such as rating points, comments, poster information, and posting date and time from the Internet. If an API is provided, it is also possible to obtain the data directly using an HTTP request.

[0133] The server centrally manages the collected rating information and converts it into a unified format. Different rating scales, such as 5-point or 10-point ratings obtained from different rating sites, are converted into a common 10-point rating. This conversion is performed using the Python Pandas library, and the data is formatted in a unified format before being stored in a database.

[0134] 2. Providing a user interface

[0135] When a user accesses the terminal, it displays an interface built using HTML / CSS and JavaScript (registered trademark), providing a form for entering travel destination information, budget, itinerary, hobbies, and preferences.

[0136] Users enter search criteria through the device interface, such as "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," and then click the submit button.

[0137] 3. Analyzing user data and generating travel plans

[0138] The terminal sends the data entered by the user to the server. The terminal uses JavaScript AJAX to send the data entered by the user asynchronously to the server.

[0139] The server parses the user data and searches the database for matching reviews. It uses the SQLAlchemy library to execute database queries and extract data that matches the user's criteria.

[0140] The server generates the optimal travel plan for the user based on the search results. It uses machine learning libraries such as PyTorch and TENSORFLOW (registered trademark) to provide prompt sentences to the generative AI model to generate the optimal plan.

[0141] Examples:

[0142] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model:

[0143] text

[0144] Purpose of trip: Hot spring trip

[0145] Budget: Under 20,000 yen per person

[0146] Dates: 3 days from September 10th

[0147] Please suggest a plan that includes highly rated hotels and restaurants.

[0148] 4. Reservation Procedure

[0149] The user checks the proposed plan and, if they wish to make a reservation, enters the reservation information on the interface. The user enters the reservation information in the form and clicks the submit button.

[0150] The server processes the reservation via the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is complete, the server sends reservation confirmation information to the terminal and notifies the user.

[0151] 5. Gathering feedback and improving the system

[0152] The server sends a feedback request message to the user after the trip or meal is completed, sending an email and providing a link to the feedback form.

[0153] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate subsequent plans.

[0154] The introduction of this system will enable travel and meal planning to be carried out efficiently and based on reliable information, allowing users to enjoy optimal plans with minimal effort. In addition, it will enable companies to properly evaluate and reflect their contributions, improving the overall quality of services.

[0155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0156] Step 1:

[0157] The server collects rating information from various rating sites and social media. This collection is done using APIs or web scraping. Specifically, it uses Python's BeautifulSoup and Selenium to periodically retrieve data such as rating points, comments, poster information, and posting date and time. The input is the rating site or social media, and the output is a collection of the retrieved rating information.

[0158] Step 2:

[0159] The server converts the collected rating information into a unified format. Different rating scales, such as 5-point or 10-point ratings, obtained from different sites are converted into a 10-point rating. Specifically, the data is converted and unified using the Python Pandas library. The input is the collected rating information, and the output is the converted rating information in a unified format.

[0160] Step 3:

[0161] The server saves the rating information in a unified format to a database. It connects to the database using the SQLAlchemy library and saves the rating information. The input is the converted rating information in the unified format, and the output is the data saved in the database.

[0162] Step 4:

[0163] The terminal displays an interface when accessed by the user. The user interface is built using HTML / CSS and JavaScript and includes forms for entering travel destination information, budget, itinerary, hobbies, and preferences. The input is the information accessed by the user, and the output is the interface that is displayed.

[0164] Step 5:

[0165] The user inputs search criteria through the terminal interface. For example, "hot spring trip," "budget under 20,000 yen per person," and "3 days starting September 10th," and then clicks the send button. The input is the user's search criteria, and the output is the submitted search criteria data.

[0166] Step 6:

[0167] The terminal sends the data entered by the user to the server. Using JavaScript AJAX, the user's input data is sent asynchronously to the server. The input is the user's search criteria data, and the output is the data sent to the server.

[0168] Step 7:

[0169] The server parses the user data and searches the database for matching reviews. It uses SQLAlchemy to execute database queries and extract data that matches the user's criteria. The input is the user's search criteria data, and the output is the search results.

[0170] Step 8:

[0171] The server generates the optimal travel plan for the user based on the search results. Using machine learning libraries such as PyTorch and TensorFlow, the server generates the optimal plan by providing prompts to the generative AI model. The specific prompts are shown below.

[0172] Examples:

[0173] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model.

[0174] text

[0175] Purpose of trip: Hot spring trip

[0176] Budget: Under 20,000 yen per person

[0177] Dates: 3 days from September 10th

[0178] Please suggest a plan that includes highly rated hotels and restaurants.

[0179] Step 9:

[0180] If the user checks the proposed plan and wishes to make a reservation, they enter their reservation information on the interface. The user enters the reservation information into the form and clicks the submit button. The input is the user's reservation information, and the output is the submitted reservation information data.

[0181] Step 10:

[0182] The server processes reservations through the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user. The input is the user's reservation information, and the output is reservation confirmation information.

[0183] Step 11:

[0184] The server sends a feedback request message to the user after the trip or meal is completed. It sends an email and provides a link to the feedback form. The input is the trip or meal completion information, and the output is the feedback request message.

[0185] Step 12:

[0186] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate future plans. The input is the user's feedback, and the output is the feedback stored in the database.

[0187] (Application example 1)

[0188] 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."

[0189] Conventional food delivery systems have difficulty comprehensively collecting word-of-mouth information from a wide range of review sites and social media to propose optimal ordering plans based on users' preferences and budgets. Furthermore, because the information provided depends on the standards of each review site, the system relies on inconsistent reviews, making it difficult to propose accurate plans. Furthermore, continuous improvement of the system and fair revenue distribution are difficult due to insufficient collection of feedback after orders and evaluation of the contributions of platform participants.

[0190] 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.

[0191] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for storing the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a food order plan, means for presenting the generated food order plan to the user and collecting information on selected orders, means for completing the order in cooperation with each delivery service based on the order information, means for collecting feedback from the user after the food order is placed, means for storing the collected feedback in a database and using it for future proposals, and means for evaluating the contributions of platform participants and distributing revenue. This allows for the proposal of an optimal food order plan based on user requests, maintains consistency in review information, and also allows for post-order feedback and evaluation of the contributions of businesses.

[0192] "Evaluation information" refers to information such as user-provided evaluation points, comments, poster information, and posting date and time, which is collected from various evaluation sites and social media.

[0193] A "unified format" is a data format that converts evaluation information provided on different evaluation scales and formats into a form that can be compared using consistent standards.

[0194] A "database" is an information storage system for systematically storing and managing collected and converted evaluation information, user input information, feedback, etc.

[0195] An "interface" is an operation screen or input form provided for users to input information such as hobbies, preferences, schedules, and budgets.

[0196] The "Food Ordering Plan" is an optimal delivery plan based on the user's input information, including suggested delivery stores and menus, reviews, ordering procedures, etc.

[0197] "Order Information" refers to data required for the ordering process based on the food ordering plan selected by the user, such as the type of food, the number of items ordered, the delivery address, and contact information.

[0198] "Feedback" refers to reaction information such as impressions, ratings, and satisfaction levels provided by users after ordering food.

[0199] "Platform participating businesses" are companies and stores that participate in the food delivery system and provide evaluation information and delivery services.

[0200] "Contribution level" refers to the degree of contribution to the system, calculated based on the quality of services provided by platform participants, word-of-mouth reviews, number of orders, etc.

[0201] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan food delivery. This system is made up of the following functions: server, terminal, and user.

[0202] 1. Collecting and converting evaluation information

[0203] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, and posting date and time. Beautiful Soup is commonly used for web scraping. The collected data is then converted into a unified format (for example, converting different rating scales into a 10-point rating system).

[0204] 2. Data storage and management

[0205] The server stores the rating information in a standardized format in a database. This database stores collected reviews, user input, and feedback. It can be managed using a relational database service such as Amazon RDS.

[0206] 3. Providing a user interface

[0207] When accessed by a user, the terminal displays an interface that includes a form for inputting delivery type, budget, cuisine type, etc. Users can input search criteria through the terminal interface and plan specific orders.

[0208] 4. Analyzing user data and generating order plans

[0209] The terminal sends the data entered by the user to the server. The server analyzes the user data and searches for matching reviews in the database. The server generates the optimal food ordering plan for the user based on the search results. This plan includes menus and restaurants based on the user's tastes, preferences, and budget. Each plan is accompanied by reviews and comments, which are provided to the user in an easy-to-understand manner.

[0210] Examples:

[0211] When a user enters the criteria "sushi," "budget under 5,000 yen," and "high reviews," the server generates a plan that matches these criteria and suggests delivery restaurants and menus with high reviews.

[0212] 5. Order Processing

[0213] If the user reviews the proposed plan and wishes to place an order, they enter the necessary information on the interface. The order information entered by the user is sent to the server via the terminal. The server processes the order through the API of each delivery service based on the order information received from the user. Once the order is completed, the server sends order confirmation information to the terminal and notifies the user.

[0214] 6. Gathering feedback and improving the system

[0215] After the food order is completed, the server sends the user a message requesting feedback. The message includes a link to a feedback form, which the user can click to enter their thoughts. Once the user submits their feedback, the server stores it in its database, which can improve the accuracy of future suggestions.

[0216] 7. Evaluation of Platform Participants and Revenue Distribution

[0217] The server evaluates the contribution of the businesses participating in the platform and distributes revenue accordingly. For example, businesses that provide more word-of-mouth information or receive more orders are given higher contribution ratings, enabling fair revenue distribution.

[0218] This system allows users to obtain reliable information with minimal effort, simplifies the delivery ordering process, and allows for continuous improvement of the system through feedback.

[0219] Example prompt sentence:

[0220] "I'm looking for a sushi delivery service. My budget is under 5,000 yen. Can you recommend a place with good reviews?"

[0221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0222] Step 1:

[0223] Collecting and converting evaluation information

[0224] The server periodically collects evaluation information from various evaluation sites and social media using APIs or web scraping.

[0225] Input: URLs of rating sites, social media, API keys, etc.

[0226] Data processing: Using Python scripts and Beautiful Soup, we extract the rating, comments, author information, and posting date and time from each page.

[0227] Output: Standardized format of the evaluation information data, including the converted evaluation scores into a 10-point scale.

[0228] Step 2:

[0229] Data storage and management

[0230] The server stores the collected and converted rating information in a database.

[0231] Input: Evaluation information data in a uniform format.

[0232] Data Computation and Storage: Use a relational database such as Amazon RDS to store the evaluation information in an organized manner.

[0233] Output: Evaluation information data stored in a database.

[0234] Step 3:

[0235] Providing a user interface

[0236] The terminal displays the interface when accessed by the user.

[0237] Input: User access.

[0238] How it works: It displays an interface built in Swift and Kotlin where users can input delivery type, budget, and cuisine type.

[0239] Output: The search criteria data entered by the user.

[0240] Step 4:

[0241] Analyzing user data and generating order plans

[0242] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[0243] Input: The search criteria data entered by the user.

[0244] Data calculation: Python scripts are used to search the database for matching reviews, and a search algorithm is used to generate the optimal food ordering plan.

[0245] Output: Optimal food ordering plan data.

[0246] Step 5:

[0247] Checkout

[0248] The user reviews the proposed plan and, if he / she wishes to place an order, enters the information required for the order on the interface.

[0249] Input: Optimal food ordering plan data and user order information.

[0250] Operation: Order information is sent to the server, and the order is processed on the server. An external API is used to connect with the delivery service.

[0251] Output: Order confirmation information.

[0252] Step 6:

[0253] Feedback collection and system improvement

[0254] The server will send a feedback request message to the user after the food order is completed, and once the user submits the feedback, the server will store the feedback in the database.

[0255] Input: Order confirmation information and user feedback information.

[0256] Data storage: Collected feedback information is stored in a database.

[0257] Output: Feedback data.

[0258] Step 7:

[0259] Evaluation of platform participants and revenue distribution

[0260] The server evaluates the contribution of the platform participants and distributes the revenue.

[0261] Input: Collected rating information, order data, feedback data.

[0262] Data calculation: Using a contribution evaluation algorithm, the contribution of each business operator is calculated and the percentage of revenue distribution is determined.

[0263] Output: Income distribution data.

[0264] 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.

[0265] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. It also combines an emotion engine that recognizes user emotions to improve customer satisfaction. This system is comprised of the following functions: server, terminal, and user.

[0266] 1. Collecting and converting evaluation information

[0267] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0268] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[0269] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0270] 2. Providing a user interface

[0271] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, etc. The device also sends the user's text input and voice data to the emotion engine.

[0272] The user inputs travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the terminal interface or by voice input.

[0273] 3. Emotion Recognition and Data Analysis

[0274] The device sends the user's input data and voice data to the emotion engine, which analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0275] The server records the emotion information sent from the emotion engine in a database and reflects it in generating travel plans for the user. For example, it may suggest plans that allow the user to relax or stay active based on the emotion information.

[0276] 4. Analyzing user data and generating travel plans

[0277] The terminal transmits the condition data and emotion information input by the user to the server.

[0278] The server searches the database based on the received user conditions and emotion information, and retrieves matching evaluation information.

[0279] The server then generates a personalized itinerary for the user based on the search results. The itinerary includes hotels, restaurants, and attractions, each with ratings and reviews. Each itinerary reflects the user's emotional state to ensure a context-optimized experience.

[0280] Examples:

[0281] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[0282] 5. Reservation Procedure

[0283] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0284] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0285] 6. Gathering feedback and improving the system

[0286] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0287] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0288] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[0289] ---

[0290] The system thus constructed ensures efficient and fair travel and dining planning, provides an optimal experience based on the user's emotional state, simplifies the overall booking process by providing reliable information with minimal effort, and continuously improves the system through feedback.

[0291] The processing flow will be explained below.

[0292] Step 1:

[0293] Subject: Server

[0294] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0295] Step 2:

[0296] Subject: Server

[0297] The server converts the collected rating information into a standardized format, for example, converting different rating scales such as 5-point and 10-point scales into a 10-point scale.

[0298] Step 3:

[0299] Subject: Server

[0300] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0301] Step 4:

[0302] Subject: Terminal

[0303] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, schedule, and hobbies and preferences.

[0304] Step 5:

[0305] Subject: User

[0306] Users input search criteria (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface, and also express their feelings through text or voice.

[0307] Step 6:

[0308] Subject: Terminal

[0309] The device sends the search criteria and voice data entered by the user to the emotion engine, which then analyzes the received text and voice data to recognize the user's emotions.

[0310] Step 7:

[0311] Subject: Server

[0312] The server records the emotion information sent from the emotion engine in a database and reflects it in generating a travel plan for the user.

[0313] Step 8:

[0314] Subject: Terminal

[0315] The device sends the information entered by the user and emotional information to the server in a data format such as JSON.

[0316] Step 9:

[0317] Subject: Server

[0318] The server searches the database for matching reviews based on the received user data, including the user's travel destination, budget, schedule, and emotional state.

[0319] Step 10:

[0320] Subject: Server

[0321] The server generates a travel plan optimized for the user based on the search results, including hotels, restaurants, and attractions with ratings and reviews, and reflects the user's emotional state.

[0322] Examples:

[0323] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[0324] Step 11:

[0325] Subject: Server

[0326] The server sends the generated travel plan to the terminal in JSON format or similar.

[0327] Step 12:

[0328] Subject: Terminal

[0329] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[0330] Step 13:

[0331] Subject: User

[0332] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact details, etc.) on the device interface.

[0333] Step 14:

[0334] Subject: Terminal

[0335] The terminal sends the reservation information entered by the user to the server in a data format such as JSON.

[0336] Step 15:

[0337] Subject: Server

[0338] The server executes the reservation through the API of each application site based on the received reservation information. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0339] Step 16:

[0340] Subject: Server

[0341] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[0342] Step 17:

[0343] Subject: User

[0344] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[0345] Step 18:

[0346] Subject: Server

[0347] The server stores the received feedback information in a database and uses it for future plan generation. Emotional information is also recorded as feedback.

[0348] Step 19:

[0349] Subject: Server

[0350] The server evaluates the contribution of each participating company based on reviews, booking history, and user satisfaction, and prepares revenue distribution data based on this.

[0351] Example 2

[0352] 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."

[0353] Conventional travel planning systems typically collect and analyze user evaluation information to make suggestions, but they do not reflect the user's emotional state during the actual trip, which means they are unable to fully increase user satisfaction. Furthermore, the booking process and feedback collection process are cumbersome, and there are still issues with the overall system efficiency.

[0354] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recognizing the emotional state from the user's input information using an emotion engine, means for recording the recognized emotional state in a database and reflecting it in the generation of a travel plan, and means for presenting the generated travel plan to the user and collecting reservation information for the selected plan. This makes it possible to propose an optimal travel plan based on the user's emotional state, significantly improving user satisfaction.

[0355] "Rating information" refers to word-of-mouth, reviews, ratings, poster information, posting date and time, etc. collected from various rating sites and social media.

[0356] An "emotion engine" refers to software or hardware that analyzes user input data (text or voice) and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0357] "Interface" refers to the display screen and operating means through which users access the system and input information such as hobbies, preferences, schedule, budget, and travel destinations.

[0358] "Travel Plan" refers to a plan that includes suggestions for accommodation, places to eat, attractions, etc. based on the user's input information and perceived emotional state.

[0359] "Database" refers to a system for storing and managing collected evaluation information, emotional information, user input information, feedback, etc.

[0360] "Feedback" refers to the impressions and evaluation information provided by users after traveling or eating.

[0361] "Platform participating companies" refer to companies that provide information and services to the system and contribute to the operation of the system.

[0362] "Contribution" refers to the degree to which platform participating companies are evaluated based on the quality and quantity of evaluation information they provide to the system, the number of reservations processed, etc.

[0363] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system aims to improve customer satisfaction. The system of the present invention is made up of the following functions: server, terminal, and user.

[0364] 1. Collecting and converting evaluation information

[0365] The server periodically collects evaluation information using APIs or web scraping functions from various evaluation sites and social media. The collected data includes evaluation scores, comments, poster information, posting date and time, etc. The necessary information is extracted from the HTML data of the evaluation sites using the Python library "BeautifulSoup" and other tools.

[0366] The server then converts the collected rating information into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale, allowing data collected from different sites to be stored in a consistent format.

[0367] Finally, the server stores the rating information in a standardized format in a MySQL® database. The stored data includes rating points, review content, site name, posting date and time, etc.

[0368] 2. Providing a user interface

[0369] When a user accesses the device, an interface is displayed for entering information such as travel destination, budget, schedule, hobbies, and preferences. This interface is built using HTML / CSS and JavaScript. Users can enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" in the text boxes.

[0370] 3. Emotion Recognition and Data Analysis

[0371] The device sends the data entered by the user and the voice data to the emotion engine, which then analyzes the received data using, for example, the emotion analysis API of IBM Watson (registered trademark) and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0372] The server records the emotion information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores information such as "Relaxed" in the "Emotional State" field.

[0373] 4. Analyzing user data and generating travel plans

[0374] The device sends the user's input criteria data and emotion information to the server. The server searches the database based on the received user criteria and emotion information to obtain matching rating information. The server then generates an optimal travel plan for the user based on the search results. This plan includes hotels, restaurants, and tourist attractions, each with its own rating and review content.

[0375] As a concrete example, if a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes a highly rated hot spring hotel and a quiet, relaxing place to eat.

[0376] 5. Reservation Procedure

[0377] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0378] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0379] 6. Gathering feedback and improving the system

[0380] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0381] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0382] The system also has a means of evaluating the contribution of companies participating in the platform and distributing income. For example, a system is in place that gives higher contribution points to companies that provide more word-of-mouth information or receive more reservations.

[0383] Prompt Sentence Examples

[0384] "I want to relax. Can you plan a three-day hot spring trip starting September 10th? My budget is under 20,000 yen per person."

[0385] "I'm planning a family trip. Can you recommend some good places to eat? My budget is 30,000 yen."

[0386] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0387] Step 1: Gather evaluation information

[0388] The server collects review information using APIs or web scraping functions from various review sites and social media. Specifically, it uses the Python library "BeautifulSoup" to parse HTML data from a specified URL and extract word-of-mouth information. The input is the URL of the review site and a query, and the output is review information such as rating points, comments, poster information, and posting date and time.

[0389] Step 2: Standardize data formats

[0390] The server converts the collected rating information into a standardized format. For example, it unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating. Specifically, it doubles each rating point to convert a 5-point rating into a 10-point rating. The input is the collected rating information, and the output is rating information in a standardized format.

[0391] Step 3: Save your data

[0392] The server stores the rating information in a standardized format in a database. Specifically, it uses a MySQL database to store records including rating points, review content, site name, and posting date and time. The input is rating information in a standardized format, and the output is the record stored in the database.

[0393] Step 4: Displaying the User Interface

[0394] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences. Specifically, it displays a web form built using HTML / CSS and JavaScript. The input is the user's access, and the output is the display of the input form.

[0395] Step 5: Entering User Data

[0396] The user inputs travel conditions (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface. For example, the user might enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" into text boxes. Input is the information the user types into the device, and output is the input data displayed on the device.

[0397] Step 6: Sending Emotion Data

[0398] The device sends the data and voice data entered by the user to the emotion engine. Specifically, the entered text data and voice data is sent to the IBM Watson emotion analysis API. The input is the user's input data, and the output is the data sent to the emotion engine.

[0399] Step 7: Recognize emotions

[0400] The emotion engine analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.). For example, it recognizes the "positive" emotion from the text "I want to relax." The input is the transmitted data, and the output is the recognized emotional state data.

[0401] Step 8: Storing Emotional Information

[0402] The server records the emotional information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores "Relaxed" in the "Emotional State" field. The input is the recognized emotional state data, and the output is the emotional information stored in the database.

[0403] Step 9: Sending condition data

[0404] The device sends the condition data and emotional information entered by the user to the server. Specifically, the user's condition data (e.g., travel destination, budget, schedule, hobbies, and preferences) and emotional information are sent via API. The input is the condition data and emotional information entered into the device, and the output is the data sent to the server.

[0405] Step 10: Search the database

[0406] The server searches the database based on the received user criteria and emotion information to retrieve matching rating information. Specifically, it uses an SQL query to search for records of hotels and tourist attractions that match the criteria. The input is the user's criteria data and emotion information, and the output is the search result records.

[0407] Step 11: Generate a travel plan

[0408] The server generates an optimal travel plan for the user based on the search results. Specifically, it creates a plan that includes highly rated hot spring hotels and quiet dining spots, and attaches their ratings and reviews. The input is the search result records, and the output is the generated travel plan.

[0409] Step 12: Present your travel plans

[0410] The terminal presents the generated itinerary to the user. Specifically, it generates a web page displaying the details of the itinerary and displays it to the user. The input is the itinerary sent from the server, and the output is the itinerary presented to the user.

[0411] Step 13: Enter reservation information

[0412] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The input is the user's personal information, and the output is the reservation information displayed on the terminal.

[0413] Step 14: Complete the booking process

[0414] The server processes reservations through the API of each application site based on the reservation information received from the user. Specifically, it uses the API of the travel reservation site to make reservations according to the specified conditions. The input is the user's reservation information, and the output is confirmation data that the reservation has been completed.

[0415] Step 15: Notification of reservation confirmation information

[0416] When the reservation is completed, the server sends the reservation confirmation information to the terminal and notifies the user. Specifically, it generates a reservation confirmation email and sends it to the user's email address. The input is the confirmation data of the reservation completion, and the output is the reservation confirmation information notified to the user.

[0417] Step 16: Submit a feedback request

[0418] After the trip or meal is completed, the server sends a feedback request message to the user. Specifically, it sends an automated email with the message "Please tell us what you thought of your trip." The input is the user's email address, and the output is the sent feedback request message.

[0419] Step 17: Submit and save your feedback

[0420] When a user submits feedback, the server stores the feedback in a database. Specifically, when a user fills out an input form and clicks the "Submit" button, the data is stored in a MySQL database. The input is the user's feedback, and the output is the feedback stored in the database.

[0421] Step 18: System Improvement

[0422] The server uses the collected feedback to improve the accuracy of future plan suggestions. Specifically, it adjusts the recommendation algorithm through feedback analysis and processes data to further increase user satisfaction. The input is the stored feedback, and the output is an improved algorithm and proposed plans.

[0423] (Application example 2)

[0424] 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."

[0425] When shopping online or planning trips and meals, it takes time and effort for users to collect reviews and find the best products and plans for themselves. Furthermore, conventional recommendation systems do not take into account the user's emotional state, making it difficult to improve customer satisfaction. Therefore, there is a need for systems that can easily find the best products and plans based on the user's emotional state and streamline the purchasing and reservation process.

[0426] 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.

[0427] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for saving the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a travel plan, means for presenting the generated travel plan to the user and collecting reservation information for the selected plan, means for completing the reservation in cooperation with each application site based on the reservation information, means for collecting feedback from the user after the trip or meal, means for saving the collected feedback in a database and using it for future plan proposals, means for evaluating the contributions of platform participating companies and distributing revenue, means for analyzing the user's emotional state using an emotion engine and saving it in a database together with the review information, means for generating product recommendation information based on the user's emotional state, means for presenting the generated recommendation information to the user and collecting purchase information for the selected product, and means for completing the purchase in cooperation with each sales site based on the purchase information. This allows users to easily find the best products and travel plans based on their emotional state and efficiently complete the purchase and reservation process.

[0428] "Evaluation information" refers to information such as evaluation scores and comments collected from various evaluation sites and social media.

[0429] A "unified format" is a data format that standardizes different evaluation scales and formats and converts them into a consistent format.

[0430] A "database" is a storage device for systematically storing collected and unified evaluation information and additional information.

[0431] An "interface" is a screen or element through which a user inputs information into a device or receives information from a system.

[0432] An "emotion engine" is a technology that analyzes user input information and voice data to recognize the user's emotional state.

[0433] "Recommendation information" is information that suggests optimal products, travel plans, etc. based on the user's hobbies, preferences, and emotional state.

[0434] "Reservation Information" refers to information including personal information and conditions necessary to reserve the plan or product selected by the user.

[0435] A "merchandise site" is a website or platform that offers products or services and accepts online purchases.

[0436] "Feedback" refers to information such as impressions, ratings, and opinions provided by users after traveling or using a product.

[0437] "Platform participating companies" are companies that provide evaluation information and services to this system and are involved in system operation.

[0438] The system of the present invention recommends optimal products and travel plans based on the user's hobbies, preferences, schedule, budget, and emotional state, and then efficiently processes the subsequent purchase and reservation procedures. Specific implementation methods of the system are described below.

[0439] 1. Collecting and converting evaluation information

[0440] The server periodically collects rating information using APIs or web scraping functions from various rating sites and social media. For example, information can be obtained using Python's BeautifulSoup or requests library. The collected data is converted into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale. The data is then stored in a relational database such as MySQL or PostgreSQL.

[0441] 2. Providing a user interface

[0442] When accessed by a user, the device uses a cross-platform UI framework such as Flutter (registered trademark) to display an interface for inputting hobbies, preferences, schedules, budgets, and emotional states. The device sends the user's text input data to a natural language processing engine such as Google (registered trademark) Dialogflow, and receives the input information.

[0443] 3. Emotion Recognition and Data Analysis

[0444] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize the user's emotional state (e.g., joy, sadness, surprise, etc.). The analyzed emotion information is sent to a server and recorded in a database.

[0445] 4. Analyzing user data and generating recommendations

[0446] The server searches the database based on the user's input criteria and emotional information to retrieve matching rating information. This is done using data analysis tools such as Python, Pandas, and ElasticSearch (registered trademark). Based on the search results, an algorithm is run to generate products and travel plans that best suit the user's emotional state.

[0447] 5. Present the generated recommendation information and process purchases and reservations

[0448] The device presents the generated recommendation information to the user and collects purchase information for the products selected by the user and reservation information for the travel plan. The purchase or reservation information is sent to the server, and the purchase or reservation process is carried out via the API of each sales site or application site. Reservation or purchase confirmation information is sent to the device and notified to the user.

[0449] 6. Gathering feedback and improving the system

[0450] After a purchase or trip is completed, the server sends a message to the user requesting feedback. The user enters their feedback and the submitted information is stored in a database and used to propose plans for the next trip.

[0451] Hardware and software used

[0452] Server hardware: AWS (registered trademark) EC2, RDS

[0453] Device hardware: iOS or ANDROID® device

[0454] Software: Python, BeautifulSoup, requests, Flutter, Google Dialogflow, IBM Watson, Google Cloud Natural Language API, Pandas, Elasticsearch, Django, SQLAlchemy, REST API

[0455] Specific examples

[0456] If a user is in an emotional state such as "I've been busy lately and want to relax," and enters the conditions "relaxation products," "budget of 5,000 yen or less," and "interested in aroma-related products," the system will recommend highly rated aroma diffusers and relaxation CDs.

[0457] Prompt Sentence Examples

[0458] Please recommend the best products to users whose current emotional state is "I want to be soothed," who are interested in "aroma-related products," and whose budget is "within 5,000 yen." Please select products that will help users relax, taking into account product reviews and sentiment analysis results.

[0459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0460] Step 1:

[0461] Collecting and converting evaluation information

[0462] The server periodically collects rating information using various rating sites, social media APIs, or web scraping functions. Specifically, it acquires information using Python's BeautifulSoup and requests libraries. Input data includes rating points, comments, poster information, posting date and time, etc. This is converted into a standardized format, and different rating scales (e.g., 5-point rating, 10-point rating, etc.) are unified and converted into a 10-point rating. The output data is rating information in a standardized format.

[0463] Step 2:

[0464] Saving rating information

[0465] The server stores the rating information in a unified format in a database. Specifically, it uses a relational database such as MySQL or PostgreSQL. The input data includes rating points, review content, site name, posting date and time, etc., and storing this data makes it easier to search and analyze later. The output includes structured rating information in the database.

[0466] Step 3:

[0467] Providing a user interface

[0468] The device uses Flutter to display an interface for users to input their hobbies, preferences, schedule, budget, and emotional state when accessed by the user. The input data is the condition information entered by the user, which is received and sent to the server. The output is the condition data entered by the user.

[0469] Step 4:

[0470] Emotion Recognition and Data Analysis

[0471] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize emotional states (e.g., joy, sadness, surprise, etc.). The input data is the user's text and voice data, and after analysis, emotional information is output and sent to the server.

[0472] Step 5:

[0473] Analyzing user data and generating recommendations

[0474] The server searches the database based on the input criteria data and emotion information to obtain matching rating information. It processes the data using data analysis tools such as Python, Pandas, and Elasticsearch. The input data are the user's criteria data and emotion information, and the output is recommendation information based on the user's emotional state.

[0475] Step 6:

[0476] Present generated recommendation information and process purchases and reservations

[0477] The terminal presents the user with recommended products and travel plans and receives the user's selection. Purchase information for the products and reservation information for the travel plans selected by the user is collected and sent from the terminal to the server. The output is the purchase information and reservation information selected by the user. Based on this information, the server processes the purchase and reservation via the APIs of each sales site and application site. Purchase confirmation and reservation confirmation information are sent to the terminal and notified to the user.

[0478] Step 7:

[0479] Gathering feedback and improving the system

[0480] After a purchase or trip is completed, the server sends a message to the user requesting feedback. When the user inputs and submits feedback, the information is stored in the database. The input data is the user's feedback, and the output data is the feedback information stored in the database. This allows for improved accuracy of future plan suggestions.

[0481] 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.

[0482] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0483] 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.

[0484] [Second embodiment]

[0485] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0486] 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.

[0487] 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).

[0488] 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.

[0489] 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.

[0490] 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).

[0491] 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.

[0492] 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.

[0493] 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.

[0494] 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.

[0495] 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.

[0496] 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."

[0497] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan trips and meals. This system is made up of the following functions: server, terminal, and user.

[0498] 1. Collecting and converting evaluation information

[0499] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, posting date and time, etc.

[0500] The server centrally manages the collected evaluation information and converts it into a unified format. For example, it converts different evaluation scales such as 5-point and 10-point ratings into a 10-point rating. It also stores each evaluation information in a database.

[0501] 2. Providing a user interface

[0502] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, itinerary, and hobbies and preferences.

[0503] Users input search criteria through the device interface, such as the purpose of their trip, the area they want to visit, their budget, and the duration of their trip.

[0504] 3. Analyzing user data and generating travel plans

[0505] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[0506] The server then generates a travel plan that best suits the user based on the search results. This plan includes hotels, restaurants, and tourist attractions based on the user's preferences and budget. Each plan is accompanied by reviews and comments, making it easy for the user to understand.

[0507] Examples:

[0508] When a user enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server generates a plan that matches these conditions and suggests a travel plan that includes highly rated hotels and restaurants.

[0509] 4. Reservation Procedure

[0510] If the user checks the proposed plan and wishes to make a reservation, they enter the necessary information on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0511] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0512] 5. Gathering feedback and improving the system

[0513] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0514] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0515] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[0516] ---

[0517] This system makes travel and dining planning efficient and fair, providing users with reliable information with minimal effort, simplifying the overall booking process, and enabling continuous improvement through feedback.

[0518] The processing flow will be explained below.

[0519] Step 1:

[0520] Subject: Server

[0521] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0522] Step 2:

[0523] Subject: Server

[0524] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[0525] Step 3:

[0526] Subject: Server

[0527] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0528] Step 4:

[0529] Subject: Terminal

[0530] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences.

[0531] Step 5:

[0532] Subject: User

[0533] The user enters the travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the device interface and clicks the "Submit" button.

[0534] Step 6:

[0535] Subject: Terminal

[0536] The terminal sends the information entered by the user to the server in a data format such as JSON.

[0537] Step 7:

[0538] Subject: Server

[0539] The server searches the database based on the received user conditions and retrieves matching evaluation information.

[0540] Step 8:

[0541] Subject: Server

[0542] The server generates a personalized itinerary for the user based on the search results, including hotels, dining options, and attractions, all with ratings and reviews.

[0543] Step 9:

[0544] Subject: Server

[0545] The server sends the generated travel plan to the terminal in JSON format or similar.

[0546] Step 10:

[0547] Subject: Terminal

[0548] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[0549] Step 11:

[0550] Subject: User

[0551] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the terminal.

[0552] Step 12:

[0553] Subject: Terminal

[0554] The terminal sends the reservation information entered by the user to the server in JSON format or similar.

[0555] Step 13:

[0556] Subject: Server

[0557] The server connects the received reservation information through the API of each application site and executes the reservation.

[0558] Step 14:

[0559] Subject: Server

[0560] When the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0561] Step 15:

[0562] Subject: Server

[0563] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[0564] Step 16:

[0565] Subject: User

[0566] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[0567] Step 17:

[0568] Subject: Server

[0569] The server stores the received feedback information in a database and uses it for subsequent plan generation.

[0570] Step 18:

[0571] Subject: Server

[0572] The server evaluates the contribution of each participating company based on reviews and booking history, and prepares revenue distribution data.

[0573] Example 1

[0574] 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."

[0575] Traditional travel and dining planning requires users to individually research multiple online review sites and social media, which can often be inefficient. Furthermore, the lack of a unified rating scale across different review sites makes it difficult to make proper comparisons. Furthermore, there are few systems that automatically generate optimal travel plans tailored to a user's specific needs and budget, and the booking process can be complicated and time-consuming. As a result, users often end up with unsatisfactory plans despite the significant effort required.

[0576] 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.

[0577] In this invention, the server includes: means for collecting review information from various review sites and social media; means for converting the collected review information into a unified format; means for saving the unified format review information in a database; means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget; means for searching the database for matching review information based on the input information and generating a travel plan; means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; means for completing the reservation by connecting with each application site based on the reservation information; means for collecting feedback from the user after the trip or meal; means for saving the collected feedback in a database and using it for future plan proposals; means for evaluating the contribution of platform participants and distributing revenue; means for using an API and web scraping to collect review information; and means for using a generative AI model to generate prompts based on the user's input information when generating a travel plan. This allows users to obtain efficient and accurate travel plans based on reliable information with little effort.

[0578] "Rating information" refers to data such as user ratings and comments, poster information, and posting date and time.

[0579] A "unified format" is a format that converts different evaluation scales into a common standard.

[0580] A "database" is a digital storage system for storing and managing evaluation information, feedback information, and the like.

[0581] An "interface" is a user interaction tool that allows users to input information such as hobbies, preferences, schedules, and budgets.

[0582] A "travel plan" is a plan including accommodations, places to eat, and tourist attractions that is generated based on information input by the user.

[0583] A "generative AI model" is an artificial intelligence algorithm that generates optimal travel plans based on user input information.

[0584] A "prompt sentence" is input text given to a generative AI model to guide the AI's response.

[0585] "Reservation Information" means the details required to reserve the travel plan selected by the User.

[0586] "Feedback" refers to ratings and comments provided by users after their travel or dining experiences.

[0587] "Contribution level" is an evaluation based on word-of-mouth information and number of reservations provided by companies participating in the platform.

[0588] "Web scraping" is a technique for automatically collecting data from web pages.

[0589] An "API" is an interface for exchanging functions and data between different software systems.

[0590] This invention is a system that collects and centrally manages word-of-mouth information from various rating sites and social media to help users efficiently plan trips and meals. This system is made up of a server, terminals, and user functions.

[0591] 1. Collecting and converting evaluation information

[0592] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. Specifically, it uses libraries such as Python's BeautifulSoup or Selenium to obtain data such as rating points, comments, poster information, and posting date and time from the Internet. If an API is provided, it is also possible to obtain the data directly using an HTTP request.

[0593] The server centrally manages the collected rating information and converts it into a unified format. Different rating scales, such as 5-point or 10-point ratings obtained from different rating sites, are converted into a common 10-point rating. This conversion is performed using the Python Pandas library, and the data is formatted in a unified format before being stored in a database.

[0594] 2. Providing a user interface

[0595] When a user accesses the device, it displays an interface built using HTML / CSS and JavaScript, providing a form for entering travel destination information, budget, itinerary, hobbies, and preferences.

[0596] Users enter search criteria through the device interface, such as "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," and then click the submit button.

[0597] 3. Analyzing user data and generating travel plans

[0598] The terminal sends the data entered by the user to the server. The terminal uses JavaScript AJAX to send the data entered by the user asynchronously to the server.

[0599] The server parses the user data and searches the database for matching reviews. It uses the SQLAlchemy library to execute database queries and extract data that matches the user's criteria.

[0600] The server generates the optimal travel plan for the user based on the search results. It uses machine learning libraries such as PyTorch and TensorFlow to provide prompt sentences to a generative AI model to generate the optimal plan.

[0601] Examples:

[0602] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model:

[0603] text

[0604] Purpose of trip: Hot spring trip

[0605] Budget: Under 20,000 yen per person

[0606] Dates: 3 days from September 10th

[0607] Please suggest a plan that includes highly rated hotels and restaurants.

[0608] 4. Reservation Procedure

[0609] The user checks the proposed plan and, if they wish to make a reservation, enters the reservation information on the interface. The user enters the reservation information in the form and clicks the submit button.

[0610] The server processes the reservation via the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is complete, the server sends reservation confirmation information to the terminal and notifies the user.

[0611] 5. Gathering feedback and improving the system

[0612] The server sends a feedback request message to the user after the trip or meal is completed, sending an email and providing a link to the feedback form.

[0613] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate subsequent plans.

[0614] The introduction of this system will enable travel and meal planning to be carried out efficiently and based on reliable information, allowing users to enjoy optimal plans with minimal effort. In addition, it will enable companies to properly evaluate and reflect their contributions, improving the overall quality of services.

[0615] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0616] Step 1:

[0617] The server collects rating information from various rating sites and social media. This collection is done using APIs or web scraping. Specifically, it uses Python's BeautifulSoup and Selenium to periodically retrieve data such as rating points, comments, poster information, and posting date and time. The input is the rating site or social media, and the output is a collection of the retrieved rating information.

[0618] Step 2:

[0619] The server converts the collected rating information into a unified format. Different rating scales, such as 5-point or 10-point ratings, obtained from different sites are converted into a 10-point rating. Specifically, the data is converted and unified using the Python Pandas library. The input is the collected rating information, and the output is the converted rating information in a unified format.

[0620] Step 3:

[0621] The server saves the rating information in a unified format to a database. It connects to the database using the SQLAlchemy library and saves the rating information. The input is the converted rating information in the unified format, and the output is the data saved in the database.

[0622] Step 4:

[0623] The terminal displays an interface when accessed by the user. The user interface is built using HTML / CSS and JavaScript and includes forms for entering travel destination information, budget, itinerary, hobbies, and preferences. The input is the information accessed by the user, and the output is the interface that is displayed.

[0624] Step 5:

[0625] The user inputs search criteria through the terminal interface. For example, "hot spring trip," "budget under 20,000 yen per person," and "3 days starting September 10th," and then clicks the send button. The input is the user's search criteria, and the output is the submitted search criteria data.

[0626] Step 6:

[0627] The terminal sends the data entered by the user to the server. Using JavaScript AJAX, the user's input data is sent asynchronously to the server. The input is the user's search criteria data, and the output is the data sent to the server.

[0628] Step 7:

[0629] The server parses the user data and searches the database for matching reviews. It uses SQLAlchemy to execute database queries and extract data that matches the user's criteria. The input is the user's search criteria data, and the output is the search results.

[0630] Step 8:

[0631] The server generates the optimal travel plan for the user based on the search results. Using machine learning libraries such as PyTorch and TensorFlow, the server generates the optimal plan by providing prompts to the generative AI model. The specific prompts are shown below.

[0632] Examples:

[0633] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model.

[0634] text

[0635] Purpose of trip: Hot spring trip

[0636] Budget: Under 20,000 yen per person

[0637] Dates: 3 days from September 10th

[0638] Please suggest a plan that includes highly rated hotels and restaurants.

[0639] Step 9:

[0640] If the user checks the proposed plan and wishes to make a reservation, they enter their reservation information on the interface. The user enters the reservation information into the form and clicks the submit button. The input is the user's reservation information, and the output is the submitted reservation information data.

[0641] Step 10:

[0642] The server processes reservations through the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user. The input is the user's reservation information, and the output is reservation confirmation information.

[0643] Step 11:

[0644] The server sends a feedback request message to the user after the trip or meal is completed. It sends an email and provides a link to the feedback form. The input is the trip or meal completion information, and the output is the feedback request message.

[0645] Step 12:

[0646] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate future plans. The input is the user's feedback, and the output is the feedback stored in the database.

[0647] (Application example 1)

[0648] 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."

[0649] Conventional food delivery systems have difficulty comprehensively collecting word-of-mouth information from a wide range of review sites and social media to propose optimal ordering plans based on users' preferences and budgets. Furthermore, because the information provided depends on the standards of each review site, the system relies on inconsistent reviews, making it difficult to propose accurate plans. Furthermore, continuous improvement of the system and fair revenue distribution are difficult due to insufficient collection of feedback after orders and evaluation of the contributions of platform participants.

[0650] 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.

[0651] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for storing the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a food order plan, means for presenting the generated food order plan to the user and collecting information on selected orders, means for completing the order in cooperation with each delivery service based on the order information, means for collecting feedback from the user after the food order is placed, means for storing the collected feedback in a database and using it for future proposals, and means for evaluating the contributions of platform participants and distributing revenue. This allows for the proposal of an optimal food order plan based on user requests, maintains consistency in review information, and also allows for post-order feedback and evaluation of the contributions of businesses.

[0652] "Evaluation information" refers to information such as user-provided evaluation points, comments, poster information, and posting date and time, which is collected from various evaluation sites and social media.

[0653] A "unified format" is a data format that converts evaluation information provided on different evaluation scales and formats into a form that can be compared using consistent standards.

[0654] A "database" is an information storage system for systematically storing and managing collected and converted evaluation information, user input information, feedback, etc.

[0655] An "interface" is an operation screen or input form provided for users to input information such as hobbies, preferences, schedules, and budgets.

[0656] The "Food Ordering Plan" is an optimal delivery plan based on the user's input information, including suggested delivery stores and menus, reviews, ordering procedures, etc.

[0657] "Order Information" refers to data required for the ordering process based on the food ordering plan selected by the user, such as the type of food, the number of items ordered, the delivery address, and contact information.

[0658] "Feedback" refers to reaction information such as impressions, ratings, and satisfaction levels provided by users after ordering food.

[0659] "Platform participating businesses" are companies and stores that participate in the food delivery system and provide evaluation information and delivery services.

[0660] "Contribution level" refers to the degree of contribution to the system, calculated based on the quality of services provided by platform participants, word-of-mouth reviews, number of orders, etc.

[0661] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan food delivery. This system is made up of the following functions: server, terminal, and user.

[0662] 1. Collecting and converting evaluation information

[0663] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, and posting date and time. Beautiful Soup is commonly used for web scraping. The collected data is then converted into a unified format (for example, converting different rating scales into a 10-point rating system).

[0664] 2. Data storage and management

[0665] The server stores the rating information in a standardized format in a database. This database stores collected reviews, user input, and feedback. It can be managed using a relational database service such as Amazon RDS.

[0666] 3. Providing a user interface

[0667] When accessed by a user, the terminal displays an interface that includes a form for inputting delivery type, budget, cuisine type, etc. Users can input search criteria through the terminal interface and plan specific orders.

[0668] 4. Analyzing user data and generating order plans

[0669] The terminal sends the data entered by the user to the server. The server analyzes the user data and searches for matching reviews in the database. The server generates the optimal food ordering plan for the user based on the search results. This plan includes menus and restaurants based on the user's tastes, preferences, and budget. Each plan is accompanied by reviews and comments, which are provided to the user in an easy-to-understand manner.

[0670] Examples:

[0671] When a user enters the criteria "sushi," "budget under 5,000 yen," and "high reviews," the server generates a plan that matches these criteria and suggests delivery restaurants and menus with high reviews.

[0672] 5. Order Processing

[0673] If the user reviews the proposed plan and wishes to place an order, they enter the necessary information on the interface. The order information entered by the user is sent to the server via the terminal. The server processes the order through the API of each delivery service based on the order information received from the user. Once the order is completed, the server sends order confirmation information to the terminal and notifies the user.

[0674] 6. Gathering feedback and improving the system

[0675] After the food order is completed, the server sends the user a message requesting feedback. The message includes a link to a feedback form, which the user can click to enter their thoughts. Once the user submits their feedback, the server stores it in its database, which can improve the accuracy of future suggestions.

[0676] 7. Evaluation of Platform Participants and Revenue Distribution

[0677] The server evaluates the contribution of the businesses participating in the platform and distributes revenue accordingly. For example, businesses that provide more word-of-mouth information or receive more orders are given higher contribution ratings, enabling fair revenue distribution.

[0678] This system allows users to obtain reliable information with minimal effort, simplifies the delivery ordering process, and allows for continuous improvement of the system through feedback.

[0679] Example prompt sentence:

[0680] "I'm looking for a sushi delivery service. My budget is under 5,000 yen. Can you recommend a place with good reviews?"

[0681] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0682] Step 1:

[0683] Collecting and converting evaluation information

[0684] The server periodically collects evaluation information from various evaluation sites and social media using APIs or web scraping.

[0685] Input: URLs of rating sites, social media, API keys, etc.

[0686] Data processing: Using Python scripts and Beautiful Soup, we extract the rating, comments, author information, and posting date and time from each page.

[0687] Output: Standardized format of the evaluation information data, including the converted evaluation scores into a 10-point scale.

[0688] Step 2:

[0689] Data storage and management

[0690] The server stores the collected and converted rating information in a database.

[0691] Input: Evaluation information data in a uniform format.

[0692] Data Computation and Storage: Use a relational database such as Amazon RDS to store the evaluation information in an organized manner.

[0693] Output: Evaluation information data stored in a database.

[0694] Step 3:

[0695] Providing a user interface

[0696] The terminal displays the interface when accessed by the user.

[0697] Input: User access.

[0698] How it works: It displays an interface built in Swift and Kotlin where users can input delivery type, budget, and cuisine type.

[0699] Output: The search criteria data entered by the user.

[0700] Step 4:

[0701] Analyzing user data and generating order plans

[0702] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[0703] Input: The search criteria data entered by the user.

[0704] Data calculation: Python scripts are used to search the database for matching reviews, and a search algorithm is used to generate the optimal food ordering plan.

[0705] Output: Optimal food ordering plan data.

[0706] Step 5:

[0707] Checkout

[0708] The user reviews the proposed plan and, if he / she wishes to place an order, enters the information required for the order on the interface.

[0709] Input: Optimal food ordering plan data and user order information.

[0710] Operation: Order information is sent to the server, and the order is processed on the server. An external API is used to connect with the delivery service.

[0711] Output: Order confirmation information.

[0712] Step 6:

[0713] Feedback collection and system improvement

[0714] The server will send a feedback request message to the user after the food order is completed, and once the user submits the feedback, the server will store the feedback in the database.

[0715] Input: Order confirmation information and user feedback information.

[0716] Data storage: Collected feedback information is stored in a database.

[0717] Output: Feedback data.

[0718] Step 7:

[0719] Evaluation of platform participants and revenue distribution

[0720] The server evaluates the contribution of the platform participants and distributes the revenue.

[0721] Input: Collected rating information, order data, feedback data.

[0722] Data calculation: Using a contribution evaluation algorithm, the contribution of each business operator is calculated and the percentage of revenue distribution is determined.

[0723] Output: Income distribution data.

[0724] 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.

[0725] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. It also combines an emotion engine that recognizes user emotions to improve customer satisfaction. This system is comprised of the following functions: server, terminal, and user.

[0726] 1. Collecting and converting evaluation information

[0727] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0728] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[0729] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0730] 2. Providing a user interface

[0731] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, etc. The device also sends the user's text input and voice data to the emotion engine.

[0732] The user inputs travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the terminal interface or by voice input.

[0733] 3. Emotion Recognition and Data Analysis

[0734] The device sends the user's input data and voice data to the emotion engine, which analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0735] The server records the emotion information sent from the emotion engine in a database and reflects it in generating travel plans for the user. For example, it may suggest plans that allow the user to relax or stay active based on the emotion information.

[0736] 4. Analyzing user data and generating travel plans

[0737] The terminal transmits the condition data and emotion information input by the user to the server.

[0738] The server searches the database based on the received user conditions and emotion information, and retrieves matching evaluation information.

[0739] The server then generates a personalized itinerary for the user based on the search results. The itinerary includes hotels, restaurants, and attractions, each with ratings and reviews. Each itinerary reflects the user's emotional state to ensure a context-optimized experience.

[0740] Examples:

[0741] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[0742] 5. Reservation Procedure

[0743] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0744] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0745] 6. Gathering feedback and improving the system

[0746] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0747] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0748] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[0749] ---

[0750] The system thus constructed ensures efficient and fair travel and dining planning, provides an optimal experience based on the user's emotional state, simplifies the overall booking process by providing reliable information with minimal effort, and continuously improves the system through feedback.

[0751] The processing flow will be explained below.

[0752] Step 1:

[0753] Subject: Server

[0754] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0755] Step 2:

[0756] Subject: Server

[0757] The server converts the collected rating information into a standardized format, for example, converting different rating scales such as 5-point and 10-point scales into a 10-point scale.

[0758] Step 3:

[0759] Subject: Server

[0760] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0761] Step 4:

[0762] Subject: Terminal

[0763] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, schedule, and hobbies and preferences.

[0764] Step 5:

[0765] Subject: User

[0766] Users input search criteria (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface, and also express their feelings through text or voice.

[0767] Step 6:

[0768] Subject: Terminal

[0769] The device sends the search criteria and voice data entered by the user to the emotion engine, which then analyzes the received text and voice data to recognize the user's emotions.

[0770] Step 7:

[0771] Subject: Server

[0772] The server records the emotion information sent from the emotion engine in a database and reflects it in generating a travel plan for the user.

[0773] Step 8:

[0774] Subject: Terminal

[0775] The device sends the information entered by the user and emotional information to the server in a data format such as JSON.

[0776] Step 9:

[0777] Subject: Server

[0778] The server searches the database for matching reviews based on the received user data, including the user's travel destination, budget, schedule, and emotional state.

[0779] Step 10:

[0780] Subject: Server

[0781] The server generates a travel plan optimized for the user based on the search results, including hotels, restaurants, and attractions with ratings and reviews, and reflects the user's emotional state.

[0782] Examples:

[0783] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[0784] Step 11:

[0785] Subject: Server

[0786] The server sends the generated travel plan to the terminal in JSON format or similar.

[0787] Step 12:

[0788] Subject: Terminal

[0789] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[0790] Step 13:

[0791] Subject: User

[0792] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact details, etc.) on the device interface.

[0793] Step 14:

[0794] Subject: Terminal

[0795] The terminal sends the reservation information entered by the user to the server in a data format such as JSON.

[0796] Step 15:

[0797] Subject: Server

[0798] The server executes the reservation through the API of each application site based on the received reservation information. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0799] Step 16:

[0800] Subject: Server

[0801] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[0802] Step 17:

[0803] Subject: User

[0804] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[0805] Step 18:

[0806] Subject: Server

[0807] The server stores the received feedback information in a database and uses it for future plan generation. Emotional information is also recorded as feedback.

[0808] Step 19:

[0809] Subject: Server

[0810] The server evaluates the contribution of each participating company based on reviews, booking history, and user satisfaction, and prepares revenue distribution data based on this.

[0811] Example 2

[0812] 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."

[0813] Conventional travel planning systems typically collect and analyze user evaluation information to make suggestions, but they do not reflect the user's emotional state during the actual trip, which means they are unable to fully increase user satisfaction. Furthermore, the booking process and feedback collection process are cumbersome, and there are still issues with the overall system efficiency.

[0814] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recognizing the emotional state from the user's input information using an emotion engine, means for recording the recognized emotional state in a database and reflecting it in the generation of a travel plan, and means for presenting the generated travel plan to the user and collecting reservation information for the selected plan. This makes it possible to propose an optimal travel plan based on the user's emotional state, significantly improving user satisfaction.

[0815] "Rating information" refers to word-of-mouth, reviews, ratings, poster information, posting date and time, etc. collected from various rating sites and social media.

[0816] An "emotion engine" refers to software or hardware that analyzes user input data (text or voice) and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0817] "Interface" refers to the display screen and operating means through which users access the system and input information such as hobbies, preferences, schedule, budget, and travel destinations.

[0818] "Travel Plan" refers to a plan that includes suggestions for accommodation, places to eat, attractions, etc. based on the user's input information and perceived emotional state.

[0819] "Database" refers to a system for storing and managing collected evaluation information, emotional information, user input information, feedback, etc.

[0820] "Feedback" refers to the impressions and evaluation information provided by users after traveling or eating.

[0821] "Platform participating companies" refer to companies that provide information and services to the system and contribute to the operation of the system.

[0822] "Contribution" refers to the degree to which platform participating companies are evaluated based on the quality and quantity of evaluation information they provide to the system, the number of reservations processed, etc.

[0823] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system aims to improve customer satisfaction. The system of the present invention is made up of the following functions: server, terminal, and user.

[0824] 1. Collecting and converting evaluation information

[0825] The server periodically collects evaluation information using APIs or web scraping functions from various evaluation sites and social media. The collected data includes evaluation scores, comments, poster information, posting date and time, etc. The necessary information is extracted from the HTML data of the evaluation sites using the Python library "BeautifulSoup" and other tools.

[0826] The server then converts the collected rating information into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale, allowing data collected from different sites to be stored in a consistent format.

[0827] Finally, the server stores the rating information in a standardized format in a MySQL database, including the rating score, review content, site name, and posting date and time.

[0828] 2. Providing a user interface

[0829] When a user accesses the device, an interface is displayed for entering information such as travel destination, budget, schedule, hobbies, and preferences. This interface is built using HTML / CSS and JavaScript. Users can enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" in the text boxes.

[0830] 3. Emotion Recognition and Data Analysis

[0831] The device sends the data entered by the user and voice data to the emotion engine, which then analyzes the received data using, for example, IBM Watson's emotion analysis API, and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[0832] The server records the emotion information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores information such as "Relaxed" in the "Emotional State" field.

[0833] 4. Analyzing user data and generating travel plans

[0834] The device sends the user's input criteria data and emotion information to the server. The server searches the database based on the received user criteria and emotion information to obtain matching rating information. The server then generates an optimal travel plan for the user based on the search results. This plan includes hotels, restaurants, and tourist attractions, each with its own rating and review content.

[0835] As a concrete example, if a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes a highly rated hot spring hotel and a quiet, relaxing place to eat.

[0836] 5. Reservation Procedure

[0837] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0838] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0839] 6. Gathering feedback and improving the system

[0840] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0841] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0842] The system also has a means of evaluating the contribution of companies participating in the platform and distributing income. For example, a system is in place that gives higher contribution points to companies that provide more word-of-mouth information or receive more reservations.

[0843] Prompt Sentence Examples

[0844] "I want to relax. Can you plan a three-day hot spring trip starting September 10th? My budget is under 20,000 yen per person."

[0845] "I'm planning a family trip. Can you recommend some good places to eat? My budget is 30,000 yen."

[0846] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0847] Step 1: Gather evaluation information

[0848] The server collects review information using APIs or web scraping functions from various review sites and social media. Specifically, it uses the Python library "BeautifulSoup" to parse HTML data from a specified URL and extract word-of-mouth information. The input is the URL of the review site and a query, and the output is review information such as rating points, comments, poster information, and posting date and time.

[0849] Step 2: Standardize data formats

[0850] The server converts the collected rating information into a standardized format. For example, it unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating. Specifically, it doubles each rating point to convert a 5-point rating into a 10-point rating. The input is the collected rating information, and the output is rating information in a standardized format.

[0851] Step 3: Save your data

[0852] The server stores the rating information in a standardized format in a database. Specifically, it uses a MySQL database to store records including rating points, review content, site name, and posting date and time. The input is rating information in a standardized format, and the output is the record stored in the database.

[0853] Step 4: Displaying the User Interface

[0854] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences. Specifically, it displays a web form built using HTML / CSS and JavaScript. The input is the user's access, and the output is the display of the input form.

[0855] Step 5: Entering User Data

[0856] The user inputs travel conditions (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface. For example, the user might enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" into text boxes. Input is the information the user types into the device, and output is the input data displayed on the device.

[0857] Step 6: Sending Emotion Data

[0858] The device sends the data and voice data entered by the user to the emotion engine. Specifically, the entered text data and voice data is sent to the IBM Watson emotion analysis API. The input is the user's input data, and the output is the data sent to the emotion engine.

[0859] Step 7: Recognize emotions

[0860] The emotion engine analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.). For example, it recognizes the "positive" emotion from the text "I want to relax." The input is the transmitted data, and the output is the recognized emotional state data.

[0861] Step 8: Storing Emotional Information

[0862] The server records the emotional information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores "Relaxed" in the "Emotional State" field. The input is the recognized emotional state data, and the output is the emotional information stored in the database.

[0863] Step 9: Sending condition data

[0864] The device sends the condition data and emotional information entered by the user to the server. Specifically, the user's condition data (e.g., travel destination, budget, schedule, hobbies, and preferences) and emotional information are sent via API. The input is the condition data and emotional information entered into the device, and the output is the data sent to the server.

[0865] Step 10: Search the database

[0866] The server searches the database based on the received user criteria and emotion information to retrieve matching rating information. Specifically, it uses an SQL query to search for records of hotels and tourist attractions that match the criteria. The input is the user's criteria data and emotion information, and the output is the search result records.

[0867] Step 11: Generate a travel plan

[0868] The server generates an optimal travel plan for the user based on the search results. Specifically, it creates a plan that includes highly rated hot spring hotels and quiet dining spots, and attaches their ratings and reviews. The input is the search result records, and the output is the generated travel plan.

[0869] Step 12: Present your travel plans

[0870] The terminal presents the generated itinerary to the user. Specifically, it generates a web page displaying the details of the itinerary and displays it to the user. The input is the itinerary sent from the server, and the output is the itinerary presented to the user.

[0871] Step 13: Enter reservation information

[0872] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The input is the user's personal information, and the output is the reservation information displayed on the terminal.

[0873] Step 14: Complete the booking process

[0874] The server processes reservations through the API of each application site based on the reservation information received from the user. Specifically, it uses the API of the travel reservation site to make reservations according to the specified conditions. The input is the user's reservation information, and the output is confirmation data that the reservation has been completed.

[0875] Step 15: Notification of reservation confirmation information

[0876] When the reservation is completed, the server sends the reservation confirmation information to the terminal and notifies the user. Specifically, it generates a reservation confirmation email and sends it to the user's email address. The input is the confirmation data of the reservation completion, and the output is the reservation confirmation information notified to the user.

[0877] Step 16: Submit a feedback request

[0878] After the trip or meal is completed, the server sends a feedback request message to the user. Specifically, it sends an automated email with the message "Please tell us what you thought of your trip." The input is the user's email address, and the output is the sent feedback request message.

[0879] Step 17: Submit and save your feedback

[0880] When a user submits feedback, the server stores the feedback in a database. Specifically, when a user fills out an input form and clicks the "Submit" button, the data is stored in a MySQL database. The input is the user's feedback, and the output is the feedback stored in the database.

[0881] Step 18: System Improvement

[0882] The server uses the collected feedback to improve the accuracy of future plan suggestions. Specifically, it adjusts the recommendation algorithm through feedback analysis and processes data to further increase user satisfaction. The input is the stored feedback, and the output is an improved algorithm and proposed plans.

[0883] (Application example 2)

[0884] 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."

[0885] When shopping online or planning trips and meals, it takes time and effort for users to collect reviews and find the best products and plans for themselves. Furthermore, conventional recommendation systems do not take into account the user's emotional state, making it difficult to improve customer satisfaction. Therefore, there is a need for systems that can easily find the best products and plans based on the user's emotional state and streamline the purchasing and reservation process.

[0886] 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.

[0887] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for saving the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a travel plan, means for presenting the generated travel plan to the user and collecting reservation information for the selected plan, means for completing the reservation in cooperation with each application site based on the reservation information, means for collecting feedback from the user after the trip or meal, means for saving the collected feedback in a database and using it for future plan proposals, means for evaluating the contributions of platform participating companies and distributing revenue, means for analyzing the user's emotional state using an emotion engine and saving it in a database together with the review information, means for generating product recommendation information based on the user's emotional state, means for presenting the generated recommendation information to the user and collecting purchase information for the selected product, and means for completing the purchase in cooperation with each sales site based on the purchase information. This allows users to easily find the best products and travel plans based on their emotional state and efficiently complete the purchase and reservation process.

[0888] "Evaluation information" refers to information such as evaluation scores and comments collected from various evaluation sites and social media.

[0889] A "unified format" is a data format that standardizes different evaluation scales and formats and converts them into a consistent format.

[0890] A "database" is a storage device for systematically storing collected and unified evaluation information and additional information.

[0891] An "interface" is a screen or element through which a user inputs information into a device or receives information from a system.

[0892] An "emotion engine" is a technology that analyzes user input information and voice data to recognize the user's emotional state.

[0893] "Recommendation information" is information that suggests optimal products, travel plans, etc. based on the user's hobbies, preferences, and emotional state.

[0894] "Reservation Information" refers to information including personal information and conditions necessary to reserve the plan or product selected by the user.

[0895] A "merchandise site" is a website or platform that offers products or services and accepts online purchases.

[0896] "Feedback" refers to information such as impressions, ratings, and opinions provided by users after traveling or using a product.

[0897] "Platform participating companies" are companies that provide evaluation information and services to this system and are involved in system operation.

[0898] The system of the present invention recommends optimal products and travel plans based on the user's hobbies, preferences, schedule, budget, and emotional state, and then efficiently processes the subsequent purchase and reservation procedures. Specific implementation methods of the system are described below.

[0899] 1. Collecting and converting evaluation information

[0900] The server periodically collects rating information using APIs or web scraping functions from various rating sites and social media. For example, information can be obtained using Python's BeautifulSoup or requests library. The collected data is converted into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale. The data is then stored in a relational database such as MySQL or PostgreSQL.

[0901] 2. Providing a user interface

[0902] The device uses a cross-platform UI framework such as Flutter to display an interface for users to enter their hobbies, preferences, schedule, budget, and emotional state. The device then sends the user's text input data to a natural language processing engine such as Google Dialogflow, which then receives the input information.

[0903] 3. Emotion Recognition and Data Analysis

[0904] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize the user's emotional state (e.g., joy, sadness, surprise, etc.). The analyzed emotion information is sent to a server and recorded in a database.

[0905] 4. Analyzing user data and generating recommendations

[0906] The server searches the database based on the user's input criteria and emotional information to retrieve matching rating information. This is done using data analysis tools such as Python, Pandas, and Elasticsearch. Based on the search results, an algorithm is run to generate products and travel plans that best fit the user's emotional state.

[0907] 5. Present the generated recommendation information and process purchases and reservations

[0908] The device presents the generated recommendation information to the user and collects purchase information for the products selected by the user and reservation information for the travel plan. The purchase or reservation information is sent to the server, and the purchase or reservation process is carried out via the API of each sales site or application site. Reservation or purchase confirmation information is sent to the device and notified to the user.

[0909] 6. Gathering feedback and improving the system

[0910] After a purchase or trip is completed, the server sends a message to the user requesting feedback. The user enters their feedback and the submitted information is stored in a database and used to propose plans for the next trip.

[0911] Hardware and software used

[0912] Server hardware: AWS EC2, RDS

[0913] Device hardware: iOS or Android device

[0914] Software: Python, BeautifulSoup, requests, Flutter, Google Dialogflow, IBM Watson, Google Cloud Natural Language API, Pandas, Elasticsearch, Django, SQLAlchemy, REST API

[0915] Specific examples

[0916] If a user is in an emotional state such as "I've been busy lately and want to relax," and enters the conditions "relaxation products," "budget of 5,000 yen or less," and "interested in aroma-related products," the system will recommend highly rated aroma diffusers and relaxation CDs.

[0917] Prompt Sentence Examples

[0918] Please recommend the best products to users whose current emotional state is "I want to be soothed," who are interested in "aroma-related products," and whose budget is "within 5,000 yen." Please select products that will help users relax, taking into account product reviews and sentiment analysis results.

[0919] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0920] Step 1:

[0921] Collecting and converting evaluation information

[0922] The server periodically collects rating information using various rating sites, social media APIs, or web scraping functions. Specifically, it acquires information using Python's BeautifulSoup and requests libraries. Input data includes rating points, comments, poster information, posting date and time, etc. This is converted into a standardized format, and different rating scales (e.g., 5-point rating, 10-point rating, etc.) are unified and converted into a 10-point rating. The output data is rating information in a standardized format.

[0923] Step 2:

[0924] Saving rating information

[0925] The server stores the rating information in a unified format in a database. Specifically, it uses a relational database such as MySQL or PostgreSQL. The input data includes rating points, review content, site name, posting date and time, etc., and storing this data makes it easier to search and analyze later. The output includes structured rating information in the database.

[0926] Step 3:

[0927] Providing a user interface

[0928] The device uses Flutter to display an interface for users to input their hobbies, preferences, schedule, budget, and emotional state when accessed by the user. The input data is the condition information entered by the user, which is received and sent to the server. The output is the condition data entered by the user.

[0929] Step 4:

[0930] Emotion Recognition and Data Analysis

[0931] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize emotional states (e.g., joy, sadness, surprise, etc.). The input data is the user's text and voice data, and after analysis, emotional information is output and sent to the server.

[0932] Step 5:

[0933] Analyzing user data and generating recommendations

[0934] The server searches the database based on the input criteria data and emotion information to obtain matching rating information. It processes the data using data analysis tools such as Python, Pandas, and Elasticsearch. The input data are the user's criteria data and emotion information, and the output is recommendation information based on the user's emotional state.

[0935] Step 6:

[0936] Present generated recommendation information and process purchases and reservations

[0937] The terminal presents the user with recommended products and travel plans and receives the user's selection. Purchase information for the products and reservation information for the travel plans selected by the user is collected and sent from the terminal to the server. The output is the purchase information and reservation information selected by the user. Based on this information, the server processes the purchase and reservation via the APIs of each sales site and application site. Purchase confirmation and reservation confirmation information are sent to the terminal and notified to the user.

[0938] Step 7:

[0939] Gathering feedback and improving the system

[0940] After a purchase or trip is completed, the server sends a message to the user requesting feedback. When the user inputs and submits feedback, the information is stored in the database. The input data is the user's feedback, and the output data is the feedback information stored in the database. This allows for improved accuracy of future plan suggestions.

[0941] 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.

[0942] 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.

[0943] 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.

[0944] [Third embodiment]

[0945] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0946] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0947] 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).

[0948] 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.

[0949] 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.

[0950] 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).

[0951] 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.

[0952] 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.

[0953] 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.

[0954] 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.

[0955] 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.

[0956] 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."

[0957] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan trips and meals. This system is made up of the following functions: server, terminal, and user.

[0958] 1. Collecting and converting evaluation information

[0959] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, posting date and time, etc.

[0960] The server centrally manages the collected evaluation information and converts it into a unified format. For example, it converts different evaluation scales such as 5-point and 10-point ratings into a 10-point rating. It also stores each evaluation information in a database.

[0961] 2. Providing a user interface

[0962] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, itinerary, and hobbies and preferences.

[0963] Users input search criteria through the device interface, such as the purpose of their trip, the area they want to visit, their budget, and the duration of their trip.

[0964] 3. Analyzing user data and generating travel plans

[0965] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[0966] The server then generates a travel plan that best suits the user based on the search results. This plan includes hotels, restaurants, and tourist attractions based on the user's preferences and budget. Each plan is accompanied by reviews and comments, making it easy for the user to understand.

[0967] Examples:

[0968] When a user enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server generates a plan that matches these conditions and suggests a travel plan that includes highly rated hotels and restaurants.

[0969] 4. Reservation Procedure

[0970] If the user checks the proposed plan and wishes to make a reservation, they enter the necessary information on the interface. The reservation information entered by the user is sent to the server via the terminal.

[0971] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[0972] 5. Gathering feedback and improving the system

[0973] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[0974] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[0975] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[0976] ---

[0977] This system makes travel and dining planning efficient and fair, providing users with reliable information with minimal effort, simplifying the overall booking process, and enabling continuous improvement through feedback.

[0978] The processing flow will be explained below.

[0979] Step 1:

[0980] Subject: Server

[0981] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[0982] Step 2:

[0983] Subject: Server

[0984] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[0985] Step 3:

[0986] Subject: Server

[0987] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[0988] Step 4:

[0989] Subject: Terminal

[0990] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences.

[0991] Step 5:

[0992] Subject: User

[0993] The user enters the travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the device interface and clicks the "Submit" button.

[0994] Step 6:

[0995] Subject: Terminal

[0996] The terminal sends the information entered by the user to the server in a data format such as JSON.

[0997] Step 7:

[0998] Subject: Server

[0999] The server searches the database based on the received user conditions and retrieves matching evaluation information.

[1000] Step 8:

[1001] Subject: Server

[1002] The server generates a personalized itinerary for the user based on the search results, including hotels, dining options, and attractions, all with ratings and reviews.

[1003] Step 9:

[1004] Subject: Server

[1005] The server sends the generated travel plan to the terminal in JSON format or similar.

[1006] Step 10:

[1007] Subject: Terminal

[1008] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[1009] Step 11:

[1010] Subject: User

[1011] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the terminal.

[1012] Step 12:

[1013] Subject: Terminal

[1014] The terminal sends the reservation information entered by the user to the server in JSON format or similar.

[1015] Step 13:

[1016] Subject: Server

[1017] The server connects the received reservation information through the API of each application site and executes the reservation.

[1018] Step 14:

[1019] Subject: Server

[1020] When the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1021] Step 15:

[1022] Subject: Server

[1023] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[1024] Step 16:

[1025] Subject: User

[1026] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[1027] Step 17:

[1028] Subject: Server

[1029] The server stores the received feedback information in a database and uses it for subsequent plan generation.

[1030] Step 18:

[1031] Subject: Server

[1032] The server evaluates the contribution of each participating company based on reviews and booking history, and prepares revenue distribution data.

[1033] Example 1

[1034] 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."

[1035] Traditional travel and dining planning requires users to individually research multiple online review sites and social media, which can often be inefficient. Furthermore, the lack of a unified rating scale across different review sites makes it difficult to make proper comparisons. Furthermore, there are few systems that automatically generate optimal travel plans tailored to a user's specific needs and budget, and the booking process can be complicated and time-consuming. As a result, users often end up with unsatisfactory plans despite the significant effort required.

[1036] 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.

[1037] In this invention, the server includes: means for collecting review information from various review sites and social media; means for converting the collected review information into a unified format; means for saving the unified format review information in a database; means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget; means for searching the database for matching review information based on the input information and generating a travel plan; means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; means for completing the reservation by connecting with each application site based on the reservation information; means for collecting feedback from the user after the trip or meal; means for saving the collected feedback in a database and using it for future plan proposals; means for evaluating the contribution of platform participants and distributing revenue; means for using an API and web scraping to collect review information; and means for using a generative AI model to generate prompts based on the user's input information when generating a travel plan. This allows users to obtain efficient and accurate travel plans based on reliable information with little effort.

[1038] "Rating information" refers to data such as user ratings and comments, poster information, and posting date and time.

[1039] A "unified format" is a format that converts different evaluation scales into a common standard.

[1040] A "database" is a digital storage system for storing and managing evaluation information, feedback information, and the like.

[1041] An "interface" is a user interaction tool that allows users to input information such as hobbies, preferences, schedules, and budgets.

[1042] A "travel plan" is a plan including accommodations, places to eat, and tourist attractions that is generated based on information input by the user.

[1043] A "generative AI model" is an artificial intelligence algorithm that generates optimal travel plans based on user input information.

[1044] A "prompt sentence" is input text given to a generative AI model to guide the AI's response.

[1045] "Reservation Information" means the details required to reserve the travel plan selected by the User.

[1046] "Feedback" refers to ratings and comments provided by users after their travel or dining experiences.

[1047] "Contribution level" is an evaluation based on word-of-mouth information and number of reservations provided by companies participating in the platform.

[1048] "Web scraping" is a technique for automatically collecting data from web pages.

[1049] An "API" is an interface for exchanging functions and data between different software systems.

[1050] This invention is a system that collects and centrally manages word-of-mouth information from various rating sites and social media to help users efficiently plan trips and meals. This system is made up of a server, terminals, and user functions.

[1051] 1. Collecting and converting evaluation information

[1052] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. Specifically, it uses libraries such as Python's BeautifulSoup or Selenium to obtain data such as rating points, comments, poster information, and posting date and time from the Internet. If an API is provided, it is also possible to obtain the data directly using an HTTP request.

[1053] The server centrally manages the collected rating information and converts it into a unified format. Different rating scales, such as 5-point or 10-point ratings obtained from different rating sites, are converted into a common 10-point rating. This conversion is performed using the Python Pandas library, and the data is formatted in a unified format before being stored in a database.

[1054] 2. Providing a user interface

[1055] When a user accesses the device, it displays an interface built using HTML / CSS and JavaScript, providing a form for entering travel destination information, budget, itinerary, hobbies, and preferences.

[1056] Users enter search criteria through the device interface, such as "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," and then click the submit button.

[1057] 3. Analyzing user data and generating travel plans

[1058] The terminal sends the data entered by the user to the server. The terminal uses JavaScript AJAX to send the data entered by the user asynchronously to the server.

[1059] The server parses the user data and searches the database for matching reviews. It uses the SQLAlchemy library to execute database queries and extract data that matches the user's criteria.

[1060] The server generates the optimal travel plan for the user based on the search results. It uses machine learning libraries such as PyTorch and TensorFlow to provide prompt sentences to a generative AI model to generate the optimal plan.

[1061] Examples:

[1062] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model:

[1063] text

[1064] Purpose of trip: Hot spring trip

[1065] Budget: Under 20,000 yen per person

[1066] Dates: 3 days from September 10th

[1067] Please suggest a plan that includes highly rated hotels and restaurants.

[1068] 4. Reservation Procedure

[1069] The user checks the proposed plan and, if they wish to make a reservation, enters the reservation information on the interface. The user enters the reservation information in the form and clicks the submit button.

[1070] The server processes the reservation via the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is complete, the server sends reservation confirmation information to the terminal and notifies the user.

[1071] 5. Gathering feedback and improving the system

[1072] The server sends a feedback request message to the user after the trip or meal is completed, sending an email and providing a link to the feedback form.

[1073] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate subsequent plans.

[1074] The introduction of this system will enable travel and meal planning to be carried out efficiently and based on reliable information, allowing users to enjoy optimal plans with minimal effort. In addition, it will enable companies to properly evaluate and reflect their contributions, improving the overall quality of services.

[1075] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1076] Step 1:

[1077] The server collects rating information from various rating sites and social media. This collection is done using APIs or web scraping. Specifically, it uses Python's BeautifulSoup and Selenium to periodically retrieve data such as rating points, comments, poster information, and posting date and time. The input is the rating site or social media, and the output is a collection of the retrieved rating information.

[1078] Step 2:

[1079] The server converts the collected rating information into a unified format. Different rating scales, such as 5-point or 10-point ratings, obtained from different sites are converted into a 10-point rating. Specifically, the data is converted and unified using the Python Pandas library. The input is the collected rating information, and the output is the converted rating information in a unified format.

[1080] Step 3:

[1081] The server saves the rating information in a unified format to a database. It connects to the database using the SQLAlchemy library and saves the rating information. The input is the converted rating information in the unified format, and the output is the data saved in the database.

[1082] Step 4:

[1083] The terminal displays an interface when accessed by the user. The user interface is built using HTML / CSS and JavaScript and includes forms for entering travel destination information, budget, itinerary, hobbies, and preferences. The input is the information accessed by the user, and the output is the interface that is displayed.

[1084] Step 5:

[1085] The user inputs search criteria through the terminal interface. For example, "hot spring trip," "budget under 20,000 yen per person," and "3 days starting September 10th," and then clicks the send button. The input is the user's search criteria, and the output is the submitted search criteria data.

[1086] Step 6:

[1087] The terminal sends the data entered by the user to the server. Using JavaScript AJAX, the user's input data is sent asynchronously to the server. The input is the user's search criteria data, and the output is the data sent to the server.

[1088] Step 7:

[1089] The server parses the user data and searches the database for matching reviews. It uses SQLAlchemy to execute database queries and extract data that matches the user's criteria. The input is the user's search criteria data, and the output is the search results.

[1090] Step 8:

[1091] The server generates the optimal travel plan for the user based on the search results. Using machine learning libraries such as PyTorch and TensorFlow, the server generates the optimal plan by providing prompts to the generative AI model. The specific prompts are shown below.

[1092] Examples:

[1093] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model.

[1094] text

[1095] Purpose of trip: Hot spring trip

[1096] Budget: Under 20,000 yen per person

[1097] Dates: 3 days from September 10th

[1098] Please suggest a plan that includes highly rated hotels and restaurants.

[1099] Step 9:

[1100] If the user checks the proposed plan and wishes to make a reservation, they enter their reservation information on the interface. The user enters the reservation information into the form and clicks the submit button. The input is the user's reservation information, and the output is the submitted reservation information data.

[1101] Step 10:

[1102] The server processes reservations through the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user. The input is the user's reservation information, and the output is reservation confirmation information.

[1103] Step 11:

[1104] The server sends a feedback request message to the user after the trip or meal is completed. It sends an email and provides a link to the feedback form. The input is the trip or meal completion information, and the output is the feedback request message.

[1105] Step 12:

[1106] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate future plans. The input is the user's feedback, and the output is the feedback stored in the database.

[1107] (Application example 1)

[1108] 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."

[1109] Conventional food delivery systems have difficulty comprehensively collecting word-of-mouth information from a wide range of review sites and social media to propose optimal ordering plans based on users' preferences and budgets. Furthermore, because the information provided depends on the standards of each review site, the system relies on inconsistent reviews, making it difficult to propose accurate plans. Furthermore, continuous improvement of the system and fair revenue distribution are difficult due to insufficient collection of feedback after orders and evaluation of the contributions of platform participants.

[1110] 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.

[1111] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for storing the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a food order plan, means for presenting the generated food order plan to the user and collecting information on selected orders, means for completing the order in cooperation with each delivery service based on the order information, means for collecting feedback from the user after the food order is placed, means for storing the collected feedback in a database and using it for future proposals, and means for evaluating the contributions of platform participants and distributing revenue. This allows for the proposal of an optimal food order plan based on user requests, maintains consistency in review information, and also allows for post-order feedback and evaluation of the contributions of businesses.

[1112] "Evaluation information" refers to information such as user-provided evaluation points, comments, poster information, and posting date and time, which is collected from various evaluation sites and social media.

[1113] A "unified format" is a data format that converts evaluation information provided on different evaluation scales and formats into a form that can be compared using consistent standards.

[1114] A "database" is an information storage system for systematically storing and managing collected and converted evaluation information, user input information, feedback, etc.

[1115] An "interface" is an operation screen or input form provided for users to input information such as hobbies, preferences, schedules, and budgets.

[1116] The "Food Ordering Plan" is an optimal delivery plan based on the user's input information, including suggested delivery stores and menus, reviews, ordering procedures, etc.

[1117] "Order Information" refers to data required for the ordering process based on the food ordering plan selected by the user, such as the type of food, the number of items ordered, the delivery address, and contact information.

[1118] "Feedback" refers to reaction information such as impressions, ratings, and satisfaction levels provided by users after ordering food.

[1119] "Platform participating businesses" are companies and stores that participate in the food delivery system and provide evaluation information and delivery services.

[1120] "Contribution level" refers to the degree of contribution to the system, calculated based on the quality of services provided by platform participants, word-of-mouth reviews, number of orders, etc.

[1121] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan food delivery. This system is made up of the following functions: server, terminal, and user.

[1122] 1. Collecting and converting evaluation information

[1123] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, and posting date and time. Beautiful Soup is commonly used for web scraping. The collected data is then converted into a unified format (for example, converting different rating scales into a 10-point rating system).

[1124] 2. Data storage and management

[1125] The server stores the rating information in a standardized format in a database. This database stores collected reviews, user input, and feedback. It can be managed using a relational database service such as Amazon RDS.

[1126] 3. Providing a user interface

[1127] When accessed by a user, the terminal displays an interface that includes a form for inputting delivery type, budget, cuisine type, etc. Users can input search criteria through the terminal interface and plan specific orders.

[1128] 4. Analyzing user data and generating order plans

[1129] The terminal sends the data entered by the user to the server. The server analyzes the user data and searches for matching reviews in the database. The server generates the optimal food ordering plan for the user based on the search results. This plan includes menus and restaurants based on the user's tastes, preferences, and budget. Each plan is accompanied by reviews and comments, which are provided to the user in an easy-to-understand manner.

[1130] Examples:

[1131] When a user enters the criteria "sushi," "budget under 5,000 yen," and "high reviews," the server generates a plan that matches these criteria and suggests delivery restaurants and menus with high reviews.

[1132] 5. Order Processing

[1133] If the user reviews the proposed plan and wishes to place an order, they enter the necessary information on the interface. The order information entered by the user is sent to the server via the terminal. The server processes the order through the API of each delivery service based on the order information received from the user. Once the order is completed, the server sends order confirmation information to the terminal and notifies the user.

[1134] 6. Gathering feedback and improving the system

[1135] After the food order is completed, the server sends the user a message requesting feedback. The message includes a link to a feedback form, which the user can click to enter their thoughts. Once the user submits their feedback, the server stores it in its database, which can improve the accuracy of future suggestions.

[1136] 7. Evaluation of Platform Participants and Revenue Distribution

[1137] The server evaluates the contribution of the businesses participating in the platform and distributes revenue accordingly. For example, businesses that provide more word-of-mouth information or receive more orders are given higher contribution ratings, enabling fair revenue distribution.

[1138] This system allows users to obtain reliable information with minimal effort, simplifies the delivery ordering process, and allows for continuous improvement of the system through feedback.

[1139] Example prompt sentence:

[1140] "I'm looking for a sushi delivery service. My budget is under 5,000 yen. Can you recommend a place with good reviews?"

[1141] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1142] Step 1:

[1143] Collecting and converting evaluation information

[1144] The server periodically collects evaluation information from various evaluation sites and social media using APIs or web scraping.

[1145] Input: URLs of rating sites, social media, API keys, etc.

[1146] Data processing: Using Python scripts and Beautiful Soup, we extract the rating, comments, author information, and posting date and time from each page.

[1147] Output: Standardized format of the evaluation information data, including the converted evaluation scores into a 10-point scale.

[1148] Step 2:

[1149] Data storage and management

[1150] The server stores the collected and converted rating information in a database.

[1151] Input: Evaluation information data in a uniform format.

[1152] Data Computation and Storage: Use a relational database such as Amazon RDS to store the evaluation information in an organized manner.

[1153] Output: Evaluation information data stored in a database.

[1154] Step 3:

[1155] Providing a user interface

[1156] The terminal displays the interface when accessed by the user.

[1157] Input: User access.

[1158] How it works: It displays an interface built in Swift and Kotlin where users can input delivery type, budget, and cuisine type.

[1159] Output: The search criteria data entered by the user.

[1160] Step 4:

[1161] Analyzing user data and generating order plans

[1162] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[1163] Input: The search criteria data entered by the user.

[1164] Data calculation: Python scripts are used to search the database for matching reviews, and a search algorithm is used to generate the optimal food ordering plan.

[1165] Output: Optimal food ordering plan data.

[1166] Step 5:

[1167] Checkout

[1168] The user reviews the proposed plan and, if he / she wishes to place an order, enters the information required for the order on the interface.

[1169] Input: Optimal food ordering plan data and user order information.

[1170] Operation: Order information is sent to the server, and the order is processed on the server. An external API is used to connect with the delivery service.

[1171] Output: Order confirmation information.

[1172] Step 6:

[1173] Feedback collection and system improvement

[1174] The server will send a feedback request message to the user after the food order is completed, and once the user submits the feedback, the server will store the feedback in the database.

[1175] Input: Order confirmation information and user feedback information.

[1176] Data storage: Collected feedback information is stored in a database.

[1177] Output: Feedback data.

[1178] Step 7:

[1179] Evaluation of platform participants and revenue distribution

[1180] The server evaluates the contribution of the platform participants and distributes the revenue.

[1181] Input: Collected rating information, order data, feedback data.

[1182] Data calculation: Using a contribution evaluation algorithm, the contribution of each business operator is calculated and the percentage of revenue distribution is determined.

[1183] Output: Income distribution data.

[1184] 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.

[1185] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. It also combines an emotion engine that recognizes user emotions to improve customer satisfaction. This system is comprised of the following functions: server, terminal, and user.

[1186] 1. Collecting and converting evaluation information

[1187] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[1188] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[1189] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[1190] 2. Providing a user interface

[1191] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, etc. The device also sends the user's text input and voice data to the emotion engine.

[1192] The user inputs travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the terminal interface or by voice input.

[1193] 3. Emotion Recognition and Data Analysis

[1194] The device sends the user's input data and voice data to the emotion engine, which analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1195] The server records the emotion information sent from the emotion engine in a database and reflects it in generating travel plans for the user. For example, it may suggest plans that allow the user to relax or stay active based on the emotion information.

[1196] 4. Analyzing user data and generating travel plans

[1197] The terminal transmits the condition data and emotion information input by the user to the server.

[1198] The server searches the database based on the received user conditions and emotion information, and retrieves matching evaluation information.

[1199] The server then generates a personalized itinerary for the user based on the search results. The itinerary includes hotels, restaurants, and attractions, each with ratings and reviews. Each itinerary reflects the user's emotional state to ensure a context-optimized experience.

[1200] Examples:

[1201] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[1202] 5. Reservation Procedure

[1203] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[1204] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1205] 6. Gathering feedback and improving the system

[1206] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[1207] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[1208] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[1209] ---

[1210] The system thus constructed ensures efficient and fair travel and dining planning, provides an optimal experience based on the user's emotional state, simplifies the overall booking process by providing reliable information with minimal effort, and continuously improves the system through feedback.

[1211] The processing flow will be explained below.

[1212] Step 1:

[1213] Subject: Server

[1214] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[1215] Step 2:

[1216] Subject: Server

[1217] The server converts the collected rating information into a standardized format, for example, converting different rating scales such as 5-point and 10-point scales into a 10-point scale.

[1218] Step 3:

[1219] Subject: Server

[1220] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[1221] Step 4:

[1222] Subject: Terminal

[1223] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, schedule, and hobbies and preferences.

[1224] Step 5:

[1225] Subject: User

[1226] Users input search criteria (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface, and also express their feelings through text or voice.

[1227] Step 6:

[1228] Subject: Terminal

[1229] The device sends the search criteria and voice data entered by the user to the emotion engine, which then analyzes the received text and voice data to recognize the user's emotions.

[1230] Step 7:

[1231] Subject: Server

[1232] The server records the emotion information sent from the emotion engine in a database and reflects it in generating a travel plan for the user.

[1233] Step 8:

[1234] Subject: Terminal

[1235] The device sends the information entered by the user and emotional information to the server in a data format such as JSON.

[1236] Step 9:

[1237] Subject: Server

[1238] The server searches the database for matching reviews based on the received user data, including the user's travel destination, budget, schedule, and emotional state.

[1239] Step 10:

[1240] Subject: Server

[1241] The server generates a travel plan optimized for the user based on the search results, including hotels, restaurants, and attractions with ratings and reviews, and reflects the user's emotional state.

[1242] Examples:

[1243] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[1244] Step 11:

[1245] Subject: Server

[1246] The server sends the generated travel plan to the terminal in JSON format or similar.

[1247] Step 12:

[1248] Subject: Terminal

[1249] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[1250] Step 13:

[1251] Subject: User

[1252] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact details, etc.) on the device interface.

[1253] Step 14:

[1254] Subject: Terminal

[1255] The terminal sends the reservation information entered by the user to the server in a data format such as JSON.

[1256] Step 15:

[1257] Subject: Server

[1258] The server executes the reservation through the API of each application site based on the received reservation information. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1259] Step 16:

[1260] Subject: Server

[1261] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[1262] Step 17:

[1263] Subject: User

[1264] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[1265] Step 18:

[1266] Subject: Server

[1267] The server stores the received feedback information in a database and uses it for future plan generation. Emotional information is also recorded as feedback.

[1268] Step 19:

[1269] Subject: Server

[1270] The server evaluates the contribution of each participating company based on reviews, booking history, and user satisfaction, and prepares revenue distribution data based on this.

[1271] Example 2

[1272] 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."

[1273] Conventional travel planning systems typically collect and analyze user evaluation information to make suggestions, but they do not reflect the user's emotional state during the actual trip, which means they are unable to fully increase user satisfaction. Furthermore, the booking process and feedback collection process are cumbersome, and there are still issues with the overall system efficiency.

[1274] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recognizing the emotional state from the user's input information using an emotion engine, means for recording the recognized emotional state in a database and reflecting it in the generation of a travel plan, and means for presenting the generated travel plan to the user and collecting reservation information for the selected plan. This makes it possible to propose an optimal travel plan based on the user's emotional state, significantly improving user satisfaction.

[1275] "Rating information" refers to word-of-mouth, reviews, ratings, poster information, posting date and time, etc. collected from various rating sites and social media.

[1276] An "emotion engine" refers to software or hardware that analyzes user input data (text or voice) and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1277] "Interface" refers to the display screen and operating means through which users access the system and input information such as hobbies, preferences, schedule, budget, and travel destinations.

[1278] "Travel Plan" refers to a plan that includes suggestions for accommodation, places to eat, attractions, etc. based on the user's input information and perceived emotional state.

[1279] "Database" refers to a system for storing and managing collected evaluation information, emotional information, user input information, feedback, etc.

[1280] "Feedback" refers to the impressions and evaluation information provided by users after traveling or eating.

[1281] "Platform participating companies" refer to companies that provide information and services to the system and contribute to the operation of the system.

[1282] "Contribution" refers to the degree to which platform participating companies are evaluated based on the quality and quantity of evaluation information they provide to the system, the number of reservations processed, etc.

[1283] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system aims to improve customer satisfaction. The system of the present invention is made up of the following functions: server, terminal, and user.

[1284] 1. Collecting and converting evaluation information

[1285] The server periodically collects evaluation information using APIs or web scraping functions from various evaluation sites and social media. The collected data includes evaluation scores, comments, poster information, posting date and time, etc. The necessary information is extracted from the HTML data of the evaluation sites using the Python library "BeautifulSoup" and other tools.

[1286] The server then converts the collected rating information into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale, allowing data collected from different sites to be stored in a consistent format.

[1287] Finally, the server stores the rating information in a standardized format in a MySQL database, including the rating score, review content, site name, and posting date and time.

[1288] 2. Providing a user interface

[1289] When a user accesses the device, an interface is displayed for entering information such as travel destination, budget, schedule, hobbies, and preferences. This interface is built using HTML / CSS and JavaScript. Users can enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" in the text boxes.

[1290] 3. Emotion Recognition and Data Analysis

[1291] The device sends the data entered by the user and voice data to the emotion engine, which then analyzes the received data using, for example, IBM Watson's emotion analysis API, and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1292] The server records the emotion information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores information such as "Relaxed" in the "Emotional State" field.

[1293] 4. Analyzing user data and generating travel plans

[1294] The device sends the user's input criteria data and emotion information to the server. The server searches the database based on the received user criteria and emotion information to obtain matching rating information. The server then generates an optimal travel plan for the user based on the search results. This plan includes hotels, restaurants, and tourist attractions, each with its own rating and review content.

[1295] As a concrete example, if a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes a highly rated hot spring hotel and a quiet, relaxing place to eat.

[1296] 5. Reservation Procedure

[1297] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[1298] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1299] 6. Gathering feedback and improving the system

[1300] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[1301] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[1302] The system also has a means of evaluating the contribution of companies participating in the platform and distributing income. For example, a system is in place that gives higher contribution points to companies that provide more word-of-mouth information or receive more reservations.

[1303] Prompt Sentence Examples

[1304] "I want to relax. Can you plan a three-day hot spring trip starting September 10th? My budget is under 20,000 yen per person."

[1305] "I'm planning a family trip. Can you recommend some good places to eat? My budget is 30,000 yen."

[1306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1307] Step 1: Gather evaluation information

[1308] The server collects review information using APIs or web scraping functions from various review sites and social media. Specifically, it uses the Python library "BeautifulSoup" to parse HTML data from a specified URL and extract word-of-mouth information. The input is the URL of the review site and a query, and the output is review information such as rating points, comments, poster information, and posting date and time.

[1309] Step 2: Standardize data formats

[1310] The server converts the collected rating information into a standardized format. For example, it unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating. Specifically, it doubles each rating point to convert a 5-point rating into a 10-point rating. The input is the collected rating information, and the output is rating information in a standardized format.

[1311] Step 3: Save your data

[1312] The server stores the rating information in a standardized format in a database. Specifically, it uses a MySQL database to store records including rating points, review content, site name, and posting date and time. The input is rating information in a standardized format, and the output is the record stored in the database.

[1313] Step 4: Displaying the User Interface

[1314] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences. Specifically, it displays a web form built using HTML / CSS and JavaScript. The input is the user's access, and the output is the display of the input form.

[1315] Step 5: Entering User Data

[1316] The user inputs travel conditions (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface. For example, the user might enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" into text boxes. Input is the information the user types into the device, and output is the input data displayed on the device.

[1317] Step 6: Sending Emotion Data

[1318] The device sends the data and voice data entered by the user to the emotion engine. Specifically, the entered text data and voice data is sent to the IBM Watson emotion analysis API. The input is the user's input data, and the output is the data sent to the emotion engine.

[1319] Step 7: Recognize emotions

[1320] The emotion engine analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.). For example, it recognizes the "positive" emotion from the text "I want to relax." The input is the transmitted data, and the output is the recognized emotional state data.

[1321] Step 8: Storing Emotional Information

[1322] The server records the emotional information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores "Relaxed" in the "Emotional State" field. The input is the recognized emotional state data, and the output is the emotional information stored in the database.

[1323] Step 9: Sending condition data

[1324] The device sends the condition data and emotional information entered by the user to the server. Specifically, the user's condition data (e.g., travel destination, budget, schedule, hobbies, and preferences) and emotional information are sent via API. The input is the condition data and emotional information entered into the device, and the output is the data sent to the server.

[1325] Step 10: Search the database

[1326] The server searches the database based on the received user criteria and emotion information to retrieve matching rating information. Specifically, it uses an SQL query to search for records of hotels and tourist attractions that match the criteria. The input is the user's criteria data and emotion information, and the output is the search result records.

[1327] Step 11: Generate a travel plan

[1328] The server generates an optimal travel plan for the user based on the search results. Specifically, it creates a plan that includes highly rated hot spring hotels and quiet dining spots, and attaches their ratings and reviews. The input is the search result records, and the output is the generated travel plan.

[1329] Step 12: Present your travel plans

[1330] The terminal presents the generated itinerary to the user. Specifically, it generates a web page displaying the details of the itinerary and displays it to the user. The input is the itinerary sent from the server, and the output is the itinerary presented to the user.

[1331] Step 13: Enter reservation information

[1332] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The input is the user's personal information, and the output is the reservation information displayed on the terminal.

[1333] Step 14: Complete the booking process

[1334] The server processes reservations through the API of each application site based on the reservation information received from the user. Specifically, it uses the API of the travel reservation site to make reservations according to the specified conditions. The input is the user's reservation information, and the output is confirmation data that the reservation has been completed.

[1335] Step 15: Notification of reservation confirmation information

[1336] When the reservation is completed, the server sends the reservation confirmation information to the terminal and notifies the user. Specifically, it generates a reservation confirmation email and sends it to the user's email address. The input is the confirmation data of the reservation completion, and the output is the reservation confirmation information notified to the user.

[1337] Step 16: Submit a feedback request

[1338] After the trip or meal is completed, the server sends a feedback request message to the user. Specifically, it sends an automated email with the message "Please tell us what you thought of your trip." The input is the user's email address, and the output is the sent feedback request message.

[1339] Step 17: Submit and save your feedback

[1340] When a user submits feedback, the server stores the feedback in a database. Specifically, when a user fills out an input form and clicks the "Submit" button, the data is stored in a MySQL database. The input is the user's feedback, and the output is the feedback stored in the database.

[1341] Step 18: System Improvement

[1342] The server uses the collected feedback to improve the accuracy of future plan suggestions. Specifically, it adjusts the recommendation algorithm through feedback analysis and processes data to further increase user satisfaction. The input is the stored feedback, and the output is an improved algorithm and proposed plans.

[1343] (Application example 2)

[1344] 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."

[1345] When shopping online or planning trips and meals, it takes time and effort for users to collect reviews and find the best products and plans for themselves. Furthermore, conventional recommendation systems do not take into account the user's emotional state, making it difficult to improve customer satisfaction. Therefore, there is a need for systems that can easily find the best products and plans based on the user's emotional state and streamline the purchasing and reservation process.

[1346] 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.

[1347] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for saving the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a travel plan, means for presenting the generated travel plan to the user and collecting reservation information for the selected plan, means for completing the reservation in cooperation with each application site based on the reservation information, means for collecting feedback from the user after the trip or meal, means for saving the collected feedback in a database and using it for future plan proposals, means for evaluating the contributions of platform participating companies and distributing revenue, means for analyzing the user's emotional state using an emotion engine and saving it in a database together with the review information, means for generating product recommendation information based on the user's emotional state, means for presenting the generated recommendation information to the user and collecting purchase information for the selected product, and means for completing the purchase in cooperation with each sales site based on the purchase information. This allows users to easily find the best products and travel plans based on their emotional state and efficiently complete the purchase and reservation process.

[1348] "Evaluation information" refers to information such as evaluation scores and comments collected from various evaluation sites and social media.

[1349] A "unified format" is a data format that standardizes different evaluation scales and formats and converts them into a consistent format.

[1350] A "database" is a storage device for systematically storing collected and unified evaluation information and additional information.

[1351] An "interface" is a screen or element through which a user inputs information into a device or receives information from a system.

[1352] An "emotion engine" is a technology that analyzes user input information and voice data to recognize the user's emotional state.

[1353] "Recommendation information" is information that suggests optimal products, travel plans, etc. based on the user's hobbies, preferences, and emotional state.

[1354] "Reservation Information" refers to information including personal information and conditions necessary to reserve the plan or product selected by the user.

[1355] A "merchandise site" is a website or platform that offers products or services and accepts online purchases.

[1356] "Feedback" refers to information such as impressions, ratings, and opinions provided by users after traveling or using a product.

[1357] "Platform participating companies" are companies that provide evaluation information and services to this system and are involved in system operation.

[1358] The system of the present invention recommends optimal products and travel plans based on the user's hobbies, preferences, schedule, budget, and emotional state, and then efficiently processes the subsequent purchase and reservation procedures. Specific implementation methods of the system are described below.

[1359] 1. Collecting and converting evaluation information

[1360] The server periodically collects rating information using APIs or web scraping functions from various rating sites and social media. For example, information can be obtained using Python's BeautifulSoup or requests library. The collected data is converted into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale. The data is then stored in a relational database such as MySQL or PostgreSQL.

[1361] 2. Providing a user interface

[1362] The device uses a cross-platform UI framework such as Flutter to display an interface for users to enter their hobbies, preferences, schedule, budget, and emotional state. The device then sends the user's text input data to a natural language processing engine such as Google Dialogflow, which then receives the input information.

[1363] 3. Emotion Recognition and Data Analysis

[1364] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize the user's emotional state (e.g., joy, sadness, surprise, etc.). The analyzed emotion information is sent to a server and recorded in a database.

[1365] 4. Analyzing user data and generating recommendations

[1366] The server searches the database based on the user's input criteria and emotional information to retrieve matching rating information. This is done using data analysis tools such as Python, Pandas, and Elasticsearch. Based on the search results, an algorithm is run to generate products and travel plans that best fit the user's emotional state.

[1367] 5. Present the generated recommendation information and process purchases and reservations

[1368] The device presents the generated recommendation information to the user and collects purchase information for the products selected by the user and reservation information for the travel plan. The purchase or reservation information is sent to the server, and the purchase or reservation process is carried out via the API of each sales site or application site. Reservation or purchase confirmation information is sent to the device and notified to the user.

[1369] 6. Gathering feedback and improving the system

[1370] After a purchase or trip is completed, the server sends a message to the user requesting feedback. The user enters their feedback and the submitted information is stored in a database and used to propose plans for the next trip.

[1371] Hardware and software used

[1372] Server hardware: AWS EC2, RDS

[1373] Device hardware: iOS or Android device

[1374] Software: Python, BeautifulSoup, requests, Flutter, Google Dialogflow, IBM Watson, Google Cloud Natural Language API, Pandas, Elasticsearch, Django, SQLAlchemy, REST API

[1375] Specific examples

[1376] If a user is in an emotional state such as "I've been busy lately and want to relax," and enters the conditions "relaxation products," "budget of 5,000 yen or less," and "interested in aroma-related products," the system will recommend highly rated aroma diffusers and relaxation CDs.

[1377] Prompt Sentence Examples

[1378] Please recommend the best products to users whose current emotional state is "I want to be soothed," who are interested in "aroma-related products," and whose budget is "within 5,000 yen." Please select products that will help users relax, taking into account product reviews and sentiment analysis results.

[1379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1380] Step 1:

[1381] Collecting and converting evaluation information

[1382] The server periodically collects rating information using various rating sites, social media APIs, or web scraping functions. Specifically, it acquires information using Python's BeautifulSoup and requests libraries. Input data includes rating points, comments, poster information, posting date and time, etc. This is converted into a standardized format, and different rating scales (e.g., 5-point rating, 10-point rating, etc.) are unified and converted into a 10-point rating. The output data is rating information in a standardized format.

[1383] Step 2:

[1384] Saving rating information

[1385] The server stores the rating information in a unified format in a database. Specifically, it uses a relational database such as MySQL or PostgreSQL. The input data includes rating points, review content, site name, posting date and time, etc., and storing this data makes it easier to search and analyze later. The output includes structured rating information in the database.

[1386] Step 3:

[1387] Providing a user interface

[1388] The device uses Flutter to display an interface for users to input their hobbies, preferences, schedule, budget, and emotional state when accessed by the user. The input data is the condition information entered by the user, which is received and sent to the server. The output is the condition data entered by the user.

[1389] Step 4:

[1390] Emotion Recognition and Data Analysis

[1391] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize emotional states (e.g., joy, sadness, surprise, etc.). The input data is the user's text and voice data, and after analysis, emotional information is output and sent to the server.

[1392] Step 5:

[1393] Analyzing user data and generating recommendations

[1394] The server searches the database based on the input criteria data and emotion information to obtain matching rating information. It processes the data using data analysis tools such as Python, Pandas, and Elasticsearch. The input data are the user's criteria data and emotion information, and the output is recommendation information based on the user's emotional state.

[1395] Step 6:

[1396] Present generated recommendation information and process purchases and reservations

[1397] The terminal presents the user with recommended products and travel plans and receives the user's selection. Purchase information for the products and reservation information for the travel plans selected by the user is collected and sent from the terminal to the server. The output is the purchase information and reservation information selected by the user. Based on this information, the server processes the purchase and reservation via the APIs of each sales site and application site. Purchase confirmation and reservation confirmation information are sent to the terminal and notified to the user.

[1398] Step 7:

[1399] Gathering feedback and improving the system

[1400] After a purchase or trip is completed, the server sends a message to the user requesting feedback. When the user inputs and submits feedback, the information is stored in the database. The input data is the user's feedback, and the output data is the feedback information stored in the database. This allows for improved accuracy of future plan suggestions.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] [Fourth embodiment]

[1405] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1406] 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.

[1407] 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).

[1408] 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.

[1409] 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.

[1410] 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).

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] 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."

[1418] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan trips and meals. This system is made up of the following functions: server, terminal, and user.

[1419] 1. Collecting and converting evaluation information

[1420] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, posting date and time, etc.

[1421] The server centrally manages the collected evaluation information and converts it into a unified format. For example, it converts different evaluation scales such as 5-point and 10-point ratings into a 10-point rating. It also stores each evaluation information in a database.

[1422] 2. Providing a user interface

[1423] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, itinerary, and hobbies and preferences.

[1424] Users input search criteria through the device interface, such as the purpose of their trip, the area they want to visit, their budget, and the duration of their trip.

[1425] 3. Analyzing user data and generating travel plans

[1426] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[1427] The server then generates a travel plan that best suits the user based on the search results. This plan includes hotels, restaurants, and tourist attractions based on the user's preferences and budget. Each plan is accompanied by reviews and comments, making it easy for the user to understand.

[1428] Examples:

[1429] When a user enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server generates a plan that matches these conditions and suggests a travel plan that includes highly rated hotels and restaurants.

[1430] 4. Reservation Procedure

[1431] If the user checks the proposed plan and wishes to make a reservation, they enter the necessary information on the interface. The reservation information entered by the user is sent to the server via the terminal.

[1432] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1433] 5. Gathering feedback and improving the system

[1434] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[1435] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[1436] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[1437] ---

[1438] This system makes travel and dining planning efficient and fair, providing users with reliable information with minimal effort, simplifying the overall booking process, and enabling continuous improvement through feedback.

[1439] The processing flow will be explained below.

[1440] Step 1:

[1441] Subject: Server

[1442] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[1443] Step 2:

[1444] Subject: Server

[1445] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[1446] Step 3:

[1447] Subject: Server

[1448] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[1449] Step 4:

[1450] Subject: Terminal

[1451] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences.

[1452] Step 5:

[1453] Subject: User

[1454] The user enters the travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the device interface and clicks the "Submit" button.

[1455] Step 6:

[1456] Subject: Terminal

[1457] The terminal sends the information entered by the user to the server in a data format such as JSON.

[1458] Step 7:

[1459] Subject: Server

[1460] The server searches the database based on the received user conditions and retrieves matching evaluation information.

[1461] Step 8:

[1462] Subject: Server

[1463] The server generates a personalized itinerary for the user based on the search results, including hotels, dining options, and attractions, all with ratings and reviews.

[1464] Step 9:

[1465] Subject: Server

[1466] The server sends the generated travel plan to the terminal in JSON format or similar.

[1467] Step 10:

[1468] Subject: Terminal

[1469] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[1470] Step 11:

[1471] Subject: User

[1472] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the terminal.

[1473] Step 12:

[1474] Subject: Terminal

[1475] The terminal sends the reservation information entered by the user to the server in JSON format or similar.

[1476] Step 13:

[1477] Subject: Server

[1478] The server connects the received reservation information through the API of each application site and executes the reservation.

[1479] Step 14:

[1480] Subject: Server

[1481] When the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1482] Step 15:

[1483] Subject: Server

[1484] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[1485] Step 16:

[1486] Subject: User

[1487] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[1488] Step 17:

[1489] Subject: Server

[1490] The server stores the received feedback information in a database and uses it for subsequent plan generation.

[1491] Step 18:

[1492] Subject: Server

[1493] The server evaluates the contribution of each participating company based on reviews and booking history, and prepares revenue distribution data.

[1494] Example 1

[1495] 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."

[1496] Traditional travel and dining planning requires users to individually research multiple online review sites and social media, which can often be inefficient. Furthermore, the lack of a unified rating scale across different review sites makes it difficult to make proper comparisons. Furthermore, there are few systems that automatically generate optimal travel plans tailored to a user's specific needs and budget, and the booking process can be complicated and time-consuming. As a result, users often end up with unsatisfactory plans despite the significant effort required.

[1497] 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.

[1498] In this invention, the server includes: means for collecting review information from various review sites and social media; means for converting the collected review information into a unified format; means for saving the unified format review information in a database; means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget; means for searching the database for matching review information based on the input information and generating a travel plan; means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; means for completing the reservation by connecting with each application site based on the reservation information; means for collecting feedback from the user after the trip or meal; means for saving the collected feedback in a database and using it for future plan proposals; means for evaluating the contribution of platform participants and distributing revenue; means for using an API and web scraping to collect review information; and means for using a generative AI model to generate prompts based on the user's input information when generating a travel plan. This allows users to obtain efficient and accurate travel plans based on reliable information with little effort.

[1499] "Rating information" refers to data such as user ratings and comments, poster information, and posting date and time.

[1500] A "unified format" is a format that converts different evaluation scales into a common standard.

[1501] A "database" is a digital storage system for storing and managing evaluation information, feedback information, and the like.

[1502] An "interface" is a user interaction tool that allows users to input information such as hobbies, preferences, schedules, and budgets.

[1503] A "travel plan" is a plan including accommodations, places to eat, and tourist attractions that is generated based on information input by the user.

[1504] A "generative AI model" is an artificial intelligence algorithm that generates optimal travel plans based on user input information.

[1505] A "prompt sentence" is input text given to a generative AI model to guide the AI's response.

[1506] "Reservation Information" means the details required to reserve the travel plan selected by the User.

[1507] "Feedback" refers to ratings and comments provided by users after their travel or dining experiences.

[1508] "Contribution level" is an evaluation based on word-of-mouth information and number of reservations provided by companies participating in the platform.

[1509] "Web scraping" is a technique for automatically collecting data from web pages.

[1510] An "API" is an interface for exchanging functions and data between different software systems.

[1511] This invention is a system that collects and centrally manages word-of-mouth information from various rating sites and social media to help users efficiently plan trips and meals. This system is made up of a server, terminals, and user functions.

[1512] 1. Collecting and converting evaluation information

[1513] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. Specifically, it uses libraries such as Python's BeautifulSoup or Selenium to obtain data such as rating points, comments, poster information, and posting date and time from the Internet. If an API is provided, it is also possible to obtain the data directly using an HTTP request.

[1514] The server centrally manages the collected rating information and converts it into a unified format. Different rating scales, such as 5-point or 10-point ratings obtained from different rating sites, are converted into a common 10-point rating. This conversion is performed using the Python Pandas library, and the data is formatted in a unified format before being stored in a database.

[1515] 2. Providing a user interface

[1516] When a user accesses the device, it displays an interface built using HTML / CSS and JavaScript, providing a form for entering travel destination information, budget, itinerary, hobbies, and preferences.

[1517] Users enter search criteria through the device interface, such as "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," and then click the submit button.

[1518] 3. Analyzing user data and generating travel plans

[1519] The terminal sends the data entered by the user to the server. The terminal uses JavaScript AJAX to send the data entered by the user asynchronously to the server.

[1520] The server parses the user data and searches the database for matching reviews. It uses the SQLAlchemy library to execute database queries and extract data that matches the user's criteria.

[1521] The server generates the optimal travel plan for the user based on the search results. It uses machine learning libraries such as PyTorch and TensorFlow to provide prompt sentences to a generative AI model to generate the optimal plan.

[1522] Examples:

[1523] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model:

[1524] text

[1525] Purpose of trip: Hot spring trip

[1526] Budget: Under 20,000 yen per person

[1527] Dates: 3 days from September 10th

[1528] Please suggest a plan that includes highly rated hotels and restaurants.

[1529] 4. Reservation Procedure

[1530] The user checks the proposed plan and, if they wish to make a reservation, enters the reservation information on the interface. The user enters the reservation information in the form and clicks the submit button.

[1531] The server processes the reservation via the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is complete, the server sends reservation confirmation information to the terminal and notifies the user.

[1532] 5. Gathering feedback and improving the system

[1533] The server sends a feedback request message to the user after the trip or meal is completed, sending an email and providing a link to the feedback form.

[1534] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate subsequent plans.

[1535] The introduction of this system will enable travel and meal planning to be carried out efficiently and based on reliable information, allowing users to enjoy optimal plans with minimal effort. In addition, it will enable companies to properly evaluate and reflect their contributions, improving the overall quality of services.

[1536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1537] Step 1:

[1538] The server collects rating information from various rating sites and social media. This collection is done using APIs or web scraping. Specifically, it uses Python's BeautifulSoup and Selenium to periodically retrieve data such as rating points, comments, poster information, and posting date and time. The input is the rating site or social media, and the output is a collection of the retrieved rating information.

[1539] Step 2:

[1540] The server converts the collected rating information into a unified format. Different rating scales, such as 5-point or 10-point ratings, obtained from different sites are converted into a 10-point rating. Specifically, the data is converted and unified using the Python Pandas library. The input is the collected rating information, and the output is the converted rating information in a unified format.

[1541] Step 3:

[1542] The server saves the rating information in a unified format to a database. It connects to the database using the SQLAlchemy library and saves the rating information. The input is the converted rating information in the unified format, and the output is the data saved in the database.

[1543] Step 4:

[1544] The terminal displays an interface when accessed by the user. The user interface is built using HTML / CSS and JavaScript and includes forms for entering travel destination information, budget, itinerary, hobbies, and preferences. The input is the information accessed by the user, and the output is the interface that is displayed.

[1545] Step 5:

[1546] The user inputs search criteria through the terminal interface. For example, "hot spring trip," "budget under 20,000 yen per person," and "3 days starting September 10th," and then clicks the send button. The input is the user's search criteria, and the output is the submitted search criteria data.

[1547] Step 6:

[1548] The terminal sends the data entered by the user to the server. Using JavaScript AJAX, the user's input data is sent asynchronously to the server. The input is the user's search criteria data, and the output is the data sent to the server.

[1549] Step 7:

[1550] The server parses the user data and searches the database for matching reviews. It uses SQLAlchemy to execute database queries and extract data that matches the user's criteria. The input is the user's search criteria data, and the output is the search results.

[1551] Step 8:

[1552] The server generates the optimal travel plan for the user based on the search results. Using machine learning libraries such as PyTorch and TensorFlow, the server generates the optimal plan by providing prompts to the generative AI model. The specific prompts are shown below.

[1553] Examples:

[1554] Based on the conditions entered by the user, the system will suggest travel plans that include highly rated hotels and restaurants. The following is an example of a prompt sentence to be input into the generative AI model.

[1555] text

[1556] Purpose of trip: Hot spring trip

[1557] Budget: Under 20,000 yen per person

[1558] Dates: 3 days from September 10th

[1559] Please suggest a plan that includes highly rated hotels and restaurants.

[1560] Step 9:

[1561] If the user checks the proposed plan and wishes to make a reservation, they enter their reservation information on the interface. The user enters the reservation information into the form and clicks the submit button. The input is the user's reservation information, and the output is the submitted reservation information data.

[1562] Step 10:

[1563] The server processes reservations through the API of each application site based on the received reservation information. It uses the Requests library to send an API request and confirm the reservation. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user. The input is the user's reservation information, and the output is reservation confirmation information.

[1564] Step 11:

[1565] The server sends a feedback request message to the user after the trip or meal is completed. It sends an email and provides a link to the feedback form. The input is the trip or meal completion information, and the output is the feedback request message.

[1566] Step 12:

[1567] When a user submits feedback, the server stores the feedback in a database. To improve the accuracy of future plan proposals, the feedback data is stored in the database and used to generate future plans. The input is the user's feedback, and the output is the feedback stored in the database.

[1568] (Application example 1)

[1569] 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."

[1570] Conventional food delivery systems have difficulty comprehensively collecting word-of-mouth information from a wide range of review sites and social media to propose optimal ordering plans based on users' preferences and budgets. Furthermore, because the information provided depends on the standards of each review site, the system relies on inconsistent reviews, making it difficult to propose accurate plans. Furthermore, continuous improvement of the system and fair revenue distribution are difficult due to insufficient collection of feedback after orders and evaluation of the contributions of platform participants.

[1571] 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.

[1572] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for storing the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a food order plan, means for presenting the generated food order plan to the user and collecting information on selected orders, means for completing the order in cooperation with each delivery service based on the order information, means for collecting feedback from the user after the food order is placed, means for storing the collected feedback in a database and using it for future proposals, and means for evaluating the contributions of platform participants and distributing revenue. This allows for the proposal of an optimal food order plan based on user requests, maintains consistency in review information, and also allows for post-order feedback and evaluation of the contributions of businesses.

[1573] "Evaluation information" refers to information such as user-provided evaluation points, comments, poster information, and posting date and time, which is collected from various evaluation sites and social media.

[1574] A "unified format" is a data format that converts evaluation information provided on different evaluation scales and formats into a form that can be compared using consistent standards.

[1575] A "database" is an information storage system for systematically storing and managing collected and converted evaluation information, user input information, feedback, etc.

[1576] An "interface" is an operation screen or input form provided for users to input information such as hobbies, preferences, schedules, and budgets.

[1577] The "Food Ordering Plan" is an optimal delivery plan based on the user's input information, including suggested delivery stores and menus, reviews, ordering procedures, etc.

[1578] "Order Information" refers to data required for the ordering process based on the food ordering plan selected by the user, such as the type of food, the number of items ordered, the delivery address, and contact information.

[1579] "Feedback" refers to reaction information such as impressions, ratings, and satisfaction levels provided by users after ordering food.

[1580] "Platform participating businesses" are companies and stores that participate in the food delivery system and provide evaluation information and delivery services.

[1581] "Contribution level" refers to the degree of contribution to the system, calculated based on the quality of services provided by platform participants, word-of-mouth reviews, number of orders, etc.

[1582] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media in order to efficiently plan food delivery. This system is made up of the following functions: server, terminal, and user.

[1583] 1. Collecting and converting evaluation information

[1584] The server periodically collects rating information from various rating sites and social media using APIs or web scraping. The collected data includes rating points, comments, poster information, and posting date and time. Beautiful Soup is commonly used for web scraping. The collected data is then converted into a unified format (for example, converting different rating scales into a 10-point rating system).

[1585] 2. Data storage and management

[1586] The server stores the rating information in a standardized format in a database. This database stores collected reviews, user input, and feedback. It can be managed using a relational database service such as Amazon RDS.

[1587] 3. Providing a user interface

[1588] When accessed by a user, the terminal displays an interface that includes a form for inputting delivery type, budget, cuisine type, etc. Users can input search criteria through the terminal interface and plan specific orders.

[1589] 4. Analyzing user data and generating order plans

[1590] The terminal sends the data entered by the user to the server. The server analyzes the user data and searches for matching reviews in the database. The server generates the optimal food ordering plan for the user based on the search results. This plan includes menus and restaurants based on the user's tastes, preferences, and budget. Each plan is accompanied by reviews and comments, which are provided to the user in an easy-to-understand manner.

[1591] Examples:

[1592] When a user enters the criteria "sushi," "budget under 5,000 yen," and "high reviews," the server generates a plan that matches these criteria and suggests delivery restaurants and menus with high reviews.

[1593] 5. Order Processing

[1594] If the user reviews the proposed plan and wishes to place an order, they enter the necessary information on the interface. The order information entered by the user is sent to the server via the terminal. The server processes the order through the API of each delivery service based on the order information received from the user. Once the order is completed, the server sends order confirmation information to the terminal and notifies the user.

[1595] 6. Gathering feedback and improving the system

[1596] After the food order is completed, the server sends the user a message requesting feedback. The message includes a link to a feedback form, which the user can click to enter their thoughts. Once the user submits their feedback, the server stores it in its database, which can improve the accuracy of future suggestions.

[1597] 7. Evaluation of Platform Participants and Revenue Distribution

[1598] The server evaluates the contribution of the businesses participating in the platform and distributes revenue accordingly. For example, businesses that provide more word-of-mouth information or receive more orders are given higher contribution ratings, enabling fair revenue distribution.

[1599] This system allows users to obtain reliable information with minimal effort, simplifies the delivery ordering process, and allows for continuous improvement of the system through feedback.

[1600] Example prompt sentence:

[1601] "I'm looking for a sushi delivery service. My budget is under 5,000 yen. Can you recommend a place with good reviews?"

[1602] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1603] Step 1:

[1604] Collecting and converting evaluation information

[1605] The server periodically collects evaluation information from various evaluation sites and social media using APIs or web scraping.

[1606] Input: URLs of rating sites, social media, API keys, etc.

[1607] Data processing: Using Python scripts and Beautiful Soup, we extract the rating, comments, author information, and posting date and time from each page.

[1608] Output: Standardized format of the evaluation information data, including the converted evaluation scores into a 10-point scale.

[1609] Step 2:

[1610] Data storage and management

[1611] The server stores the collected and converted rating information in a database.

[1612] Input: Evaluation information data in a uniform format.

[1613] Data Computation and Storage: Use a relational database such as Amazon RDS to store the evaluation information in an organized manner.

[1614] Output: Evaluation information data stored in a database.

[1615] Step 3:

[1616] Providing a user interface

[1617] The terminal displays the interface when accessed by the user.

[1618] Input: User access.

[1619] How it works: It displays an interface built in Swift and Kotlin where users can input delivery type, budget, and cuisine type.

[1620] Output: The search criteria data entered by the user.

[1621] Step 4:

[1622] Analyzing user data and generating order plans

[1623] The terminal sends the data entered by the user to the server, which analyzes the user data and searches the database for matching reviews.

[1624] Input: The search criteria data entered by the user.

[1625] Data calculation: Python scripts are used to search the database for matching reviews, and a search algorithm is used to generate the optimal food ordering plan.

[1626] Output: Optimal food ordering plan data.

[1627] Step 5:

[1628] Checkout

[1629] The user reviews the proposed plan and, if he / she wishes to place an order, enters the information required for the order on the interface.

[1630] Input: Optimal food ordering plan data and user order information.

[1631] Operation: Order information is sent to the server, and the order is processed on the server. An external API is used to connect with the delivery service.

[1632] Output: Order confirmation information.

[1633] Step 6:

[1634] Feedback collection and system improvement

[1635] The server will send a feedback request message to the user after the food order is completed, and once the user submits the feedback, the server will store the feedback in the database.

[1636] Input: Order confirmation information and user feedback information.

[1637] Data storage: Collected feedback information is stored in a database.

[1638] Output: Feedback data.

[1639] Step 7:

[1640] Evaluation of platform participants and revenue distribution

[1641] The server evaluates the contribution of the platform participants and distributes the revenue.

[1642] Input: Collected rating information, order data, feedback data.

[1643] Data calculation: Using a contribution evaluation algorithm, the contribution of each business operator is calculated and the percentage of revenue distribution is determined.

[1644] Output: Income distribution data.

[1645] 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.

[1646] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. It also combines an emotion engine that recognizes user emotions to improve customer satisfaction. This system is comprised of the following functions: server, terminal, and user.

[1647] 1. Collecting and converting evaluation information

[1648] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[1649] The server converts the collected rating information into a standardized format and unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating.

[1650] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[1651] 2. Providing a user interface

[1652] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, etc. The device also sends the user's text input and voice data to the emotion engine.

[1653] The user inputs travel conditions (e.g., destination, budget, schedule, hobbies, etc.) through the terminal interface or by voice input.

[1654] 3. Emotion Recognition and Data Analysis

[1655] The device sends the user's input data and voice data to the emotion engine, which analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1656] The server records the emotion information sent from the emotion engine in a database and reflects it in generating travel plans for the user. For example, it may suggest plans that allow the user to relax or stay active based on the emotion information.

[1657] 4. Analyzing user data and generating travel plans

[1658] The terminal transmits the condition data and emotion information input by the user to the server.

[1659] The server searches the database based on the received user conditions and emotion information, and retrieves matching evaluation information.

[1660] The server then generates a personalized itinerary for the user based on the search results. The itinerary includes hotels, restaurants, and attractions, each with ratings and reviews. Each itinerary reflects the user's emotional state to ensure a context-optimized experience.

[1661] Examples:

[1662] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[1663] 5. Reservation Procedure

[1664] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[1665] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1666] 6. Gathering feedback and improving the system

[1667] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[1668] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[1669] The system also has a means of evaluating the contribution of companies participating in the platform and distributing revenue. For example, companies that provide more word-of-mouth information or receive more reservations will be given higher contribution points.

[1670] ---

[1671] The system thus constructed ensures efficient and fair travel and dining planning, provides an optimal experience based on the user's emotional state, simplifies the overall booking process by providing reliable information with minimal effort, and continuously improves the system through feedback.

[1672] The processing flow will be explained below.

[1673] Step 1:

[1674] Subject: Server

[1675] The server periodically collects evaluation information using APIs or web scraping functions of various evaluation sites and social media. The collected data includes evaluation points, comments, poster information, posting date and time, etc.

[1676] Step 2:

[1677] Subject: Server

[1678] The server converts the collected rating information into a standardized format, for example, converting different rating scales such as 5-point and 10-point scales into a 10-point scale.

[1679] Step 3:

[1680] Subject: Server

[1681] The server stores the evaluation information in a database in a standardized format, including the evaluation score, review content, site name, posting date and time, etc.

[1682] Step 4:

[1683] Subject: Terminal

[1684] When accessed by a user, the device displays an interface that includes a form for entering information such as travel destination, budget, schedule, and hobbies and preferences.

[1685] Step 5:

[1686] Subject: User

[1687] Users input search criteria (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface, and also express their feelings through text or voice.

[1688] Step 6:

[1689] Subject: Terminal

[1690] The device sends the search criteria and voice data entered by the user to the emotion engine, which then analyzes the received text and voice data to recognize the user's emotions.

[1691] Step 7:

[1692] Subject: Server

[1693] The server records the emotion information sent from the emotion engine in a database and reflects it in generating a travel plan for the user.

[1694] Step 8:

[1695] Subject: Terminal

[1696] The device sends the information entered by the user and emotional information to the server in a data format such as JSON.

[1697] Step 9:

[1698] Subject: Server

[1699] The server searches the database for matching reviews based on the received user data, including the user's travel destination, budget, schedule, and emotional state.

[1700] Step 10:

[1701] Subject: Server

[1702] The server generates a travel plan optimized for the user based on the search results, including hotels, restaurants, and attractions with ratings and reviews, and reflects the user's emotional state.

[1703] Examples:

[1704] If a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "three days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes highly rated hot spring hotels and quiet, relaxing places to eat.

[1705] Step 11:

[1706] Subject: Server

[1707] The server sends the generated travel plan to the terminal in JSON format or similar.

[1708] Step 12:

[1709] Subject: Terminal

[1710] The device displays the travel plans received from the server to the user, along with detailed information and ratings for each plan.

[1711] Step 13:

[1712] Subject: User

[1713] Once the user selects the desired plan, they enter the personal information required for the reservation (e.g., name, contact details, etc.) on the device interface.

[1714] Step 14:

[1715] Subject: Terminal

[1716] The terminal sends the reservation information entered by the user to the server in a data format such as JSON.

[1717] Step 15:

[1718] Subject: Server

[1719] The server executes the reservation through the API of each application site based on the received reservation information. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1720] Step 16:

[1721] Subject: Server

[1722] The server sends a feedback request message to the user after the trip or meal is completed, and the message includes a link to a feedback form.

[1723] Step 17:

[1724] Subject: User

[1725] Users access the feedback form, enter their thoughts about their trip or meal, and click the "Submit" button.

[1726] Step 18:

[1727] Subject: Server

[1728] The server stores the received feedback information in a database and uses it for future plan generation. Emotional information is also recorded as feedback.

[1729] Step 19:

[1730] Subject: Server

[1731] The server evaluates the contribution of each participating company based on reviews, booking history, and user satisfaction, and prepares revenue distribution data based on this.

[1732] Example 2

[1733] 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."

[1734] Conventional travel planning systems typically collect and analyze user evaluation information to make suggestions, but they do not reflect the user's emotional state during the actual trip, which means they are unable to fully increase user satisfaction. Furthermore, the booking process and feedback collection process are cumbersome, and there are still issues with the overall system efficiency.

[1735] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recognizing the emotional state from the user's input information using an emotion engine, means for recording the recognized emotional state in a database and reflecting it in the generation of a travel plan, and means for presenting the generated travel plan to the user and collecting reservation information for the selected plan. This makes it possible to propose an optimal travel plan based on the user's emotional state, significantly improving user satisfaction.

[1736] "Rating information" refers to word-of-mouth, reviews, ratings, poster information, posting date and time, etc. collected from various rating sites and social media.

[1737] An "emotion engine" refers to software or hardware that analyzes user input data (text or voice) and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1738] "Interface" refers to the display screen and operating means through which users access the system and input information such as hobbies, preferences, schedule, budget, and travel destinations.

[1739] "Travel Plan" refers to a plan that includes suggestions for accommodation, places to eat, attractions, etc. based on the user's input information and perceived emotional state.

[1740] "Database" refers to a system for storing and managing collected evaluation information, emotional information, user input information, feedback, etc.

[1741] "Feedback" refers to the impressions and evaluation information provided by users after traveling or eating.

[1742] "Platform participating companies" refer to companies that provide information and services to the system and contribute to the operation of the system.

[1743] "Contribution" refers to the degree to which platform participating companies are evaluated based on the quality and quantity of evaluation information they provide to the system, the number of reservations processed, etc.

[1744] The system of the present invention collects and centrally manages word-of-mouth information from various review sites and social media to enable efficient travel and dining planning. Furthermore, by combining it with an emotion engine that recognizes user emotions, the system aims to improve customer satisfaction. The system of the present invention is made up of the following functions: server, terminal, and user.

[1745] 1. Collecting and converting evaluation information

[1746] The server periodically collects evaluation information using APIs or web scraping functions from various evaluation sites and social media. The collected data includes evaluation scores, comments, poster information, posting date and time, etc. The necessary information is extracted from the HTML data of the evaluation sites using the Python library "BeautifulSoup" and other tools.

[1747] The server then converts the collected rating information into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale, allowing data collected from different sites to be stored in a consistent format.

[1748] Finally, the server stores the rating information in a standardized format in a MySQL database, including the rating score, review content, site name, and posting date and time.

[1749] 2. Providing a user interface

[1750] When a user accesses the device, an interface is displayed for entering information such as travel destination, budget, schedule, hobbies, and preferences. This interface is built using HTML / CSS and JavaScript. Users can enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" in the text boxes.

[1751] 3. Emotion Recognition and Data Analysis

[1752] The device sends the data entered by the user and voice data to the emotion engine, which then analyzes the received data using, for example, IBM Watson's emotion analysis API, and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.).

[1753] The server records the emotion information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores information such as "Relaxed" in the "Emotional State" field.

[1754] 4. Analyzing user data and generating travel plans

[1755] The device sends the user's input criteria data and emotion information to the server. The server searches the database based on the received user criteria and emotion information to obtain matching rating information. The server then generates an optimal travel plan for the user based on the search results. This plan includes hotels, restaurants, and tourist attractions, each with its own rating and review content.

[1756] As a concrete example, if a user is in an emotional state of "I want to relax" and enters the conditions "hot spring trip," "budget of less than 20,000 yen per person," and "3 days from September 10th," the server will generate a plan that matches these conditions and suggest a travel plan that includes a highly rated hot spring hotel and a quiet, relaxing place to eat.

[1757] 5. Reservation Procedure

[1758] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The reservation information entered by the user is sent to the server via the terminal.

[1759] The server processes the reservation via the API of each application site based on the reservation information received from the user. Once the reservation is completed, the server sends reservation confirmation information to the terminal and notifies the user.

[1760] 6. Gathering feedback and improving the system

[1761] After the trip or meal is completed, the server sends the user a message requesting feedback, which includes a link to a feedback form that the user can click to enter their thoughts.

[1762] When users submit feedback, the server stores it in a database, which helps improve the accuracy of future plan suggestions.

[1763] The system also has a means of evaluating the contribution of companies participating in the platform and distributing income. For example, a system is in place that gives higher contribution points to companies that provide more word-of-mouth information or receive more reservations.

[1764] Prompt Sentence Examples

[1765] "I want to relax. Can you plan a three-day hot spring trip starting September 10th? My budget is under 20,000 yen per person."

[1766] "I'm planning a family trip. Can you recommend some good places to eat? My budget is 30,000 yen."

[1767] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1768] Step 1: Gather evaluation information

[1769] The server collects review information using APIs or web scraping functions from various review sites and social media. Specifically, it uses the Python library "BeautifulSoup" to parse HTML data from a specified URL and extract word-of-mouth information. The input is the URL of the review site and a query, and the output is review information such as rating points, comments, poster information, and posting date and time.

[1770] Step 2: Standardize data formats

[1771] The server converts the collected rating information into a standardized format. For example, it unifies different rating scales (e.g., 5-point rating, 10-point rating, etc.) into a 10-point rating. Specifically, it doubles each rating point to convert a 5-point rating into a 10-point rating. The input is the collected rating information, and the output is rating information in a standardized format.

[1772] Step 3: Save your data

[1773] The server stores the rating information in a standardized format in a database. Specifically, it uses a MySQL database to store records including rating points, review content, site name, and posting date and time. The input is rating information in a standardized format, and the output is the record stored in the database.

[1774] Step 4: Displaying the User Interface

[1775] When a user accesses the device, it displays an interface for entering information such as travel destination, budget, schedule, hobbies, and preferences. Specifically, it displays a web form built using HTML / CSS and JavaScript. The input is the user's access, and the output is the display of the input form.

[1776] Step 5: Entering User Data

[1777] The user inputs travel conditions (e.g., travel destination, budget, schedule, hobbies, etc.) through the device interface. For example, the user might enter information such as "Okinawa," "30,000 yen," "3 days from May 1st," and "beach resort" into text boxes. Input is the information the user types into the device, and output is the input data displayed on the device.

[1778] Step 6: Sending Emotion Data

[1779] The device sends the data and voice data entered by the user to the emotion engine. Specifically, the entered text data and voice data is sent to the IBM Watson emotion analysis API. The input is the user's input data, and the output is the data sent to the emotion engine.

[1780] Step 7: Recognize emotions

[1781] The emotion engine analyzes the received data and recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.). For example, it recognizes the "positive" emotion from the text "I want to relax." The input is the transmitted data, and the output is the recognized emotional state data.

[1782] Step 8: Storing Emotional Information

[1783] The server records the emotional information sent from the emotion engine in a database and reflects it in the generation of the user's travel plan. Specifically, it stores "Relaxed" in the "Emotional State" field. The input is the recognized emotional state data, and the output is the emotional information stored in the database.

[1784] Step 9: Sending condition data

[1785] The device sends the condition data and emotional information entered by the user to the server. Specifically, the user's condition data (e.g., travel destination, budget, schedule, hobbies, and preferences) and emotional information are sent via API. The input is the condition data and emotional information entered into the device, and the output is the data sent to the server.

[1786] Step 10: Search the database

[1787] The server searches the database based on the received user criteria and emotion information to retrieve matching rating information. Specifically, it uses an SQL query to search for records of hotels and tourist attractions that match the criteria. The input is the user's criteria data and emotion information, and the output is the search result records.

[1788] Step 11: Generate a travel plan

[1789] The server generates an optimal travel plan for the user based on the search results. Specifically, it creates a plan that includes highly rated hot spring hotels and quiet dining spots, and attaches their ratings and reviews. The input is the search result records, and the output is the generated travel plan.

[1790] Step 12: Present your travel plans

[1791] The terminal presents the generated itinerary to the user. Specifically, it generates a web page displaying the details of the itinerary and displays it to the user. The input is the itinerary sent from the server, and the output is the itinerary presented to the user.

[1792] Step 13: Enter reservation information

[1793] If the user checks the proposed plan and wishes to make a reservation, they enter the personal information required for the reservation (e.g., name, contact information, etc.) on the interface. The input is the user's personal information, and the output is the reservation information displayed on the terminal.

[1794] Step 14: Complete the booking process

[1795] The server processes reservations through the API of each application site based on the reservation information received from the user. Specifically, it uses the API of the travel reservation site to make reservations according to the specified conditions. The input is the user's reservation information, and the output is confirmation data that the reservation has been completed.

[1796] Step 15: Notification of reservation confirmation information

[1797] When the reservation is completed, the server sends the reservation confirmation information to the terminal and notifies the user. Specifically, it generates a reservation confirmation email and sends it to the user's email address. The input is the confirmation data of the reservation completion, and the output is the reservation confirmation information notified to the user.

[1798] Step 16: Submit a feedback request

[1799] After the trip or meal is completed, the server sends a feedback request message to the user. Specifically, it sends an automated email with the message "Please tell us what you thought of your trip." The input is the user's email address, and the output is the sent feedback request message.

[1800] Step 17: Submit and save your feedback

[1801] When a user submits feedback, the server stores the feedback in a database. Specifically, when a user fills out an input form and clicks the "Submit" button, the data is stored in a MySQL database. The input is the user's feedback, and the output is the feedback stored in the database.

[1802] Step 18: System Improvement

[1803] The server uses the collected feedback to improve the accuracy of future plan suggestions. Specifically, it adjusts the recommendation algorithm through feedback analysis and processes data to further increase user satisfaction. The input is the stored feedback, and the output is an improved algorithm and proposed plans.

[1804] (Application example 2)

[1805] 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 robot 414 will be referred to as a "terminal."

[1806] When shopping online or planning trips and meals, it takes time and effort for users to collect reviews and find the best products and plans for themselves. Furthermore, conventional recommendation systems do not take into account the user's emotional state, making it difficult to improve customer satisfaction. Therefore, there is a need for systems that can easily find the best products and plans based on the user's emotional state and streamline the purchasing and reservation process.

[1807] 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.

[1808] In this invention, the server includes means for collecting review information from various review sites and social media, means for converting the collected review information into a unified format, means for saving the unified format review information in a database, means for providing an interface for inputting a user's hobbies, preferences, schedule, and budget, means for searching the database for matching review information based on the input information and generating a travel plan, means for presenting the generated travel plan to the user and collecting reservation information for the selected plan, means for completing the reservation in cooperation with each application site based on the reservation information, means for collecting feedback from the user after the trip or meal, means for saving the collected feedback in a database and using it for future plan proposals, means for evaluating the contributions of platform participating companies and distributing revenue, means for analyzing the user's emotional state using an emotion engine and saving it in a database together with the review information, means for generating product recommendation information based on the user's emotional state, means for presenting the generated recommendation information to the user and collecting purchase information for the selected product, and means for completing the purchase in cooperation with each sales site based on the purchase information. This allows users to easily find the best products and travel plans based on their emotional state and efficiently complete the purchase and reservation process.

[1809] "Evaluation information" refers to information such as evaluation scores and comments collected from various evaluation sites and social media.

[1810] A "unified format" is a data format that standardizes different evaluation scales and formats and converts them into a consistent format.

[1811] A "database" is a storage device for systematically storing collected and unified evaluation information and additional information.

[1812] An "interface" is a screen or element through which a user inputs information into a device or receives information from a system.

[1813] An "emotion engine" is a technology that analyzes user input information and voice data to recognize the user's emotional state.

[1814] "Recommendation information" is information that suggests optimal products, travel plans, etc. based on the user's hobbies, preferences, and emotional state.

[1815] "Reservation Information" refers to information including personal information and conditions necessary to reserve the plan or product selected by the user.

[1816] A "merchandise site" is a website or platform that offers products or services and accepts online purchases.

[1817] "Feedback" refers to information such as impressions, ratings, and opinions provided by users after traveling or using a product.

[1818] "Platform participating companies" are companies that provide evaluation information and services to this system and are involved in system operation.

[1819] The system of the present invention recommends optimal products and travel plans based on the user's hobbies, preferences, schedule, budget, and emotional state, and then efficiently processes the subsequent purchase and reservation procedures. Specific implementation methods of the system are described below.

[1820] 1. Collecting and converting evaluation information

[1821] The server periodically collects rating information using APIs or web scraping functions from various rating sites and social media. For example, information can be obtained using Python's BeautifulSoup or requests library. The collected data is converted into a standardized format, unifying different rating scales (e.g., 5-point scale, 10-point scale, etc.) into a 10-point scale. The data is then stored in a relational database such as MySQL or PostgreSQL.

[1822] 2. Providing a user interface

[1823] The device uses a cross-platform UI framework such as Flutter to display an interface for users to enter their hobbies, preferences, schedule, budget, and emotional state. The device then sends the user's text input data to a natural language processing engine such as Google Dialogflow, which then receives the input information.

[1824] 3. Emotion Recognition and Data Analysis

[1825] The device sends the text and voice data entered by the user to the emotion engine, which uses IBM Watson and Google Cloud Natural Language APIs to recognize the user's emotional state (e.g., joy, sadness, surprise, etc.). The analyzed emotion information is sent to a server and recorded in a database.

[1826] 4. Analyzing user data and generating recommendations

[1827] The server searches the database based on the user's input criteria and emotional information to retrieve matching rating information. This is done using data analysis tools such as Python, Pandas, and Elasticsearch. Based on the search results, an algorithm is run to generate products and travel plans that best fit the user's emotional state.

[1828] 5. Present the generated recommendation information and process purchases and reservations

[1829] The device presents the generated recommendation information to the user and collects purchase information for the products selected by the user and reservation information for the travel plan. The purchase or reservation information is sent to the server, and the purchase or reservation process is carried out via the API of each sales site or application site. Reservation or purchase confirmation information is sent to the device and notified to the user.

[1830] 6. Gathering feedback and improving the system

[1831] After a purchase or trip is completed, the server sends a message to the user requesting feedback. The user enters their feedback and th...

Claims

1. A means of collecting evaluation information from various evaluation sites and social media; a means of converting the collected evaluation information into a uniform format; a means for storing the evaluation information in a database in a uniform format; A means for providing an interface for inputting a user's preferences, schedule, and budget; A means for searching a database for matching rating information based on input information and generating a travel plan; A means for presenting the generated travel plan to the user and collecting reservation information for the selected plan; A means to complete reservations by linking with each application site based on reservation information, A means of collecting feedback from users after their trip or meal, and The collected feedback will be saved in a database and used for future plan proposals. A means to evaluate the contribution of platform participants and distribute revenue, A system including:

2. The system of claim 1 further comprising an algorithm for analyzing user input information and proposing an optimal travel plan.

3. 2. The system according to claim 1, further comprising means for notifying the user of reservation confirmation information when the travel plan reservation is completed.

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